Circular Dichroism: Theory and Spectroscopy: Theory and Spectroscopy [1 ed.] 9781612091990, 9781611225228

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Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers, Nova

Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

BIOCHEMISTRY RESEARCH TRENDS

CIRCULAR DICHROISM

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THEORY AND SPECTROSCOPY

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Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

BIOCHEMISTRY RESEARCH TRENDS

CIRCULAR DICHROISM THEORY AND SPECTROSCOPY

DAVID S. RODGERS Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

EDITOR

Nova Science Publishers, Inc. New York Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

Copyright © 2012 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

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Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Circular dichroism : theory and spectroscopy / editor, David S. Rodgers. p. ; cm. Includes bibliographical references and index. ISBN:  (eBook)

1. Circular dichroism. 2. DNA-binding proteins. I. Rodgers, David S. [DNLM: 1. Circular Dichroism. 2. DNA--metabolism. 3. DNA-Binding Proteins--metabolism. 4. Protein Conformation. QD 473] QP519.9.C57C58 2011 541.7--dc22 2010041295

Published by Nova Science Publishers, Inc. † New York Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

CONTENTS Preface Chapter 1

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Chapter 2

vii The CD Spectra of Double-Stranded DNA Liquid-Crystalline Dispersions Yu. M. Yevdokimov, V. I. Salyano, S. G. Skuridin, S. V. Semenov and O. N. Kompanets Vibrational Circular Dichroism Studies of Biological Macromolecules and Their Complexes Alexander M. Polyanichko, Valery V. Andrushchenko, Petr Bouř and Helmut Wieser

Chapter 3

Magnetic Circular Dichroism in Electron Microscopy Ján Rusz, Stefano Rubino, Klaus Leifer, Hans Lidbaum, Peter M. Oppeneer, Anders Johansson and Olle Eriksson

Chapter 4

Application of Circular Dichroism to Lipoproteins: Structure, Stability and Remodeling of Good and Bad Cholesterol Xuan Gao, Shobini Jayaraman, Jeremiah Wally, Madhumita Guha, Mengxiao Lu, David Atkinson and Olga Gursky

Chapter 5

Chapter 6

Chapter 7

Chapter 8

1

67

127

175

The Use of Circular Dichroism Methods to Monitor Unfolding Transitions in Peptides, Globular and Membrane Proteins Ernesto A. Roman, Javier Santos and F. Luis González Flecha

217

Ultrafast Time-resolved Circular Dichroism in a Pump-Probe Experiment François Hache

255

On the Utility of Circular Dichroism Spectropolarimetry in Assessing Protein Interactions with Nanoparticles Michael J. W. Johnston and Mary Alice Hefford

281

Investigation of Radiation-Induced Damages in DNA Structure by Circular Dichroism and UV Absorption Spectroscopy S. V. Paston, O. A. Dommes and A. E. Tarasov

301

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

vi Chapter 9

Chapter 10

Chapter 11

Chapter 12

Contents Magnetic Circular Dichroism Applied in the Study of Symmetry and Functional Properties of Porphyrinoids Iseli Lourenço Nantes, Frank Nelson Crespilho, Katia Cristina Ugolini Mugnol, Juliana Casares Araújo Chaves, Roberto Alves de Sousa Luz, Otaciro Rangel Nascimento and Sandra Marilia de Souza Pinto

321

Application of Circular Dichroism for Short Peptides as HIV-1 Inhibitors Kazuhide Miyamoto

345

The Circular Dichroism in X-ray Absorption and X-ray Photoelectron Spectra Takashi Fujikawa and Ikuko Hojo

351

Aromatic Side-Chain Contributions to Protein Circular Dichroism Robert W. Woody

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Index

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

433 487

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PREFACE Circular dichroism (CD) refers to the differential absorption of left and right circularly polarized light. This phenomenon is exhibited in the absorption bands of optically active chiral molecules. CD spectroscopy has a wide range of applications in many different fields. Most notably, UV CD is used to investigate the secondary structure of proteins. This important book presents current research in the study of circular dichroism, including a study of the peculiarities of the circular dichroism spectra of double-stranded DNA cholesteric liquid-crystalline dispersions; magnetic circular dichroism in electron microscopy; and the application of CD spectroscopy for short peptides such as the human immunodeficiency virus type 1 (HIV-1) inhibitor. Chapter 1 – The goal of this Chapter is the consideration of the peculiarities of the circular dichroism (CD) spectra of the double-stranded (ds) DNA cholesteric liquidcrystalline dispersions (CLCDs). In PART 1 the authors demonstrate the main physico-chemical properties of the ds DNA liquid crystals and liquid-crystalline dispersions formed as a result of the phase exclusion of these molecules in water-salt or water-salt-polymer-containing solutions. PART 2 is devoted to the main principles of the theory of optical properties of imperfect, absorbing, cholesteric liquid crystals, which was used for description of the CD spectra of the ds DNA LCDs. The ds DNA molecules, due to various levels inherent anisotropy, tend to generate spatially twisted (cholesteric) structures. The theory predicts an appearance of abnormal optical activity, expressed as an intense (abnormal) band in the CD spectra in the case of cholesteric mode of packing neighboring quasinematic layers formed by ds DNA molecules in the particles. The coincidence of shape of the theoretically calculated and experimentally measured CD spectra for ds DNA cholestric LCDs (CLCDs) shows that the method used to calculate the CD spectra of ds DNA CLCDs, although phenomenological in its background, describes the optical properties of DNA CLCDs properly. In addition to this, the theory gives the dependence of the amplitude of an abnormal CD band on such parameters as the value of the pitch of helical twist, on the diameter of particles of the CLCDs, etc. The theory was applied as well for description of the optical properties of the CLCDs formed by ds DNA molecules complexed with various chemical and biologically active compounds. In PART 3 two approaches for obtaining the ―rigid‖ nanoconstructions, based on ds DNA molecules are described. In both approaches the neighboring ds DNA molecules fixed in the

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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viii

David S. Rodgers

structure of particles of CLCDs were used as ―building blocks‖ for nanodesign. First approach is devoted to the formation and properties of nanoconstructions based on ds DNA cross-linked by artificial nanobridges consisting of alternating copper ions and daunomycin molecules. In contrast to the spatial arrangement of the initial ds DNA CLCD, the structure of the resulting nanoconstruction is not longer ―liquid-crystalline‖; rather, it is «rigid», crystallike, three-dimensional structure. The second approach for the formation of rigid ds DNA nanoconstructions is based on the interaction between the ―modified‖ (as a result of their interaction with gadolinium cations) fragments of ds DNA molecules, fixed in a layered structure of particles of CLCDs. This type of rigid ds DNA nanoconstruction has unique combination of the physicochemical properties. The peculiarities of the CD spectra of these ds DNA nanoobjects are considered. The formed ―rigid‖ ds DNA nanoconstructions open a gate for various manipulations with these biomaterials. Chapter 2 – Vibrational circular dichroism (VCD) being a relatively new spectroscopic technique is quite promising for studying of biological molecules and their complexes. It combines conformational sensitivity of electronic circular dichroism (CD, or ECD) with extensive local mode information provided by the vibrational spectroscopy. Another advantage of VCD over ECD is its applicability to complexes of biological macromolecules, which would cause considerable light scattering in the UV region. This makes VCD a particularly useful tool for the investigation and characterization of various molecular structures. Here, the authors overview the theoretical background, discuss some practical aspects of VCD application to biological molecules, and list major spectral features encountered in the most common types of DNA and protein secondary structures. The authors also describe VCD applications to structural and conformational analysis of biological macromolecules and their complexes, including those with metal ions and drugs. In the end of the chapter, the authors outline some of the current state of the art methodology for computations of VCD spectra of large biopolymers. Chapter 3 – Magnetic circular dichroism experiments are traditionally a domain of the photon or x-ray physics. Particularly, x-ray magnetic circular dichroism (XMCD) experiments are an invaluable tool for obtaining the element-specific spin and orbital moments of studied samples. Until recently, there was no known equivalent of XMCD in the electron microscope. However, Schattschneider et al. have demonstrated that it is possible to observe an analogous effect in electron energy loss spectra in a transmission electron microscope. A rapid development of the method has followed. Shortly after the discovery of this phenomenon named electron magnetic circular dichroism (EMCD) a first-principles theory has been formulated and a set of sum rules has been derived. EMCD sum rules allow extraction of the spin and orbital moments in a way similar to their XMCD counterparts. On the experimental side, the spatial resolution was gradually improved from 200 nm in the prototype experiment, through 30 nm down to 2 nm using converged electron beams. Different experimental geometries have been implemented as well, providing alternative methods of recording a full datacube of energy, spatial and/or angular parameters. The first quantitative EMCD experiment using sum rules was reported by Lidbaum. Recent focus has been directed towards fine-tuning the quantitative EMCD experiments, studying the influence of the plural scattering of probe electrons on the extracted orbital-to-spin moment ratios. The first measurements of the EMCD in the image mode are reported—they should allow in the future to observe spatial variations of atom-specific moments. Finally, progresses in

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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Preface

ix

simulations and theory of the EMCD effect are described. Active research is devoted to the development of the EMCD technique into a routine complementary tool to XMCD with an advantage of bulk sensitivity and superior spatial resolution. Chapter 4 – Lipoproteins are water-soluble non-covalent assemblies comprised of several proteins (termed apolipoproteins) and several hundred lipid molecules. These assemblies mediate transport and metabolism of lipids and are central to the development of major human diseases, most notably atherosclerosis. Plasma lipoproteins are divided into classes according to particle size, density, composition and function. High-density lipoproteins (HDL, or Good Cholesterol, d=8-13 nm) mediate cholesterol removal from the peripheral tissues, and low-density lipoproteins (LDL, or Bad Cholesterol, d=22 nm) mediate cholesterol delivery. The balance between LDL and HDL determines the risk of developing atherosclerosis. Compositional and structural heterogeneity as well as the large size of lipoproteins have hindered their high-resolution structural studies. Low-resolution methods such as circular dichroism (CD) have been extensively used for studies of lipoprotein structure and stability. Far- and near-UV CD in conjunction with site-directed mutagenesis has been used to assess apolipoprotein conformation in solution and on lipoproteins. In addition, thermal denaturation data recorded by far- and near-UV CD, together with turbidity and light scattering measurements in CD experiments, have been instrumental in uncovering kinetic mechanism of lipoprotein stabilization in vitro and in linking it to metabolic lipoprotein remodeling in vivo. This chapter describes the application of CD spectroscopy to the analysis of apolipoprotein conformation and to studies of structural stability and remodeling of the major lipoprotein classes, including nascent reconstituted HDL (rHDL) as well as mature high-, low-, and very low-density lipoproteins from human plasma. The results demonstrate the power of CD spectroscopy coupled with other biophysical techniques, such as light scattering, electron microscopy, and differential scanning calorimetry, for the analysis of complex structural transitions in heterogeneous macromolecular assemblies. Chapter 5 – This chapter discusses the use of far and near UV circular dichroism methods to analyze changes in secondary and tertiary structure during protein unfolding, and how to obtain thermodynamic and kinetic information from CD experiments. The authors will give a brief introduction on the basics of this technique and discuss practical examples on the analysis of the unfolding of peptides, globular and membrane proteins. Here the authors will deal with important practical issues such as protein concentration, path length, choice of buffer, wavelength selection, and specific issues for unfolding experiments as the determination of the pre and post transition baselines. The importance of steady–state and time–resolved CD measurements on protein folding studies will be pointed out. Near– and far–UV CD experiments under equilibrium condition will aid us in the characterization of folded, partially folded, and unfolded states, and in the quantitative description of the unfolding transition, whereas folding–unfolding kinetics (non–equilibrium experiments) will give us a clue about the dynamics of the process involved. The selected examples will focus on the unfolding of the soluble proteins β-lactamase, lysozyme and thioredoxin, and on the thermophilic membrane protein CopA from Archaeoglobus fulgidus. Also, the induction of a helical structure by co–solvents (e.g., TFE, SDS) and their stability will be discussed. The authors will give a walkthrough to perform experiments and quantitatively analyze them in terms of the two–state and multi–state protein folding transitions, pointing to the determination and proper interpretation of thermodynamic and kinetic parameters. In addition, the advantages of using this method and its limitations will be discussed.

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David S. Rodgers

Chapter 6 – Circular dichroism (CD) is known to be a very sensitive probe of molecular conformation, and it is in particular widely used in biochemistry. Measuring the CD as a function of time is therefore very appealing to access information on the dynamics of conformational changes in molecules or biomolecules. An idea developed in the last decade is to implement the measurement of circular dichroism in a pump-probe experiment, which should allow one to access changes of CD with an unprecedented time resolution, down to the subpicosecond range. The most straightforward way to do so is to modulate the probe polarization form left to right circular and to measure the CD as a function of the pump-probe delay. This technique is however prone to many artifacts and one must be very careful when carrying out measurements. An alternative technique relies on the measurement of the pumpinduced probe ellipticity. Although less direct, this technique is much more robust and very well fitted for measurements in the ultraviolet. Both techniques are described in details in this article. The authors then present several results obtained with these techniques. First, demonstration of the technique is made on the dynamics of the binaphthol dihedral angle after photoexcitation in the ultraviolet. The authors then present a complete study of the dynamics of conformational changes following photolysis of carboxy-myoglobin. Combining timeresolved CD in the visible and in the far-ultraviolet with classical calculations of CD based on coupled oscillators, the authors can assign the 100 ps dynamics that they measure to a transient deformation of the proximal histidine following the heme doming. Extension of these techniques to longer timescales, and particularly to the protein folding problem will be addressed in conclusion. Chapter 7 – Nanotechnology is the manipulation of material resulting in the production of particles or structures at the nanoscale with distinct characteristics that are novel or superior as compared to the bulk material. The resulting nanoparticles, due to their small size, may demonstrate altered physical, chemical and/or biological properties. One of the most promising avenues for nanotechnology is in the medical field. Nanoparticles are currently being used or are proposed as effective means for medical imaging and as vehicles for vaccine and drug delivery. As a result of the increased surface/volume ratio nanoparticles display compared to the bulk form of the material and the increased reactivity for a given weight of material, interactions between nanoparticles and biological systems are of increased concern. Of particular interest is the potential for enhanced interaction with proteins; either those natively to the body or those administered with the nanoparticle as a therapeutic. Nanoparticle/protein interactions may cause protein conformational changes resulting in alterations in and/or abolition of function or, if severe enough, immunological recognition of the protein as foreign. This chapter will review the utility of circular dichroism spectropolarimetry, a technique classically used to assess the secondary and tertiary structure of proteins, as a method for assessing conformational changes in proteins adsorbed to the surface of a nanoparticle, encapsulated as a drug payload within a nanoparticle or externally conjugated to the nanoparticle and functioning as a targeting ligand. Chapter 8 – It is well known that ionizing radiation causes modification and destruction of nitrogenous bases in DNA molecule. There are also local breakages of hydrogen bonds (partial denaturation) both in the lesion sites mentioned above and in other sites of the macromolecule. To reveal the amount of some of these damages the authors applied circular dichroism and UV absorption spectroscopy. Radiation-induced changes in DNA structure influence its UV absorbtion spectrum in different ways: partial denaturation causes hyperchromic effect, while destruction of the bases results in hypochromic shift. At the same

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Preface

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time both of them result in the same changes in DNA CD spectra: the decrease in intensity. The authors attempted to segregate the described damages in DNA structure and studied the influence of DNA ionic surroundings on the radiation effect. The authors have demonstrated that the radiation efficiency of base destruction and partial denaturation increases with decreasing concentration of NaCl in irradiated solution. The substitution of a portion of Na+ ions on Mg2+ with the total ionic strength remaining constant (0.005 M) does not influence the radiation efficiency. At the higher electrolyte concentration (3 M) the yield of bases destruction is smaller in MgCl2 solutions than in NaCl ones, whereas the secondary structure of irradiated DNA is destabilized stronger in MgCl2 solutions. Also the authors have investigated the DNA spectral parameters in the presence of some biologically active compounds in irradiated solutions such as aliphatic alcohols, catechin, epicatechin and caffeine. It has been shown that all of these compounds reveal a radioprotective properties. Chapter 9 – Porphyrins, phtallocyanines and hemeproteins have been largely used for the design and build-up of supramolecular structures that has been applied successfully in nanotechnology. The large application of these compounds in nanotechnology comes from their photochemical, photoelectrochemical, catalytic, electrocatalytic properties associated to the possibility to establish a sort of weak non-covalent interactions such as metal-ligand coordinate bonds, hydrogen-bonding, aromatic --stacking and hydrophobic interactions. In this Chapter, it is presented and discussed the basis of UV-visible and magnetic circular dichroism of porphyrins and phtallocynines as well as spectral results obtained for these compounds at different conditions such as in complexes with apoproteins, layer by layer films and association to micelles. The effect of the medium, supramolecular organization and colloidal systems are discussed by the analysis of the UV-visible, CD and MCD spectra of protoporphyrin IX, metallo-meso-tetrakis porphyrins and phtallocyanine. Changes in the symmetry of porphyrins were also analyzed by UV-visible and magnetic circular dichroism (MCD) and correlated with their structure and catalytic properties. Both synthetic and biological porphyrins exhibited large symmetry-breaking distortions promoted by the medium and different topologies in micelles and liposomes feasible to be analyzed by UV-visible and MCD spectroscopy. Chapter 10 - Circular dichroism (CD) is defined as the differential absorption of left and right circularly polarized light. A CD spectrum is obtained as the function of wavelength, and it provides the information about the structural feature related to the chirality. Nowadays, the CD measurements are performed for the study of the structures of the chiral molecules such as peptides and proteins, because their secondary structures produce the characteristic CD curve. Also, the peptide (or protein)-solvent interactions could be researched by using the CD spectrum. When a solution including the molecules of interest induces the changes of the secondary structures of peptides or proteins, the resulting CD spectrum shows the characteristic CD curve for the changed secondary structures. Namely, we could obtain the information about the solvent-effect from a point of view of the structural changes. Even in the case of a short peptide, this solvent-effect appears in the CD curve. This chapter presents the applications of CD spectroscopy for short peptides such as the human immunodeficiency virus type 1 (HIV-1) inhibitor. Ch 11 – The authors discuss basic features and some applications of circular dichroism in high- energy spectroscopies like X-ray absorption and X-ray photoelectron spectra. In particular, they focus their discussion on X-ray magnetic circular dichroism (XMCD) from which they can extract useful and novel information on magnetic structures in solids that

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include their surfaces and interfaces. Theoretical backgrounds to analyze the spectra are discussed in detail. General scattering theory, relativistic many-electron theory and Green's functions are described starting from introductory level. Some advantages and disadvantages of this method are illustrated. Some illustrative examples and recent developments in measurement and their analyses are discussed. Furthermore the circular dichroism in angular distribution is discussed on the basis of multiple scattering theory, which clearly give us clear physical interpretation of observed spectra. Some practical applications are also shown to provide us with new information on surface geometric and magnetic structures. Ch 12 - The aromatic amino acids – phenylalanine, tyrosine, tryptophan – make distinctive contributions to the near-UV circular dichroism (CD) of proteins and contribute more subtly to the far-UV CD. The characteristic chromophores of Phe, Tyr, and Trp are described. The basic theory of CD is outlined, with emphasis on the most widely used method for predicting CD, the matrix method. Three proteins (ribonuclease A, barnase, carbonic anhydrase) are discussed in some detail as the CD contributions of individual aromatic amino-acid residues have been determined experimentally by site-directed mutagenesis. Theoretical calculations of these contributions have accounted for the experimental data quite well in most cases. Far-UV CD bands arising from aromatic side chains can adversely affect the analysis of protein secondary structure. However, current methods for such analysis utilize flexibility in the choice and weighting of reference proteins that can generally accommodate such non-peptide features without degrading the results. Applications of aromatic CD to the characterization of protein tertiary structure, detection of protein folding intermediates, and the study of ligand binding are discussed.

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

In: Circular Dichroism: Theory and Spectroscopy Editor: David S. Rodgers

ISBN: 978-1-61122-522-8 2012 Nova Science Publishers, Inc.

Chapter 1

THE CD SPECTRA OF DOUBLE-STRANDED DNA LIQUID-CRYSTALLINE DISPERSIONS Yu. M. Yevdokimov1*, V. I. Salyano1, S. G. Skuridin1, S. V. Semenov2, and O. N. Kompanets3

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1

Engelhardt Institute of Molecular Biology of the Russian Academy of Sciences, Moscow, Vavilova, Russia 2 Russian Research Center “Kurchatov Institute”, Moscow, Kurchatov Squ.1, Russia 3 Institute of Spectroscopy of the the Russian Academy of Sciences, Troizk, Moscow Region

ABSTRACT The goal of this Chapter is the consideration of the peculiarities of the circular dichroism (CD) spectra of the double-stranded (ds) DNA cholesteric liquid-crystalline dispersions (CLCDs). In PART 1 we demonstrate the main physico-chemical properties of the ds DNA liquid crystals and liquid-crystalline dispersions formed as a result of the phase exclusion of these molecules in water-salt or water-salt-polymer-containing solutions. PART 2 is devoted to the main principles of the theory of optical properties of imperfect, absorbing, cholesteric liquid crystals, which was used for description of the CD spectra of the ds DNA LCDs. The ds DNA molecules, due to various levels inherent anisotropy, tend to generate spatially twisted (cholesteric) structures. The theory predicts an appearance of abnormal optical activity, expressed as an intense (abnormal) band in the CD spectra in the case of cholesteric mode of packing neighboring quasinematic layers formed by ds DNA molecules in the particles. The coincidence of shape of the theoretically calculated and experimentally measured CD spectra for ds DNA cholestric LCDs (CLCDs) shows that the method used to calculate the CD spectra of ds DNA CLCDs, although phenomenological in its background, describes the optical properties of DNA CLCDs properly. In addition to this, the theory gives the dependence of the * To whom correspondence should be addressed E-mail- [email protected]

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

2

Yu. M. Yevdokimov, V. I. Salyanov, S.G. Skuridin et al. amplitude of an abnormal CD band on such parameters as the value of the pitch of helical twist, on the diameter of particles of the CLCDs, etc. The theory was applied as well for description of the optical properties of the CLCDs formed by ds DNA molecules complexed with various chemical and biologically active compounds. In PART 3 two approaches for obtaining the rigid nanoconstructions, based on ds DNA molecules are described. In both approaches the neighboring ds DNA molecules fixed in the structure of particles of CLCDs were used as building blocks for nanodesign. First approach is devoted to the formation and properties of nanoconstructions based on ds DNA cross-linked by artificial nanobridges consisting of alternating copper ions and daunomycin molecules. In contrast to the spatial arrangement of the initial ds DNA CLCD, the structure of the resulting nanoconstruction is not longer liquid-crystalline; rather, it is rigid, crystal-like, three-dimensional structure. The second approach for the formation of rigid ds DNA nanoconstructions is based on the interaction between the modified (as a result of their interaction with gadolinium cations) fragments of ds DNA molecules, fixed in a layered structure of particles of CLCDs. This type of rigid ds DNA nanoconstruction has unique combination of the physicochemical properties. The peculiarities of the CD spectra of these ds DNA nanoobjects are considered. The formed rigid ds DNA nanoconstructions open a gate for various manipulations with these biomaterials.

Keywords: double-stranded (ds) DNA molecules, liquid crystals, liquid-crystalline dispersions, the circular dichroism (CD), ds DNA cholesteric liquid crystalline dispersions, complexes of ds DNA with low-molecular mass compounds, intercalators, polycations, rigid ds DNA nanoconstructions.

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INTRODUCTION The actuality of the state of DNA in biological objects (viruses, chromosomes of the Protozoa, etc.) was raised immediately after the discovery of the DNA structure more than 50 years ago. Calculations showed that the volume occupied by a DNA molecule in solution is several thousand times larger than the volume of the head of the bacteriophage (bacterial virus) in which this DNA is packed. This means that local DNA concentration inside a bacteriophage may reach hundreds of milligrams per milliliter that is, it may differ thousands of times from the concentrations usually used in laboratories. It is interesting, that the DNA molecules in biological objects are not only concentrated (condensed) but are also highly ordered. Thus, a specific property of biological objects is the dense packing of the DNA molecules, which, in addition, changes easily and reversibly in the course of biological processes. The estimation of the mechanism (or mechanisms) of the functioning of the biological materials in a living cell is a complicated problem. Since definite analytical techniques, that would solve it definitively, have not yet been developed, great importance is attached to the modeling the process of condensation of the DNA molecules in laboratory conditions. One of these models is the so-called “liquid crystals” of the DNA molecules. To this point the properties of liquid-crystalline dispersions are of special interest for several reasons.

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

The CD Spectra of Double-Stranded DNA Liquid-Crystalline Dispersions

3

From a theoretical point of view, the physico-chemical properties of particles of dispersions can differ considerably from those of bulk liquid crystalline phases. This is especially important for dispersions where the particle size ranges from 10.0 to 1,000 nm. The physico-chemical properties of nucleic acid dispersions of are of biological interest [1-6] because chromosomes of primitive organisms and DNA containing viruses are isolated systems of microscopic size with an ordered, but labile packing, despite the high rigidity high and molecular mass of the DNA molecules. This means that the physico-chemical properties of the DNA dispersions may reflect some properties of these macromolecules in biological systems. Finally, from a practical point of view, particles of dispersions are of interest because of their potential as sensing units for biosensor devices [7, 8] intended for the detection of compounds interacting with DNA molecules. The goal of this paper is the consideration of peculiarities of the CD spectra of liquidcrystalline dispersions formed by double-stranded nucleic acid molecules. Because the subject is too large for a comprehensive analysis, we have selected areas to highlight, and apologize for those omitted. The CD spectra open a gate not only for the characterization of various types of dispersions (from their ―liquid‖ to ―rigid‖ state) but they can be used as an analytical criterion to detect different groups of compounds influencing both the secondary structure of DNA molecules and spatial structure of their liquid-crystalline dispersions.

PART 1. THE DOUBLE-STRANDED DNA LIQUID CRYSTALS AND LIQUID-CRYSTALLINE DISPERSIONS

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1.1. The DNA Liquid-Crystalline Phases Liquid crystals represent a special state of the matter that is situated between the perfectly ordered structure of crystal and the total disorder of the liquid state. Indeed, in a liquid crystal, molecules are able to move relative to each other as in a liquid, but they must follow certain constraints of orientation [9]. The simplest liquid-crystalline phase is the ―nematic‖ phase, characterized by long-range uniaxial order of anisotropic molecules called ―nematogens‖. The centers of mass of the constituent molecules are homogeneously distributed as in isotropic liquid, but one of their anisotropy axes aligns, on average, along a common unit vector n→ called the director. If nematogens are chiral, the simplest twisted nematic phase - ―chiral nematic‖ or ―cholesteric‖ phase is formed [10]. (The term ―cholesteric‖ has a merely historical sense: it was introduced in 1922 by G. Friedel to designate a class of liquid crystals comprising predominantly cholesterol derivatives). In the cholesteric phase the preferable orientation of the long molecular axes in the microscopic layers (quasinematic layers) is also characterized by the vector n→ (director). However, the orientation of n→ is smoothly changed along the microscopic helicoidal axis [11]. As a result, the cholesteric phase possesses an additional length scale, commonly referred to as the ―cholesteric pitch‖, P, which characterizes the distance along the pitch axis over which the local director makes a full turn [12]. Hence, in a cholesteric liquid crystal, molecules present a regular twist of their orientation, giving rise to a helical structure in

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which the molecules are all perpendicular to the helicoidal axis [9]. Between crossed polars, the cholesteric phase frequently shows periodic alterations of light and dark lines (a so-called ―texture‖). The orientation of the cholesteric axis can change in the preparation plane leading to the well-known ―fingerprint texture‖ [13]. The observed periodicity in the fingerprint texture corresponds to half of the helical pitch of the structure, (P/2) [13]. The helical pitch, P, measured directly on the micrographs, can vary from hundreds of nanometers to many microns or more, depending on the certain system [10]. The pitch sign is defined as positive or negative, according to the right- or left-handedness of the macroscopic cholesteric helix, respectively [14]. Hence, twist deformation characterizing a cholesteric (chiral nematic) phase is specified by the sign of the twist and magnitude of the pitch of the macroscopic helix formed in space by the director n→. The evaluation of the twist sign is an important task. Studies of the liquid crystals of nucleic acid molecules follow two mutually complementary directions: intermolecular condensation of low molecular mass molecules and intramolecular condensation of high molecular mass single molecules. In 1961, examining a fine layer of a concentrated DNA solution by polarizing microscope, K. Robinson [15] observed the ―fingerprint texture,‖ which was analogous to the texture of the fine layer of poly--benzyl-L-glutamate in organic solvents. K.Robinson cautiously postulated, that the DNA molecules form liquid-crystalline (LC) phase in concentrated solutions. Since that time, extensive investigations of the properties of the LC phases formed by nucleic acid molecules have been carried out in a number of laboratories in many countries [16-19]. It was demonstrated that the linear, low-molecular mass, rigid, double-stranded (ds) DNA molecules in concentrated solutions form a variety of lyotropic LC phases (nematic, cholesteric, etc. [20-24]). DNA liquid crystals represent by themselves viscous solutions in which molecules are ordered, while keeping their ability to slide relative to each other [25]. Owing to simultaneous presence of several levels of chirality (helical secondary structure of ds DNA molecules, helical distribution of counter-ions near DNA surface as well as asymmetry of C-atoms in the sugar residues), packing the adjacent quasinematic layers in highly hydrated liquid crystals is generally cholesteric [26]. This means parallel organization of ds DNA molecules in quasinematic layers, which are then twisted so that each layer of DNA molecules is twisted on a small angle relative to the two neighboring ones, with a period equal to the pitch similar to that found in cholesteric liquid crystals of substances with low-molecular mass [27, 28]. The cholesteric structure remains stable up to distances, dinter, between the neighboring DNA molecules (which can be obtained from X-ray scattering studies of cholesteric phases) around 3.5 nm [29]. At dinter below 3.0 nm the transition from the chiral cholesteric phase into a nonchiral hexagonal phase is observed even though the DNA molecules are still separated by more than nanometer of water [25, 30]; at dinter greater than 5.0 nm the transition from the cholesteric phase to isotropic state takes place. The cholesteric DNA phase has the fingerprint texture used for evaluation of the cholesteric pitch value under various conditions. In the range of distances between ds DNA molecules within 5.0-3.0 nm, the P value of the macroscopic helix varies negligibly, increasing from 2.4 to 2.5 m [29]. Since

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P= 2  dinter / 0 where: P is the pitch of the cholesteric structure, dinter is the distance between neighboring DNA molecules in the liquid crystal, and 0 is the twist angle, which DNA layers make relative to each other, one can determine that for DNA cholesteric liquid crystals the twist angle, 0 , is about 0.70 [31,32]. An interesting question regards the sign of the twist of the cholesteric structure formed by the ds DNA molecules. To obtain an answer, the structure of this phase was investigated primarily by polarizing microscope with comparison to other biopolymers [33]. At the beginning, by goniometric experiments, the cholesteric structure was demonstrated to be lefthanded in Dinoflagellate chromosomes [34]. The high voltage electron microscope supplied with goniometric stage was helpful in the study of thick sections of the Dinoflagellate chromosome specimens. The handedness of the twist occurring between DNA molecules in chromosomes was determined by tilting longitudinal sections of chromosomes together in a goniometric stage in the electron microscope. The cholesteric organization is mainly characterized by special pattern where thin sections of the materials are observed in the electron microscope, i.e., series of nested arcs, which have been interpreted as the visualization of the helical organization of the nucleofilamets. The sense of the concavity of the arcs obtained for a given inclination of the preparation can be related to the handedness of the cholesteric structure. Chromosomes of two species of Dinoflagellate present a left-handed twist [34, 35]. LC phases of ds DNA have also shown the presence of left-handed packing of these molecules [4, 34]. The freeze-fracture method was used later to confirm the handedness of local twist between DNA molecules [33]. The twisted structure of cholesteric liquid crystals is recognizable by the characteristic pattern obtained in thin sections prepared for transmission electron microscopy. This pattern consists of a set of parallel series of nested arcs. Despite speculations concerning the origin of these arcs, geometric and goniometric analyses have led to the conclusion that they correspond to a cholesteric organization with a constant left-handed twist [5, 36]. Hence, direct measurements showed that, at a concentration of approximately 200 mg/ml, the right-handed ds DNA molecules form a cholesteric phase in which the adjacent quasinematic layers have a left-hand twist. It is usually said that the right-handed DNA molecules form a cholesteric with a left-handed twist of the spatial structure. The fact that right-handed DNA molecules (B-family) condense to give a left-handed twisted spatial structure is somehow surprising. One fact to remember here that R.Rudall was the first (1955) to suggest that the helical nature of a molecule could be responsible for the twist occurring between them [37]. The determination of handedness in characterizing the DNA cholesteric phase is very important. The sign is a serious piece of information, which should always accompany the value of the cholesteric pitch and should not be ignored by theories for cholesteric DNA phase [12, 14]. Understanding the connection between the mode of interactions between ds DNA molecules in water-salt solutions responsible for chirality on the ―microscopic‖ scale and the structures of the formed ―macroscopic‖ liquid-crystalline phases is a challenge in the physics of LCs. For instance, following L.Onsager‘s [38] approach, J. Straley [39, 40] was able to

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connect the fact that helices take up less space when packed in a helical arrangement compared to a parallel arrangement. Indeed, right-handed screw bits fall into a counterclockwise arrangement among screws, predicting a left-handed cholesteric twist. This approach may not be universal [41] because right-handed screws with large diameters and a small pitch densely packed fall clockwise rather than counterclockwise, as in the J.Straley model [39]. Threfore, depending on the value of the helix opening angle, α, right-handed helical molecules can form either right- or left-handed twist phases [10]. However, these sterical ―fitting rules‖ can be applied for ideal thick densely packed helices. In reality, ds DNA molecules are right-handed helices with α < 450, but they are known to form predominantly left-handed cholesteric phases. Summing up many research findings, one can say the following. At a certain ―critical concentration‖ in water-salt solutions linear, rigid, low-molecular mass, ds DNA molecules are spontaneously condensed, forming a phase with a characteristic distance between molecules in the range of 5.0-2.5 nm. This phase has two specific features. It follows from a DNA X-ray diagrams that, although the DNA molecules in the emergent phase are ordered, three-dimensional order in their arrangement is absent; that is, the phase has the properties of a uni-dimensional crystal. At the same time, the phase has fluidity and the adjacent DNA molecules retain some diffusion degree of freedom typical of them; that is, the phase has the properties of a liquid. The combination of the two groups of characteristics justifies using the term ―lyotropic liquid crystal‖ to designate the phase formed by DNA molecules [26]. The structures of LC DNA phases depend on the properties of the solvent, on the DNA concentration and on the peculiarities of the DNA secondary structure. Finally, there are direct experimental techniques to estimate both the value of the helical twist and the handedness of this twist for the cholesteric phase formed because of the increase in the DNA concentration in solution. Besides, it was shown that mixing of ds DNA solutions with water-salt solutions of some polymers leads to the phase exclusion of DNA molecules. Such condensation of a single high-molecular mass (20x106 Da) ds DNA molecule is accompanied by formation of a toroid-like DNA particle. This intramolecular process is known since the L.Lerman experiments ―ψ-condensation‖ (psi is the acronym for polymer-salt-induced) [42-45]. Experiments have proved beyond any doubt that because of the ψ-condensation single toroid-like particles appear with a diameter of approximately 100 nm. Occasionally, other spatial structures appear. There is also proof that in these particles the adjacent segments of single DNA molecules are arranged in an orderly manner; however, which state is matched by this packing remains open to questions. One can stress, that it is not easy to examine experimentally the process of condensation of a single DNA molecules because it can be observed only with the help of an electron or atomic force microscope. Moreover, the experiments have to use solutions in which the concentration of nucleic acids does not exceed 0.1 μg/ml, and they should take place under conditions that preclude damage of the secondary structure of these molecules. A parallel and practically independent event was the study of the phase exclusion of ds DNA molecules, whose molecular mass did not exceed 106 Da, from polymer-containing solutions. Obviously, the ψ -condensation of low-molecular mass, linear, rigid, ds DNA molecules is an intermolecular process. This is accompanied both by the formation of LC phases or dispersions of these molecules [24, 46].

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The CD Spectra of Double-Stranded DNA Liquid-Crystalline Dispersions

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However, the packing mode DNA molecules in particles of LC dispersions may, in principle, differ from their packing in bulk LC phases.

1.2. The Formation and Properties of the Double-Stranded DNA LiquidCrystalline Dispersions in Polymer-Containing Water-Salt Solutions Dispersions of nucleic acids are formed as the result of phase exclusion when their watersalt solutions are mixed with water-salt solutions of some synthetic, water-soluble, chemically neutral polymers, for instance, poly(ethylene glycol) (PEG) [21, 47]. The efficiency of phase exclusion is related to a number of variables (Figure 1). The formation of dispersions can be easily demonstrated using absorption spectroscopy. Starting from a particular PEG concentration (CcrPEG) in solution, the optical density in the absorption region of nitrogen bases of the nucleic acid decreases (a so-called ―flattening‖ the absorption spectra), whilst at wavelengths above 320 nm (where neither DNA nor PEG molecules absorb) it is increased (an apparent optical density, Aapp, (Figure 2). Both optical effects indicate the formation of DNA dispersions. The diameter, D, of the particles of formed dispersion has been evaluated [47] using the relationship: Aapp = K -n

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where:  is the wavelength and parameter n is related under certain conditions to the diameter, D, of the particles.

Figure 1. The scheme of the liquid-crystalline dispersion (LCD, right panel) particle formation as a result of phase exclusion of double-stranded DNA molecules from water-salt polymer-containing solution.

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Figure 2.The absorption spectra of the DNA water-salt solution added with various concentrations of polyethyleneglycol (PEG). Curve 1 – CPEG = 0; curve 2 – CPEG = 150; curve 3 – CPEG = 180 mg/ml; Curves 3 and 4 are transformed into curves 4 and 5 as a result of Aapp substraction;

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Insert: The dependence of the Aapp value versus CPEG.

The evaluations show that the D value is equal to about 103 Å for DNA dispersions. This value tends to rise with DNA concentration and falls as the PEG concentration is increased. For instance, D = 4.5 x 103 Å at CPEG = 100 mg/ml and D = 3.8 x 103 Å at CPEG = 300 mg/ml. The size of the DNA particles is related to the molecular mass of PEG although the precise relationship has not been established [48]. The translational diffusion coefficient (DT) has been found for DNA dispersions (CPEG = 170 mg/ml; molecular mass of PEG = 4,000; 0.3 M NaCl) using laser correlation spectroscopy: DT = 14 x 10-10 cm2/s as CDNA → 0. This value corresponds to spherical particles with D = 3.7 x 103 Å. The coefficient of sedimentation (S) is determined for DNA dispersions by means of low speed centrifugation: S = 14.3 x 103 Svedberg units as CDNA → 0. The radius, R, of DNA particles has been calculated in terms of the Grosberg theory [49] that describes the condensation of the DNA molecules in polymer-containing solutions. The theoretical value of R (R = 2.9 x 103 Å at CPEG = 170mg/ml) is the same order of magnitude as that found experimentally. Using the DT and S values, the molecular mass of a particle of DNA dispersion was estimated as about 5x1010 Da [48]. Since the mean molecular mass of one DNA molecule is

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about 106, each particle of the DNA dispersion contains about 104 DNA molecules (at CPEG = 170 mg/ml). Absorption spectra allows one to estimate both a critical concentration of PEG (CcrPEG) at which the formation of DNA dispersions takes place and to establish its dependence on the properties of the solution used. The determination of CcrPEG values for PEG containing solutions, where the molecular mass of PEG ranges from 400 to 40,000, shows that the higher the PEG molecular mass, the lower the CcrPEG value. DNA dispersion can be formed if the molecular mass of PEG exceeds 600 [50, 51]. If the DNA molecule is regarded as a polyphosphate chain, one can use some properties of water-salt solutions to influence the effectiveness of the formation of the DNA dispersions. When the ionic strength of PEG containing solutions of alkali metal salts is raised from 0.1 to 0.7, the CcrPEG values decrease; the minimal values correspond to sodium salts in all cases. If the anionic composition of PEG containing solutions is altered, this does not affect the CcrPEG values determined in a solution with a fixed cationic composition. The CcrPEG values decrease when passing from solutions of alkali metal to those of alkaline earth metal salts. For instance, the ionic strength of a solution sufficient for the formation of dispersion is 0.15 (CPEG =170 mg/m) for a Na+ containing solution and only about 0.003 for a Mg2+ containing solution [52]. The formation of dispersions from molecules of other nucleic acids and synthetic polynucleotides in PEG-containing solutions has also been examined [26, 48]. When watersalt solutions of PEG (molecular mass = 4,000) were mixed with water-salt (0.3 M NaCl) solutions of ds RNA (the replicative form of phage f2, mol. mass about 2 x 106), an ―apparent‖ optical density appears at  > 320 nm, just as for ds DNA, the amplitude of the intrinsic absorption band decreases, and its maximum shifts slightly to the longer wavelengths. Similar changes in absorption spectra were observed for solutions of some synthetic ds polynucleotides: poly(I) x poly(C), poly(A) x poly(U), poly(dAT) x poly(dAT) and poly(dA) x poly(dT). The absorption spectra of water-salt (0.3 M NaCl) solutions of a single-stranded poly(U) or poly(A) and poly(G), as well as of tRNA, in the presence of PEG (molecular mass = 20,000) do not demonstrate the formation of dispersions. This means that only rigid ds molecules of nucleic acids can form dispersions in PEG -containing solutions. Thus, the conditions for formation of dispersions of nucleic acids involve such variables as ionic strength, cationic composition of the solutions, as well as the concentration and molecular mass of PEG (Figure 1). The dispersions, formed by the phase exclusion of linear low-molecular mass ds DNAs, display several specific features. First, the polymer (PEG), used for DNA condensation is not included in the content of formed particles and exerts an osmotic pressure on them, whereas water and small ions are free to move between the water-salt solution and condensed DNA [51, 53]. Second, following results of X-ray studies of the phases formed as result of low-speed sedimentation of the ds DNA particles, the interhelical distances (dinter) between adjacent DNA molecules in particles lies within the range of 2.5 - 5.0 nm. At equilibrium, intermolecular distance, measured by X-ray diffraction, is determined by a balance between the expansive forces, due to intermolecular repulsion, and the compressive osmotic pressure from the PEG solution. Hence, this distance can be regulated by specifying the PEG concentration in the solution [50, 51, 53]. For instance, if concentration of PEG in final solution equals 170 mg/ml the value of dinter is close to 3.4 nm [26, 48]. This means that the

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particles retain a high (in the range of 160–600 mg/ml) DNA local concentration with the ordered arrangement of the DNA molecules in the neighboring layers. Third, due to a set of inherent anisotropies, DNA molecules tend to form spatially twisted structure in particles of LCD. It is shoud be stressed that the layered structure of particles shown in Figure 1, favorably display the results of reconstructions of three-dimensional structure of the chromosomes of Dinoflagellate, based on the investigation of their crosssections performed by Y. Bouligand and F. Livolant [2-6, 33]. Note that the particles of the low-molecular mass ds DNA dispersions are ―microscopic droplets of concentrated DNA solution‖, which cannot be ―taken in hand‖ or ―directly seen‖. A ―liquid‖ mode of packing ds DNA molecules in the particles of dispersions prevents their immobilization on the surface of membrane filters. The results presented above show that the mean diameter of a particle is close to 400-500 nm and that one particle contains approximately 104 DNA molecules [47, 48]. This also means that the DNA molecules can condense without immediate complete precipitation out of solution [54]. The above evaluations of the physico-chemical parameters of the DNA particles are approximate, as they are made by calculating the formed ds DNA particles as spherical objects. Consequently, the question of how to visualize the particles of ds DNA dispersions and directly assess their sizes, is still open. The question of how DNA molecules are packed in particles is also unanswered. Here one can stress that the main differences between properties of LC dispersions and bulk LC phases can arise because of the ―size effect‖ [55]. This results from the contributions to the free energy of the particles of dispersion, which arise from the surface tension of the small droplets. There can be also packing defects within these particles caused by the curvature of the surface, and the structure within a particle may not be the same as that in the bulk phase. The presence of such contributions can lead, in particular, to the absence in particles of dispersions the packing mode characteristic of LC phases [55]. Proof of the specific mode of DNA molecule packing in particles of dispersions is based on an analysis of the peculiarities of their CD spectra.

PART 2. THE PECULIARITIES OF THE CD SPECTRA OF DOUBLESTRANDED DNA LIQUID-CRYSTALLINE DISPERSIONS AND THEIR COMPLEXES 2.1. The CD Spectra of Various Types of Double-Stranded DNA LiquidCrystalline Dispersions Since 1951 various approaches have been used for the description of optical properties, in particular, circular dichroism of the particles of dispersions of many compounds, including nucleic acids [56-63]. However, from a practical point of view, it is useful to analyze experimental data on LCD circular dichroism, by means of a phenomenological theory developed by V. Belyakov. This theory allows the possibility to describe and predict many optical peculiarities of the particles of ds DNA dispersions formed namely in PEG-containing solutions [64]. This theory takes into account both the layered structure of the packed ds DNA

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molecules, and the microscopic data shown above regarding these particles of dispersions. In particular, experimental data enables one to treat the particles of dispersions formed by ds DNA molecules of low molecular mass (about 106 Da) as spheres of diameter, D, for which, due to inherent rigidity of the secondary DNA structure, the liquid-crystalline ordering is specific. In addition, the particles of DNA dispersions are considered polycrystalline systems, with random distribution and orientation of individual particles, possessing their own absorption in the UV-region of the spectra due to the presence of the nitrogen bases (―chromophores‖) in the DNA structure. It is also assumed that the separate particles are small enough to justify the application of the kinematic approximation of the theory of diffraction to describe the optical properties of individual particles. An approach based on such assumptions was previously applied to imperfect non-absorbing LCs [65]. Calculations of the optical properties of absorbing cholesteric LCs in the case of light propagation along the cholesteric axis have also been performed [66]. It is known that the modification of the effective dielectric constant of a medium (0) due to light scattering is proportional to the forward scattering amplitude of an isolated scattering object measured at the frequency of the propagating light (). Therefore [64]:

 eff   0 

4c 2 02

(0)

(1)

where: 0 is the volume of a single dispersion particle and (0) is the forward scattering

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amplitude averaged over all orientations of the particles, i.e. over all possible directions of the reciprocal lattice vector . Taking the perturbation theory to the second order in the framework of the kinematic diffraction approach, it follows that the forward scattering amplitude (0) , non-averaged over all orientations of vector , for light of eigen polarization (e), which is diffracted by the helical structure, for the case of spherical crystallites with diameter D, may be expressed as:

( 0) 

[(Re  ) 2  (Im  ) 2  2i Re  Im ][  02  2  (  0  ) 2 ](  0  ) 2  64 4  50  4  02 i

 [1  x 2 / 2  ix 3 / 3  (1  ix) exp(ix)]

(2)

where: x   0 D ,   [ 2  2(  0 )] / 2 02 , and Re and Im are real and imaginary parts of the dielectric anisotropy of cholesterics, respectively. After averaging (0) over all possible orientations оf the dispersed particles, the eigen polarizations can only be circular, because in a disordered dispersed system there is no preferential direction. Carrying out the projecting polarization (e) over the circular ones and averaging (0) over all orientations of vectors (), one can obtain from the real and the imaginary parts of equations (1) and (2) the equation 3 (expressions (3a and 3b), which describes the optical rotation of the plane of polarization (/L) and the coefficients of transmittance (IL,R) of waves with left-(L)- and right-(R)-circular polarizations, respectively:

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/L 

3 02 D 1 {[(Re  ) 2  (Im  ) 2 ](sin x  x cos x  x 3 / 3)  2  32 0 1  2 Re  Im (1  x 2 / 2  cos x  x sin x)}  (1  y 2 )(y / x 4 )dy

(I L,R )   exp[

(3a)

3 02 DL 1 {[(Im  ) 2  (Re  ) 2 ](1  x 2 / 2  cos x  x sin x)  3  2 16 0 1

 2 Re  Im (sin x  x cos x  x 3 / 3)}  (1  y 2 )(1  sy ) 2 x 4 dy (3b)

where: x  D(y   / 2 0 ) ;

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 is the reciprocal lattice vector which is equal to 4/P, and  0 is the wave vector of the incident radiation; L is the thickness of the ―effective‖ DNA layer determined from the formula L = Cl/, where С and  are the concentration and the density (g/cm3) of DNA, respectively, and l is the thickness of the cell (1 cm);.  = (1 - 2)/2 is the dielectric anisotropy of the cholesteric LC; 1, 2 = 3 are the principal values of the tensor of dielectric permittivity, and s = ± 1, depending on the sense of twist of the cholesteric structure. One can suppose that each particle of an individual particle of DNA dispersion is specific to the spatially twisted (cholesteric) ordering of adjacent molecules, characterized by a pitch, P, of helical structure, and by dielectric anisotropy, , which contains resonant components for absorption bands of the DNA nitrogen bases (as well as for additional compounds, which can be incorporated in this system). This permits us to apply the equations (1-3) to describe the dependence of the optical parameters of the DNA dispersions upon the wavelength of the light. For further consideration it is important that the chromophores in the considered system have a local anisotropy of absorption, i.e. the anisotropy of the dielectric constant, , which has an imaginary part for corresponding wavelengths. In the expression for dielectric anisotropy, it is convenient to specify the component, originating from the absorption bands, i.e. to present, , in the form:

     i

(4) i To take into account the absorption of the nitrogen bases, as well as of ―external‖ chromophores introduced into DNA molecule for instance, colored antibiotics. One can assume that one of main values of I, and, consequently I, has the resonant form:

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

The CD Spectra of Double-Stranded DNA Liquid-Crystalline Dispersions i 

ri  02 i

    2  i i 

13

(5)

where: ri - are proportional to product of concentration of chromophores on force of their oscillators;  - factor conditioned by polarization of the medium. It is known that the circular dichroism is the difference in absorption for incident L- and R-circularly polarized light. Traditionally, it is the intensity of the transmitted light; this is related to the absorbance by the standard formula: I = I0 x 10-A

(6)

where:: I is the transmitted intensity, I0 is the incident light intensity, and A is the absorbance. The standard experimental circular dichrograph measures the following ratio: (IL - IR)/ (IL + IR) = signal

(7)

where: (IL) = (I0L) exp (- АL) and (IR) = (I0R) exp (- АR), if the material under study obeys the Beer-Lambert law for each polarization Using equations (3), the CD spectra, i.e. the dependence of the measured ∆A or (AL -AR) value upon , for the DNA LCDs, were theoretically calculated by the simple formula:

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∆A = (AL - AR) = log[(IR)/(IL)]

(8)

From equation (3), it follows that for circular dichroism in the region of the absorption band, which is located far from the region of selective reflection for the cholesteric LC structure, theory recognizes that the qualitative behavior of the circular dichroism is the same as that considered earlier for cholesterics with propagation of light along their helicoidal axes. Despite further details, it is possible to consider those results of theoretical calculations [64], which have a direct relationship to the peculiarities of the circular dichroism of the particles of DNA dispersions.

2.1.1. A Few Practically Important Consequences From the Theory 2.1.1.1. Ds DNA Molecules of Low-Molecular Mass The initial theoretical guess is based on a suggestion that the ds DNA molecules of lowmolecular mass form the quasinematic layers in the particles of dispersons and for these layers the spatially twisted (cholesteric) structure is characteristic. The twisted structure means that the average orientation of the ―director‖ (n) of the layer is changed in the

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subsequent quasinematic layers on a fixed angle. In this case, anisotropy of chromophores absorption or linear polarizations of light give rise to circular dichroism. Hence, one can expect an appearance of an intense band in the CD spectrum in the region of absorption of the DNA nitrogen bases (‗chomophores‖ absorbing in the UV-region). It is necessary to note that since the F.D. Saeva papers (1971-1972), the phenomenon of an appearance of the band in the CD spectra for compounds ―dissolved‖ in the cholesteric LC phases has been termed ―liquid crystal induced circular dichroism‖ (LCICD) [67-69]. Figure 3 represents the theoretically calculated CD spectrum for a DNA LCD. This CD spectrum has an intense band in the region of absorption of the nitrogen bases of DNA.

Figure 3. The CD spectrum theoretically calculated for ds DNA CLCD. СDNA = 10 μg/ml; ∆Α = (ΑL - ΑR) х 2.5х10-5 opt.un.

Figure 4 compares the experimentally measured CD spectrum of a water-salt solution of the initial, linear, rigid ds DNA (B-form, curve 1) with the CD spectra for LCD (curve 2) and the LC phase (20 μm-cell, curve 3) formed by the same DNA in a PEG-containing water-salt solution (CPEG > CcrPEG). One can see that the formation of both DNA LC and LCD is clearly accompanied by the appearance of the intense band in the CD spectra in the region, where the DNA nitrogen bases absorb. Additionally, in the case of the thin film of the LC phase it is

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difficult to obtain a perfect alignment of the cholesteric phase in respect to the light beam. Homogeneous (without any defects) alignment is observed only exceptionally and in small domains [13]. This influences the real magnitude of amplitude of the intense band in the CD spectrum.

Figure 4.The CD spectra of linear ds DNA in water-salt solution (curve 1), DNA CLCD in water-salt PEG-containing solution (curve 2) and the DNA CLC phase (20 μm-cell, curve 3).

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0.3 M NaCl; 170 mg/ml PEG.

According to the above theoretical considerations, the intense band in the CD spectrum (Figure 4, curves 2, 3) located in the absorption region of the molecules of chromophores incorporated in the content of the bulk LC phase is direct evidence of the formation of the helically twisted structure [62, 63]. Indeed, many authors postulated that the sign of intense band in the CD spectra observed in condensed forms of DNA was related to the handedness of the helical twist occurring between DNA molecules. The decisive experiment was performed by M.Maestre and C. Reich [60] with twisted films of LC phase of DNA molecules. A thin film was sandwiched between two quartz plates; when the plates were twisted to generate a right-handed helically twisted structure a positive band in the CD spectrum at about 290 nm was obtained, whereas a negative band in the CD spectrum was correlated to opposite twisting of the plates. Hence, the sense of the helicity is reflected in the sign of the intense band in the CD spectrum (i.e. a positive band reflects a right-handed helical arrangement, and a negative band reflects a left-handed twist). Any random packing of nucleic acids was unaccompanied by any change in the amplitude of the CD band except that produced by changes in secondary structure [9]. Following G. Spada [70] an intense negative band in the CD spectrum for the B-DNA LC phase can be used as an additional, simple criterion for estimation of the handedness of this phase. Indeed, the handedness of the twisted structure can be correlated to the CD spectrum by equation (9):

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Yu. M. Yevdokimov, V. I. Salyanov, S.G. Skuridin et al. (AL – AR)i = P i 3 n(A - A)i /2 ( i2 - 02)

(9)

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Here: (AL – AR )i - is the circular dichroism at frequency  i, 0 - is the frequency of the selective reflection, n – is the linear birefringence, (A - A) i - is the linear dichroism of the quasinematic layers, P - the pitch of the cholesteric structure. that was developed from a model composed of a helical array of stacked chromophores [71, 72]. In the case of the DNA twisted structure, as it follows from the fingerprint textures, the pitch, P, is about 2-2.5 m and, hence,0 is in the I.R. The pitch was defined as positive for a right-handed spatial structure as shown directly above. It is also known that the electronic transitions in nitrogen bases are polarized in the molecular planes. As a consequence the linear dichroism (A - A ) of the individual DNA molecules is negative [73]; as is also the linear birefringence (n) [22]. Taking into account all these parameters, the negative sign of the band in the CD spectrum for the DNA LC phase (Figure 4, curve 3) indicates a left-handed twist of the LC formed by the ds DNA molecules. The obtained result coincides with estimation of the handedness of the DNA LC phase performed earlier in the other techniques (see above). Figure 4 also shows that the intense bands both in the CD spectra of DNA LC and LCDs, have identical, negative, signs. An appearance of intense bands both in the CD spectra of the ds DNA LC phase and LCDs means that the purine and pyrimidine nitrogen bases do play the role of ―chromophores‖ providing information about the spatial packing of DNA molecules both in the bulk LC phase and in the particles of LCDs. The coincidence of shapes of the calculated theoretically (Figure 3) and measured experimentally (Figure 4, curve 2) CD spectra for the DNA LCDs shows that the method used to calculate the CD spectra of DNA LCDs, although phenomenological in its background, describes the optical properties of DNA LCDs properly. This allows one to draw the conclusion that the appearance of intense band in the CD spectra unequivocally reflects the left-handed twist of neighboring quasinematic layers of DNA molecules packed not only in the LC phases but also in the particles of LCDs. According to the X-ray study of LC phases formed as a result of low-speed sedimentation of particles of LCDs, ds DNA molecules are ordered in the particle at distances of 3.0-5.0 nm, i.e. they acquire the properties of a crystal, but molecules in the neighboring layers are mobile, i.e. they retain the properties of a liquid. In order to stress the twisting of quasinematic layers, the term ―cholesteric liquid-crystalline dispersions‖ (CLCDs) was used to signify these dispersions [64]. This deduction corresponds to a common statement that the cholesteric packing is a specific property of any molecules having geometrical and optical anisotropy. Hence, rigid, anisotropic, ds nucleic acid molecules (DNA, RNA, etc.) tend to realize their potential tendency to the cholesteric mode of packing in the particles of LCDs. The bands in the CD spectra both for DNA CLC and DNA CLCD have shapes similar to that of the DNA absorption (Figure 2), but the maxima of the bands in the CD spectra are ―red‖ shifted (~ 270-300 nm). The experimental displacement of the maximum of the band in the CD spectra for DNA CLC and DNA CLCD compared to the DNA absorption band

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(Figure 4, curves 2 and 3) is connected with diffraction effects (together with the known polarization displacement due to ―effective field‖ effects acting on molecules in the cholesteric phase). This means that, together with the component of circular dichroism, which is determined by absorption (Imi), there is a diffraction contribution to the circular dichroism, determined by the value of Rei. In connection with different frequency dependencies of values of Imi and Rei near the absorption band (the value of Imi on resonant frequency reaches its maximum, but the value of Rei approaches zero at the main absorption band and has different signs on different sides of the main absorption band) the maximum of the band in the CD spectrum is shifted around the main band of absorption. (This displacement should, in principle, depend on the size of the particles of the DNA CLCDs). Hence, one can finally conclude that the negative sign of the band in the CD spectrum (Figure 4, curve 2) proves the left-handed cholesteric twist of quasinematic layers formed by the right-handed DNA molecules (B-form) in particles of LCDs. Here additional remarks are necessary. The value of ∆270 (~ - 100 units), which can be used to ―reflect‖ the value of circular dichroism оf the nitrogen bases in the structures of DNA CLC and DNA CLCD, is far larger than the molecular circular dichroism,  (~ 2.5 units, Figure 4, curve 1), i.e. the physical constant usually used for description of the peculiarities of isolated nitrogen bases and individual molecules of nucleic acids. The value of , as the constant in the case of isolated nitrogen bases as well as of individual, initial, linear ds DNA [74] molecules, can be calculated theoretically. To evaluate the CD of nitrogen bases, and hence, to estimate the value of  it is necessary to calculate dipole strengths, rotational strengths, and transition frequencies. The key assumption in the theoretical calculations is that there is no electron exchange between nitrogen bases in solutions. There are two different strategies used in calculating their optical properties depending on whether the corresponding transition in the nitrogen bases is electrically allowed (such as *) or magnetically allowed (such as n*) [74]. Under standard conditions (in solution) a density of ―choromophores‖ (nitrogen bases) is much less that 1 chromophore/nm2. In these circumstances the delocalization of the excitation via the various coupling mechanisms is not significant and will involve only nearest neighbor delocalization. Such a system will show a small, conservative CD spectrum (Figure 4, curve 1) [62]. The calculations also show that the alterations of the ds DNA secondary structure (denaturation, transition between the conformations such as A-, C or Z-forms) are accompanied by change in  value within 1-7 units [74]. On the other hand, one can see that in the case of the DNA CLCDs or CLC phase, the CD spectra do not resemble the spectra of any known DNA conformations. Despite the intuitively reasonable ―feeling‖ that twisting of quasinematic layers should give rise to intense band in the CD spectra, an examination of known theories of optical activity shows that a chiral arrangement by itself is not enough for amplification of the band in the CD spectrum. The chromophores (nitrogen bases, in our case) must also be coupled in someway, i.e. the absorption of one chromophore must be affected by the presence of other chromophores, and by the chiral relationship they bear to each other [57]. A coupling between the excitation of neighboring choromophors (nitrogen bases) results in transitions with new polalizations and energies [73]. This means that the individual nitrogen bases in quasinematic layers formed by DNA molecules must not respond independently to the incident light.

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Hence, the nitrogen bases in the content of neighboring DNA molecules in quasinematic layers could be significantly coupled to each other. This effect will occur in large molecular spatial structures due to their ability to delocalize their excitations and respond collectively to the incident radiation. One can stress that the relative importance of various mechanisms of the coupling between any pairs of dipoles (for instance, the exciton coupling, the vibronic coupling, the crystal field mixing) [73] will depend on dimensionality of the formed structure. The long-range couplings are possible if the LC system is large and dense enough [63]. These effects are never observed in isotropic solutions of nitrogen bases or isolated DNA molecules. However, the condensation of DNA molecules, by itself, is not a sufficient condition for an appearance of intense band in the CD spectrum, since many aggregated forms of DNA (for instance, the aggregates formed by single-stranded DNA molecules) fail to show the intense band in the CD spectra. Therefore, on the one hand, an appearance of an intense band in the CD spectrum is connected with long- range coupling of the dipoles of nitrogen bases, i.e. the nitrogen bases are main contributors into optical behavior of the CLCD (in the amplitude of an intense band in the CD spectrum). On the other hand, taking into account that nitrogen bases are fixed rigidly enough in the secondary DNA structure, an appearance of this band reflects the specific type condensation of the ds DNA molecules, i.e., the helical array of ds DNA molecules. By a helical array one can consider again a parallel organization of ds DNA molecules that is then twisted slightly so that each qusinematic layer of DNA molecules is at a slight angle of twist with respect to the two neighboring ones. As the ds DNA molecules condense into particles of dispersion, local density of nitrogen bases increases to the point in which significant delocalization can occur [62]. This means that the amplitude of an intense band in the CD spectra of the DNA CLCD, formed by ds DNA molecules that possess native secondary structure and fixed properties of nitrogen bases, is connected both with ―long-range collective behavior‖ of the nitrogen bases and with a local density of ds DNA molecules in the particles of CLCDs. It, in turn, depends on the secondary structure of these molecules and on the properties on the solvent. This means that the amplitude of intense band in the CD spectra can vary in broad range of the values. Hence, value of  is not a constant. Therefore, the use of  value may have only illustrative character, and it seems to be illogical to apply this parameter for the comparison of the peculiarities of the CD spectra of various DNA CLCDs. In order to stress the difference between ―molecular‖ and a so-called ―structural‖ circular dichoism [71, 73] the term an ―abnormal band‖ was used to signify an intense band in the CD spectrum [64]. With allowance for above said, the use of the amplitude of this band in CD spectra, expressed simply as experimentally measured A value, is more reasonable. This value will be used in our paper.

2.1.1.2. The New Qualitative Results The new qualitative result obtained for CLCDs is the dependence of the amplitude of the band in the CD spectrum upon the size of the particles of the DNA CLCDs, which follows from equation (3). Figure 5 displays the theoretical CD spectra for the particles of DNA CLCDs of different size [47]. Insert is the resulting dependence of the amplitude of the negative band in the CD spectrum on the particle size. As one can see in Figure 5, the decrease in the D value for

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particles of DNA CLCDs is actually accompanied by the decrease in the amplitude of the abnormal band in the CD spectra.

Figure 5.The CD spectra theoretically calculated for the particles of the DNA CLCD of different size.

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Insert: The dependence of the amplitude the negative band in the CD spectra of the DNA CLCD on size (D) of particles. Curves 1 - 5 – D – 100; 200; 300; 400; and 500 nm; pitch (P) - 2,000 nm; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

The important conclusion resulted from the data obtained, is that a ―size effect‖ is apparent. The theoretical calculation shows that if the diameter of DNA CLCD particles reaches ~ 50 nm, the amplitude of the intense band in the CD spectrum decreases so strongly that it no longer differs from that in the CD spectrum characteristic of isolated linear DNA molecules in water-sail solutions, (Figure 5). This result means that in the case of the formation of CLCDs with a diameter of particles ~ 50 nm, their presence cannot be registered by CD spectroscopy.

2.1.1.3. In the case of DNA CLCD with Constant D Value the Influence of Pitch (P) of the Cholesteric Helix on the Amplitude of the Band in the CD Spectrum Was Established Figure 6 exemplifies the theoretical CD spectra for DNA CLCDs possessing different cholesteric pitches. The smaller the P value of a cholesteric structure, i.e. the greater is the twist, the more intense is the band in the CD spectrum. Conversely, the more untwisted the cholesteric structure is, the lower the amplitude of the band is in the CD spectrum of the

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CLCD. The theoretical treatment indicates that where the pitch of the cholesteric structure of a DNA LCD C is ~ 30 m and with constant structural properties of the ds DNA molecules, the amplitude of the negative band in the CD spectrum is already close enough to the amplitude of the band characteristic of isolated linear DNA molecules (Figure 4, curve 1).

Figure 6.The theoretically calculated CD spectra for the ds DNA CLCD possessing different cholesteric pitches (P). Insert: The dependence of the amplitude the negative band in the CD spectra on pitch of the spatially twisted structure of the DNA CLCD. Curves 1-5 – P – 2,000; 4,000; 6,000; 8,000 and 10,000 nm; D - 500 nm; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

2.1.1.4. Structure of a Quasinematic Layer Formed by ds DNA Molecules Figure 7 displays the structure of a quasinematic layer formed by ds DNA molecules. At the formation of CLCDs the chemical reactivity of structural elements (nitrogen bases, etc.) of ds DNA molecules remains unchanged [75]. One can see as well that because of the ―liquid‖ mode of ds DNA molecules packing in quasinematic layer, low-molecular-mass chemical or biologically active compounds (antitumor drugs, peptides, chemicals, metal cations, etc.) can readily diffuse into particles of CLCD.

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Figure 7. The structure of quasinematic layer formed by ds DNA molecules. Low-molecular mass compounds (shown as blue arrows) can penetrate into this layer very easily. Molecules of drug intercalating between the DNA nitrogen base pairs are shown as red rectangles.

The conservation of the ds DNA reactivity in the composition of CLCD particles and the ordered location of neighboring DNA molecules in these particles, which does not limit the diffusion of various drugs into the particles, can ensure a high penetration rate of these compounds into the particles and, therefore, a high rate of their interaction with nucleic acid molecules. These circumstances initiate an important question on the shape of the CD spectra for DNA CLCDs treated with low-molecular, colored compounds, i.e. a question of the introduction of additional ―chromophores‖ into the preformed structure of the CLCD. The above theory imposes no limitations on the number of molecules of ―external chromophores‖ that could be incorporated into the CLCD structure. Hence, one could expect an appearance of the additional abnormal band(s) preferably for compounds located by the mode similar to that one of nitrogen bases with respect to the ds DNA helix, i.e. especially for compounds incorporated (intercalated) between the nitrogen base pairs. (Note that a low extent of intercalation of these compounds between pairs of nitrogen bases does not interfere with the packing mode of neighboring ds DNA molecules in quasinematic layers, leaving the overall spatial structure of ds DNA CLCD particles intact (Figure 7). Figure 8 shows the CD spectra theoretically calculated for the CLCDs formed by the ds DNA molecules and treated with a colored drug, i.e. anthracycline antibiotic – daunomycin (DAU). A few facts are worth noting here. i)

The calculated CD spectra of these CLCDs contain two bands. One of the bands is found in the absorption region of the DNA nitrogen bases ( ~ 270 nm) and the other lies in the absorption region of the drug ( ~ 500 nm). Both bands have negative signs at any extent of daunomycin binding to the ds DNA. ii) The shapes of the bands in the CD spectra are identical to those of the absorption spectra for the DNA and the antibiotic.

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Yu. M. Yevdokimov, V. I. Salyanov, S.G. Skuridin et al. iii) Both bands have comparably high amplitudes. iv) The amplitude of the band in the CD spectrum in the region of daunomycin absorption grows with increasing number of its molecules bound to DNA, although the amplitude of the band in the region of DNA absorption remains constant.

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Note that the intercalation of daunomycin between the ds DNA nitrogen base pairs does not interfere with the packing mode of neighboring DNA molecules in quasinematic layers, leaving the overall spatial structure of the DNA CLCD particles practically intact.

Figure 8. The theoretically calculated CD spectra for the ds DNA CLCD particles treated with daunomycin. D - 500 nm; P – 2,500 nm; Curves 1 – 6 - different concentrations of daunomycin.

Figure 9 demonstrates the experimental CD spectra of the CLCD first formed by the ds DNA molecules in PEG-containing solution (preformed CLCD) and then added DAU. In agreement with theoretical predictions, the CD spectra of the DNA CLCD ―colored‖ by DAU have two bands. One occurs in the absorption region of the DNA nitrogen bases ( ~ 270 nm) and the other lies in the absorption region of DAU chromophores ( ~ 500 nm). The shapes of the bands in the CD spectrum are identical to those in the absorption spectra of DNA and DAU.

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The CD Spectra of Double-Stranded DNA Liquid-Crystalline Dispersions

Figure 9. The experimentally measured CD spectra for the ds DNA CLCD particles added with daunomycin. Curves 1- 4 – Ctot = 0; 1.2; 2.4; 3.9x10-6 M daunomycin; СDNA = 12 μg/ml; 0.3 M NaCl; 170 mg/ml PEG;

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∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

Figure 10. The theoretically calculated CD spectra for the ds DNA CLCD particles treated by mitoxantrone. D - 500 nm; P – 2,500 nm; Curve 1 – rMX = 0.02; curve 2 – rMX = 0.04; curve 3 – rMX = 0.06; Parameter rMX characterizes various MX concentrations.

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Under binding of DAU with ds DNA molecules both bands have negative signs despite DAU concentration. The identical signs of two bands in the CD spectra of the ds DNA CLCD ―colored‖ by DAU simply means that the orientation of DAU molecules coincides with the orientation of the nitrogen base about the DNA axis. Hence, DAU molecules intercalate into DNA so that the angle between the DAU molecule and the long axes of the DNA is ~ 90°. Figure 10 dispays the CD spectra theoretically calculated for DNA CLCDs treated with the colored anti-tumor compound, mitoxantrone (MX). The theoretical CD spectra contain two bands of identical sign in the regions of absorption of DNA and MX. Figure 11 shows the experimental CD spectra of preformed CLCD treated by MX. Again, a few points are notable. First, the CD spectra of the CLCD have two bands. One exists in the absorption region of the DNA bases ( ~ 270 nm) and the other appears in the absorption region of the MX chromophores ( ~ 680 nm). At a low level of binding of MX with the DNA molecules; both band have negative signs. Secondly, the shapes of the bands in the CD spectrum are identical to those in the individual absorption spectra of DNA and MX. The identical signs of the bands in the CD spectra indicate that the orientation of the MX molecules with respect to the DNA molecular axis coincides with the orientation of the nitrogen bases. The comparison of the experimental and the theoretical CD spectra (Figure 10 and Figure 11) shows that the amplitude of the band in the CD spectrum in the region of MX absorption grows as more MX molecules are bound to the DNA, although the amplitude of the band in the region of DNA absorption remains constant. It is possible to predict that such a situation will be observed so long as, under MX action, the parameters of the DNA secondary structure do not begin to vary or the intercalation mechanism of MX binding is not replaced by any other.

Figure11. The experimentally measured CD spectra of the ds DNA CLCD added with mitoxantrone. Curves 1-4 – Ctot = 0; 1.55; 3.08; 5.35x10-6 M mitoxantrone; СDNA = 10 μg/ml; 0.3 M NaCl; 170 mg/ml PEG; ∆Α = (ΑL - ΑR) х 2.5х10-5 opt.un.

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Figure 12 shows the experimental CD spectra of DNA CLCDs treated by the colored intercalating compound, ―SYBR Green‖. Again, in full agreement with theory, the CD spectra of the CLCD have two bands: one is in the absorption region of the DNA bases ( ~ 270 nm) and the other is in the absorption region of the ―SYBR Green‖ ( ~ 505 nm). Hence, ―SYBR Green‖ molecules are fixed between the DNA nitrogen bases so that the angle between the ―SYBR Green‖ molecule and the long axes of the DNA is ~ 90°. Hence, the proposed method for calculation of the CD spectra predicts the appearance of an additional band(s) in the region of absorption of the chromophore of the compound intercalated between the DNA nitrogen bases.

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Figure 12. The experimentally measured CD spectra of the ds DNA CLCD added with SYBR Green. Curves 1-4 – Ctot = 0; 1.96; 9.8; 19.6x10-6 M SYBR Green; СDNA = 10.2 μg/ml; 0.3 M NaCl; 170 mg/ml PEG; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

Here one remark seems to be reasonable. The use of ―SYBR Green‖, which retains its high fluorescence while being intercalated between the DNA nitrogen bases in the CLCD particles formed in PEG-containing solution, opens a gateway for obtaining of additional information on the peculiarities of these particles. As an example, Figure 13 shows the ―fluorescence images‖ of particles of the ds DNA CLCD treated with ―SYBR Green‖ and taken with the help of confocal microscope. The study of such ―images‖ obtained under various conditions shows that these particles exist as independent objects; the process of formation of perfect ds DNA CLCD takes time, and the mean size of the ds DNA CLCD particles depends on initial concentration of the ds DNA molecules used for the phase exclusion.

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Figure 13. The fluorescence image of the ds DNA CLCD particles treated with SYBR Green. СDNA = 50 μg/ml; 24.5x10-6 M SYBR Green; 0.3 M NaCl; 170 mg/ml PEG; Confocal microscope ―Leica TCS SP5‖;

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Bar – 4 μm.

Above we were dealing with drugs (―external chromophores‖), which were rigidly fixed in the DNA secondary structure at angle close to 900. However, following the F. Saeva [69] and B. Norden [73] theoretical consideration, the sign of the intense band in the CD spectrum in the region of absorption of ―external chromophores‖ (drugs) incorporated into cholesteric matrix will depend on their orientation with respect to the director of quasinematic layer, which in our case coincides with the mean orientation of long axes of the ds DNA molecules. It was demonstrated above that if an angle of inclination of the chromophore of drug relative to the DNA helix is ~ 90°, the sign of its band coincides with that of the band typical of the DNA nitrogen bases. However, if the drug is located on the DNA molecule so that the angle of inclination of its chromophore is within 0°-54°, the intense band in the CD spectrum can have a sign opposite to that of the band characteristic of the DNA nitrogen bases [71]. Finally, if the drug is oriented under a ―magic angle‖of inclination (54.70) the intense band in the CD spectrum can be even absent [71, 73, 76] despite its interaction with ds DNA molecules in quasinematic layers. Usually, the situation with different inclination angles is characteristic of so-called ―groove-binders‖, i.e. compounds, which are fixed in some way in the grooves on the surface of ds DNA molecules. Figure 14 illustrates the CD spectra for preformed CLCDs treated by two groove-binders, i.e. chemically analogous compounds - DBBI (i.e. dimeric bisbenzimidasol or dimeric Hoechst 33258 molecules) and original Hoechst 33258. In the case of Hoechst 33258 one can see the intense band in its absorption region is absent despite interaction of this drug with the ds DNA molecules. However, in the case of its analog - DBBI, the treatment of the CLCD results in an appearance of an intense positive band (λ ~ 320 nm), despite maintaining the

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intense negative band in the region of absorption of nitrogen bases. This fact shows that for the chromophores, which are located under various angles in respect to the DNA long axis, different signs are, indeed, specific, despite the fixed handedness of the ds DNA cholesteric structure. This confirms once more the statement that the intense band depends on long-range arrangement of chromophores but not on local parameters of the ds DNA secondary structure.

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Figure 14. The experimentally measured CD spectra of the ds DNA CLCD added with DBBI (curves 13) and with Hoechst 33258 (curves 1I – 3I). Insert: DBBI absorption spectrum; 1 – 0; 2 – 0.69; 3 – 2.5x10-6 M DBBI; 1I – 0; 2I – 1.22; 3I – 4.86x10-6 M Hoechst 33258; СDNA = 16.2 μg/ml; 0.3 M NaCl; 170 mg/ml PEG; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

Thus, the theoretical approach used to describe the CD spectra of nucleic acid CLCDs allows one to evaluate such parameters as the sense of twist of the ds DNA quasinematic layers in the structure of CLCD particles. This can determine the characteristic sizes of individual CLCD particles, as well as to assign the relative orientation of the nitrogen bases and various compounds.

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2.2. The CD Spectra of CLCDs Formed by Double-Stranded DNA Molecules Under Various Conditions

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2.2.1. The Amplitude of the Intense Band in a CD Spectrum Depends on the Length of the ds DNA Molecules Used for Formation of CLCDs. When they are short (less than 50 nitrogen base pairs or about 15 nm) no dispersion with an abnormal optical activity can be formed (Figure 15). Note that unlike a conventional aggregation of DNA molecules, which is independent of their lengths and is not accompanied by an appearance of abnormal optical activity, the CLCD is formed only when the length of the ds DNA molecules exceeds definite length. This result demonstrates the existence of a lower limit of DNA length for the formation of optically active dispersion. The upper limit of ds DNA molecular mass, where these molecules preserve their ability to form the CLCD, is close to 3x106 Da [48]. A further increase in DNA length leads to a decrease in the amplitude of the abnormal CD band displayed by dispersion, despite still being formed, as detected by the appearance of the apparent optical density in the absorption spectrum. For a ds DNA molecular mass exceeding 10x106 Da, the CD spectra for dispersions are similar enough to the CD spectra of the initial isotropic linear ds DNA solution. The absence of an abnormal optical activity of the dispersions formed by high-molecular-mass ds DNA demonstrates an important role of kinetic factors in the packing mode of ds DNA molecules.

Figure 15. The dependence of the amplitude of negative band (∆Α270) in the CD spectra of the ds DNA CLCD on the DNA molecules length. СDNA =15 μg/ml ; 0.3 M NaCl; 170 mg/ml PEG; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

The formation kinetics of the CLCD particles from ds DNA or synthetic polynucleotide molecules is a complex process [77] and is described in terms of the classical KolmogorovAvrami equation [78, 79]. This kinetics comprises the nucleation of the optically inactive center of the liquid-crystalline phase and its growth, accompanied by the spatial twisting neighboring DNA molecules and the emergence of an abnormal optical activity characteristic

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of dispersion particles. Such a kinetic pattern reflects the existence of an energy barrier, which DNA molecules must overcome to provide the separation of DNA molecules between the isotropic phase outside the dispersion particles and liquid-crystalline phase inside them and the twist of neighboring DNA molecules. The size of the DNA CLCD particles shown in Figure 1 is determined by a fine balance between the free energy of these particles and their surface free energy [51, 54, 80]. The competition between the free energy of the dispersion particle (tending to increase the particle size) and its surface free energy (which depends on the surface tension between the cholesteric phase and isotropic phase and is directed to a decrease of the surface between the DNA-rich phase and the isotropic solution [51, 54]), suggests the existence of a critical size of dispersion particles below which they are unstable or do not form at all. According to experimental results and theoretical estimations, the average size of dispersion particles depends on both DNA concentration and PEG concentration used for phase exclusion [47, 49].

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2.2.2. The Amplitude of the Band in the CD Spectrum Depends on Properties of the Solvent, Determined by Concentration of PEG (CPEG), in a Complex Manner (Figure 16) A negative band appears in the CD spectrum only after CcrPEG has been reached. Its amplitude reaches a maximum at CPEG ≈ 160-180 mg/ml, and then drops abruptly, although dispersions, that scatter light, have been formed. This effect means that the spatial structure of the DNA CLCD unwinds (the pitch increases) as the total concentration of PEG is increased (the osmotic pressure is increased) in the solution [51, 54, 81].

Figure 16. The dependence of the amplitude the negative band in the CD spectrum of the ds DNA CLCD versus PEG concentration in solution. 1- KCl; 2-KBr; 3-KI; СDNA = 25 μg/ml; 0.3 M solutions; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

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2.2.3. The Effectiveness of Formation of DNA CLCDs Depends on the Nature of the Cations and Not on the Nature of Anions Present In Solution [52] The value of CcrPEG is lower by 60 mg/ml in a solution with Na+ than in a solution containing Cs+ cations and having the same ionic strength. Nucleic acid dispersions with an abnormal optical activity are formed in PEG containing solutions only when 82 per cent of the negative charge of the phosphate groups is neutralized with counterions. These data are consistent with theoretical and experimental estimates [82, 83], which characterize the neutralization level of DNA molecules necessary for their aggregation in water-salt solutions. The discrepancy with the theoretical value (88-90 per cent) may simply reflect the existence of differences between the dielectric constants of water-salt and water-salt-PEG solutions. Therefore, depending on properties of the solvent, some dispersions are optically active while other dispersions do not possess such an activity. In terms of the theory, the twist angle, , of quasinematic layers in a CLCD depends on the ratio of the dielectric parameters of a medium and of the ds DNA molecules which form these dispersions, as well as on temperature. 2.2.4. In Framework of the Above Theoretical Considerations There is a Very Important Question Regarding the Role of the Secondary Structure of Nucleic Acids in an Appearance of Intense Bands in the CD Spectra Figure 17 demonstrates the experimental CD spectra of CLCDs formed in a PEG containing solution by right-handed, synthetic ds polynucleotides (B-family): poly(dA)x poly(dT) (curve 1) and poly (dA-dT)xpoly (dA-dT) (curve 2) with identical molecular mass, but different nitrogen base sequences in the chains. These dispersions have the same light scattering, but differ in the signs of the intense band in the CD spectrum. The CD spectra are mirror-images of each other. In view of the theoretical calculations, the change in the sign of the band in the CD spectrum shows that, in contrast to the left-handed cholesteric dispersions formed by molecules of poly(dA-dT)xpoly(dA-dT), molecules of poly(dA)xpoly(dT) form CLCDs with a right-handed twist [48]. The detailed study of dispersions formed by different synthetic, ds polyribonucleotides (the A-family), showed that ds RNA or poly(I)xpoly(C) molecules create two types of dispersions [78] which differ in the sign of the intense band in the CD spectra (Figure 18). The transition between dispersions which differ in the sign of this intense band can be caused by changing either the PEG concentration in the solution (for ds RNA) or the ionic strength (for poly(I)xpoly(C)). The ds polyribonucleotides: poly(A)xpoly(U) and poly(A)xpoly(dT) yield dispersions which have CD spectra with only a positive band under any experimental conditions used [84]. Besides, poly(dG-dC) x poly(dG-dC) molecules at a high ionic strength ( > 2.6), belonging to the left-handed, helical Z-form, can generate two families of dispersions which differ only in the signs of the intense bands in the CD spectra.

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Figure 17. The CD spectra of the CLCD formed by poly(dA)xpoly(dT) (curve 1) and by poly(dAdT)xpoly(dA-dT) molecules (curve 2).

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0.3 M NaCl; 170 mg/ml PEG.

Figure 18. The CD spectra of the CLCD formed by poly(I)xpoly(C) at various ionic strength of the solution. 1- 0.8; 2- 0.93; 3-1.0; 4 -1.13 М NaCl; СDNA =5.5 μg/ml; 0.3 M NaCl; 170 mg/ml PEG; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

Figure 17 and Figure 18 show that very small alterations in the structures of ds molecules of nucleic acids can be sufficient to cause the change from a left-handed to a right-handed spatial twist in the structure of the CLCD particles. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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Therefore, nucleic acid molecules belonging to different families (right- handed В- and A- or left-handed, Z-forms) could be used to create CLCDs, which are characterized by the CD spectra with intense bands of different signs in the absorption region of the purine and pyrimidine bases. Because nitrogen bases are fixed in respect to long helices of ds molecules of nucleic acids, the appearance of the intense bands speaks only in favor of different handedness of cholesteric structures formed by these molecules. This means, in turn, that nitrogen bases do not ―feel‖ the secondary structure of nucleic acids or, one can say, that long-range order of nitrogen bases in quasinematic layers is not correlated, in general, with short-range, local order of ds molecules forming CLCD particles (determined by X-ray studies). However, the peculiarities of the secondary structure of nucleic acids have a profound influence on the character of interaction between nucleic acids ―at the moment of their recognition at close approach‖ and mutual twisting of these molecules at formation of particles of the CLCDs. Figure 19 shows that the ―isotropic to cholesteric" transition in the DNA dispersions takes place in the distance region of about 5.0 nm. At these distances a ―twisting factor‖ begins to act. This process is accompanied by the development of abnormal optical activity of dispersions due to the low energy of nucleic acid molecules twisting. In favor of this statement speaks the fact that the energy difference between the parallel and the crossed (90°) positioning of two interacting 50 nm-long DNA molecules spaced about 4.0 nm (0.2 M NaCl) is equal to 1 kT [85-87]. Under these conditions the negligible changes in the properties of the secondary structure of nucleic acids must be accompanied by a change in the sign of the intense band in the CD spectrum. Hence, the amplitude of abnormal band in the CD spectra of CLCDs formed by nucleic acids represent by itself an idle, easily detectable criterion, reflecting both the formation of the CLCD particles from rigid, linear, ds molecules, and the change in the properties of these particles under action of various factors. The structures of these particles depend on parameters, such as DNA concentration, DNA length, counterion type and concentration, as well as concentration of PEG [47, 54].

Figure 19. The dependence of the distance (dinter) between ds DNA molecules in the content of CLCD versus osmotic pressure of solution. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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2.3. The CD Spectra of the CLCD Formed by ds DNA Molecules First Treated with Compounds Carrying Positively Charged Groups 2.3.1. The CD Spectra of the CLCD Formed by ds DNA Molecules First Treated with Colored Cationic Intercalator The results presented in the previous sections, allow us to say that, in general, a pure steric model (a model of classical cholesteric LC, formed by piling up several rigid righthanded screws) is probably inadequate for description of cholesteric ordering of ds DNA in the particles of the liquid-crystalline dispersions. The DNA-DNA surface-to-surface distances in cholesteric structures are about 1.5-2.5 nm as showm above. At these distances the steric hindrance of contacting DNA grooves is unlikely to be the dominant factor for stability of these structures [11, 88]. This means that, in general, the connection between molecular and phase chirality is not so simple and not straightforward [10, 89]. The complexity becomes even higher in the case of the simultaneous presence of a few levels of chirality. To illustrate the complexity of this problem we have compared the CD spectra for the CLCDs formed by ds DNA molecules first treated with colored cationic intercalator of anthracycline group - daunomycin. Daunomycin molecules intercalate between ds DNA nitrogen base pairs as it was shown above (Figure 9 and Figure 10). Figure 20 compares the CD spectra of CLCDs formed by (DNA-daunomycin) complexes at various concentrations of daunomycin. One can see that the CD spectra contain two intense bands located both in the ds DNA and daunomycin absorption regions (about 270 and 500 nm, respectively). According to the theory, the presence of the negative band in the CD spectrum of CLCDs formed at low daunomycin concentrations in a complex (DNAdaunomycin) is indeed reflects the insertion of DAU molecules between DNA nitrogen bases. This means that the angle between the daunomycin molecule and the ds DNA long axis is ~ 900. An appearance of two intense negative bands located in different regions of the CD spectrum speaks in favor of left-handed twist of the cholesteric structure formed by (DNAdaunomycin) complexes. However, as can be seen in Figure 21, upon increase of daunomycin concentration in the content of (DNA-daunomycin) complexes the amplitudes of both bands in the CD spectrum of the CLCD are simultaneously diminished. In the framework of theory, this means that under the influence of antibiotics the untwisting of the helicoidal structure of the cholesteric of the CLCD formed by (DNA-daunomycin) occurs. Then both negative bands change their signs (Figure 21). This effect was experimentally detected first in [90] and confirmed in [91]. The comparison of Figure 20 to Figure 21 shows that formation of the (ds DNA-daunomycin) complexes, and hence, the different extent of fixation of daunomycin molecules in the structure of the ds DNA molecules, influences the mode of ―recognition‖ of molecules of these complexes at their close approach, and affects the mode of their packing in the particles of CLCDs. (It should be noted that under all experimental conditions ds DNA molecules maintain the right-handed helical structure). The presence of free daunomycin molecules in the solution has no effect on the amplitude of the band in the CD spectrum). One can say that if the daunomycin concentration is lower than 8 M, (DNA-daunomycin) complexes form left-handed CLCD and at daunomycin concentrations exceeding 8 M, right-handed cholesteric is formed, and the CD spectrum contains two positive bands.

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Figure 20. The experimentally measured CD spectra of the CLCD formed by (DNA-DAU) complexes. Curves 1– 6 - rt = 0; 5.7; 7.5; 9.5; 11.3; 18.9x10-6 M DAU; СDNA = 20 μg/ml; 0.3 M NaCl; 170 mg/ml PEG;

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∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

Figure 21. The dependence of the amplitude of the band (∆Α270 , left ordinate) and (∆Α500 , right ordinate) in the CD spectra of the CLCD formed by (DNA-DAU) complexes on total DAU concentration in solution. СDNA = 20 μg/ml; 0.3 M NaCl; 170 mg/ml PEG; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un.

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To confirm this statement, the textures of the thin layers of CLC phases obtained as a result of low-speed centrifugation of the CLCDs formed by different (DNA-daunomycin) complexes were analyzed. If the daunomycin concentration lies in the range of 0-64 M, the texture of the (DNAdaunomycin) CLC phase is characterized by the presence of alternating dark and light lines (Figure 22 A, B). Textures shown in Figure 22 A, B are known as ―fingerprint‖ textures. They are characteristic of cholesteric LCs formed by various compounds, including ds DNA. The same is correct for the textures of the (DNA-daunomycin) CLC phases formed within 10.619.0 M range of daunomycin concentration (Figure 22 E, F).

Figure 22. The optical textures of the thin layers of liquid-crystalline phases formed by ds DNA molecules and their complexes with DAU. A – F - СDAU = 0; 6.4; 8.2; 8.8; 11.1; 19.1x10-6 M; 0.3 M NaCl; 170 mg/ml PEG; Bar – 10 μm.

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However, one can see that upon raising the daunomycin concentration, the type of texture the CLCD phase changes. At ~ 8 M of daunomycin, ―nematic‖ LCs are formed. They are distinguished by the absence of both helical structures and intense band in the CD spectrum. The periodicity (S) of the equidistant lines observed in Figure 22 is related to the pitch (P) of the cholesteric structure formed by the (DNA-daunomycin) complexes as follows: P = 2S. (The error in P determination was 10%). The dependence of P value upon daunomycin concentration is shown in Figure 23. It can be seen in Figure 23 that at daunomycin concentration of about 8 M the value of P tends to infinity. (Attention is drawn to the fact that experimentally measured and theoretically calculated above ―limiting‖ P-values (see 2.1.1.3) are of the same order of magnitude.

Figure 23. The dependence of the pitch of the cholesteric structure formed by (DNA-DAU) complexes on total DAU concentration in solution. 0.3 M NaCl; 170 mg/ml PEG.

The authors [91] assumed a possible mechanism to explain the band sign reverse in the CD spectra. This mechanism takes into account that the charged amino groups of the sugar residues of daunomycin ―remain‖ on DNA surface. Therefore, at daunomycin intercalation a helical distribution of efficient lateral dipoles arises near ds DNA surface. This provides an additional contribution to the chiral interaction between approaching (as a result of the phase exclusion) molecules of (DNA-daunomycin) complexes. At a fixed distance between neighboring positive charges due to the presence of amino groups in intercalating daunomycin molecules, an arising additional contribution leads to change in the helical twist of the cholesteric structure formed by the (DNA-daunomycin) complexes. Depending on the amount of fixed amino groups near the surface of the right-handed, ds DNA molecules (B-

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family), the (DNA-daunomycin) complexes can form two types of CLCDs, which differ in the handedness of their twist and in the signs of the intense bands in the CD spectra. However, not all compounds of the anthracycline group, being chemical homologues of daunomycin, are capable of triggering the reverse of the negative band in the CD spectra of CLCDs formed by their complexes with ds DNA [90]. This means that the question of extent, in which intercalation of anthracyclines and a mode of charge distribution of the positive groups of anthracyclines near the surface of the ds DNA molecule can modify the spatial properties of the formed CLCDs, is still unclear. One must also remembering that the properties of the DNA CLCDs cannot be explained only in framework of interaction between approaching ds DNA molecules without taking into account the presence of solvent (water) around neighboring ds DNA molecules. It was assumed that in the case of a small distance between (DNA-daunomycin) complexes, a particular ―phantom‖ structure of solvent can form around, which can act both as an elastic medium affecting the interaction between the molecules of these complexes and as a medium in which collective photon tunneling can take place. These two effects provide for ―recognition‖ of approaching (DNA-daunomycin) complexes and stabilize the cholesteric mode of packing these complexes in particles of CLCDs [92-94]. The above results confirm the statement that the correlation between molecular and phase chirality is not simple [10, 89] and long-range forces should be taken into account as ―contributors‖ to the formation of cholesteric structure of (DNA-daunomycin) complexes [32]. The complexity of this problem becomes even higher in the case of the simultaneous presence of various levels of chirality, for instance, in the case of the CLCDs formed by (DNA-chitosan) complexes.

2.3.2. The CD Spectra of the CLCD Formed by Ds DNA Molecules First Treated with Polycation A biodegradable polymer, chitosan (Chi, a copolymer of β-(1→4)-2-amino-2-deoxy-Dglucopyranose and β-(1→4)-2-acetamido-2-deoxy-D-glucopyranose residues) attracts great attention now as a good candidate for formation of CLCDs. Indeed, the chemical and spatial structures of chitosan molecules determine their ability to form stable complexes with various compounds [95,96]. In fact, data obtained recently show that ds DNA molecules might exist in a LC state because of (DNA-chitosan) complex formation [97]. It should be noted, however, that the properties of the complexes formed by chitosan and DNA molecules remain poorly studied [98-100]. Chitosan interacts with ds DNA in such a manner that the amino groups of chitosan sugar residues not only neutralize the negative charges of the DNA phosphate groups, but also create a particular distribution of positively charged amino groups in proximity to the DNA surface [101]. The details of the local structure of (DNA-chitosan) complexes depend on (i) the peculiarities of helical grooves on the surface of the DNA molecules, where the negatively charged phosphate groups are located and, probably, (ii) the peculiarities of the helical structure of the chitosan molecules, such as the sense of helical structure, that provide the most efficient steric contact with DNA molecules. So, the orientation of the chitosan molecules and the distribution of amino groups of chitosan sugar residues on the surface of the DNA molecules can define the character of the interaction between neighboring approaching DNA molecules and, hence, the direction of the spatial twist of these molecules

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in the resulting LCDs. One can suppose that not only the chemical, but also the spatial structure of chitosan affects the character of the packing of (DNA-chitosan) complexes in the particles of the LCDs. This means that this situation can be considered more complicated in comparison to the daunomycin case. However, the positive aspect of this situation lies in the fact that the chitosan preparations, which differ in the concentration of amino groups and in molecular mass, are now available now for experimentalists [102, 103]. We have studied the role of positive charge distribution fixed near the DNA surface as a factor of triggering the twist of spatial structure of the CLCDs formed by DNA molecules first complexed with chitosan molecules. For this reason we have compared the peculiarities of the CD spectra of the CLCDs formed by (DNA-chitosan) complexes in water-salt solutions [104]. Figure 24 compares the CD spectra of the initial DNA (curve 1) and of LCD of (DNAchitosan) complexes (curves 2 - 6). It is seen that an intense positive band appears in the DNA absorption region (~ 270 nm) when the ―critical concentration‖ of chitosan is achieved (insert in Figure 24). This means that titration of the water-salt solution of ds DNA with chitosan is accompanied not only by the formation of dispersions of DNA-chitosan complexes that scatter UV-irradiation, but also by the appearance of the intense positive band in the CD spectrum of these dispersions. These two processes take place simultaneously only above the threshold of chitosan binding with DNA.

Figure 24. The experimentally measured CD spectra of the CLCD formed by (DNA-chitosan) complexes. Curves 1-6 – Ctot = 0; 2.5; 5.0; 6.25; 7.8; 8.75 μg/ml of chitosan in the solution (chitosan: 85% of amino groups; mol. mass 19 kDa); СDNA = 15.5 μg/ml; 0.15 M NaCl; ∆Α = (ΑL - ΑR) х 1х10-5 opt.un; Insert: The dependence of the ∆Α270 value versus CChi.

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The formation of dispersions due to the interaction of ds poly(dA-dT)xpoly(dA-dT) and ds poly(dG-dC)xpoly(dGdC) with chitosan, similar to the case of ds DNA molecules, results in an appearance of positive rather than negative bands in the CD spectra. The abnormal band in the CD spectrum reflects the formation of cholesteric structure of the (DNA-chitosan) complexes in particles of the LCDs. However, in contrast to ―classical‖ ds DNA cholesterics, which possess intense negative bands in the CD spectra and hence relate to left-handed twisting of the spatial structure, the cholesterics of (DNA-chitosan) or (polydeoxyribonucleotide–chitosan) complexes are characterized by right-handed twisting. Figure 25 shows the dependences of the intense band in the CD spectra of CLCDs of (DNA-chitosan) complexes in solutions of various ionic strengths upon the distance between amino groups in the chitosan molecules.

Figure 25. The dependence of the maximal amplitude of the band (λ = 270 nm) in the CD spectra of the CLCD formed by (DNA-chitosan) complexes on the average distance, R, between amino groups in chitosan molecules. The average distance R between amino groups in chitosan molecules was estimated from ratio: R (A0) = 2 x (5.15 x 100%)/ (NH2), where: 5.15A0 is the distance between two neighboring repeating chitosan units, coefficient 2 takes into account the fact that, due to sterical restrictions, neighboring chitosan amino groups participate in neutralization of the negative charges of phosphate groups of DNA in alternating mode; (NH2) is a percentage of amino groups in chitosan sample. Curve 1 - (filled squares) molecular mass of chitosan – 14.6 kDa, Curve2 - (squares) molecular mass of chitosan – 8.4 kDa, Curve 3 – molecular mass of chitosan – 5.0 kDa, Curve 3I - takes into account the concentration of ―free‖(i.e., noncomplexed with chitosan) DNA molecules; Curve 4 - molecular mass of chitosan – 14.6 kDa, 0.15 M NaCl; Curve 5 - molecular mass of chitosan – 14.6 kDa, 0. 5 M NaCl; CDNA = 15.5 μg/ml; 0.05 M NaCl.

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First, one can see that the intense band is a complex function of the distance between amino groups in the chitosan molecules used for preparing dispersions. The amino group content determines the possibility of formation of two types of CLCDs having either negative or positive abnormal bands in the CD spectra (curves 1-3, Figure 25). Furthermore, definite contents of these amino groups can result in dispersions having no abnormal optical activity, the ΔA value becoming zero at both long and short distances between amino groups in the chitosan molecules. Second, the amplitude of the intense band is a function of ionic strength. The higher is the ionic strength the lower is the amplitude of the band in the CD spectra (compare curves 1, 4, 5, Figure 25) at fixed content of amino groups and mol. mass of the chitosan molecules. Finally, the decrease in chitosan molecular mass from 8–14 to 5 kDa results in displacement of the obtained dependences to the region of lower amino group content (compare curves 1, 2 and 3). Figure 25 speaks in favor of multiple spatial forms of the (DNA-chitosan) CLCDs depending on specific preparation conditions. This means that the mode of the spatial packing for the molecules of (DNA-chitosan) complexes in CLCDs depends on the character of fixation of the chitosan molecules on the surface of the ds DNA molecules. Hence, the distribution of positive charges (distance between charges, chitosan conformation, etc.) in the chitosan molecule interacting with ds DNA is the determining factor for the spatial structure of the resulting dispersions. Such an interaction provides not only the neutralization of the negative charges of DNA phosphate groups, but also makes it possible to ―introduce‖ an additional positive charge into the surface structure of the DNA molecules that, in turn, determines the value of the anisotropic contribution to the free energy of interaction of neighboring (DNA-chitosan) complexes. This means that the change in the distribution of positive charges in chitosan molecules interacting with DNA can influence the mode of spatial twist of the (DNA-chitosan) complexes. Hence, the handedness of helicoidal arrangement depends not only on the parameters of the right-handed DNA molecule (Bform), but on the mode of the charge distribution near the surface of the DNA molecules induced by formation of complexes at various properties of chitosan molecules [105]. Principal explanation of the observed effects for the CLCDs formed by ds DNA molecules complexed with low- and high mol. mass polycations is based, in general, on theoretical notions [106], according to which the ordered arrangement of electrical dipoles along the long axes of helical polymeric molecules can affect the properties of the LC phase produced by phase exclusion of these molecules. It is implied that the dipoles are perpendicular to the polymer molecular axis and smoothly rotate around it to form their own helical structure. The polymeric molecules are assumed to involve short-range steric repulsions, which favor nematic ordering of neighboring molecules in the formed phase, and dipole-dipole interactions, which produce the perturbations resulting in the helical twisting of the phase, i.e. the formation of the cholesteric phase. Depending on the sense of the spatial twist of the helical structure in the nascent phase, one can expect an appearance of the CD bands of different signs. Phase exclusion of complexes resulting from the interaction of ds DNA molecules with polypeptides of different chemical structure and carrying positively charged amino groups, is known to give rise to the formation of CLC dispersions having different signs of the abnormal optical activity, in particular, intense bands in the CD spectra [107].

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In the DNA CLCDs, the direction of the helical twist of their cholesteric structure changes with temperature or the dielectric properties of the solvent, and this can be explained in theoretical terms by the disbalance of the forces of steric repulsion and dispersion interaction of the helical segments of the nucleic acid. Following [91] one may suppose that a mechanism, responsible for the reverse of an intense band for CLCDs of (DNA-daunomycin) complexes, also takes place in case of the (DNA-chitosan) system. Due to the spatial features of the chitosan molecules, the amino groups could interact with the phosphate groups of DNA in an alternating mode [108]. This provides not only the orientation of chitosan molecules along the DNA long axis upon complexation, but also the formation of a helical array of electric dipoles. At a certain distance between the charged amino groups of chitosan arranged along the DNA, the corresponding dipole-dipole interaction may compensate the contribution of the chiral interaction between DNA molecules. In this case, the direction of the spatial twist for the helical structure of the cholesteric dispersions of the (DNA-chitosan) complexes may change, and this in turn will result in a modification in the sign of the intense band in the CD spectra. A phenomenological expression for the free energy of a cholesteric liquid crystal follows [88, 106] : Fd =(1/2) K22 (n rot n)2 +  (n rotn)

(10)

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where: the unit vector n(r) is a director that defines the average orientation of the long axes of molecules forming the liquid crystal; K22 is the twist elastic constant; the pseudoscalar parameter  determines cholesteric turn and depends only on the chiral part of the intermolecular interaction potential. In the case of cholesteric twisting, nx = cos (z), ny = sin (z), nz = 0 and the free energy minimum corresponds to the helical distribution of the director n(r) with pitch (Р): 2/Р = / K22

(11)

For DNA molecules bound to daunomycin [91], electrostatic interaction between two charged helical structures of the (DNA-antibiotic) complexes provides the following contribution for parameter : d= - (9/16)(d42L/kT) exp( - 2xR)R-6sin(2qb)

(12)

where: R = (R02+b2)1/2; d = r0e; q = 2/ps; ps - is the pitch of the helical structure of the B form of the ds DNA molecule. In this case: r0 is the radius of DNA molecule, L is the length of DNA molecule,  is the number of DNA molecules per volume unit,  is the number of closest neighbors, R0 is the average distance between DNA molecules in the arising phase,

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Yu. M. Yevdokimov, V. I. Salyanov, S.G. Skuridin et al. b is the average distance between neighboring positive charges of antibiotic molecule.

The exponential factor in the expression for d corresponds to the electrostatic shielding of negative charges of DNA phosphate groups by counterions in solution. In equation (12), x means the Debye–Huckel screening parameter x = (8  e2/100 εr kT) ½ I ½ where: I is the solution ionic strength, εr the dielectric constant of solvent, and the other parameters have the standard meanings. The pitch of the DNA cholesteric structure is determined by two factors: parameter d, depending on bound daunomycin molecules, which affects the value of b, and the contribution of all other chiral interactions between DNA chains, - 0.

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2 /Р= (0 - d)/ K22

(13)

where: Р is the pitch of the cholesteric structure formed by the DNA molecules. At particular magnitudes of b, value 0-d becomes zero, which causes disappearance of the helical twist of the cholesteric dispersion of (DNA-daunomycin) complex and, hence, of the intense band of resulting LCD. Moreover, an alteration in the sign of the initial band of the cholesteric is possible at certain values of 0 and d. (It should be noted that the increase in daunomycin concentration is equivalent to the decrease in the distance between the positive charges fixed on the DNA surface). One may suppose that similar consideration is also correct for the (DNA-chitosan) system due to the specific properties of chitosan molecules. Indeed, helical chitosan molecules contain amino groups carrying partial positive charge at pH ~ 7 and they could interact with the phosphate groups of DNA in alternating mode [108]. This causes not only the orientation of chitosan molecules along the DNA long axis upon complexation but also the formation of helical structure of electric dipoles. At a certain distance, b, between the charged amino groups of chitosan arranged along the ds DNA molecule, the corresponding dipole-dipole interaction may compensate by the contribution of the dispersion chiral interaction between (DNA-chitosan) complexes. In this case, the direction of the helical twist of (DNA-chitosan) complexes in the structure of the cholesteric dispersions may be changed, that, in turn, will result in alteration in the sign of abnormal optical activity of these dispersions. Let us consider that the molecular mass of the ds DNA used in the chitosan-DNA complex formation, was about 7x105 Da. This corresponds to the molecular length of L = 3.5x10-7 m, while the R0 value estimated from the X-ray diffraction study was 30x10-10 m, the calculation of d versus b, i.e. the distance between the amino group charges, was performed for different values of parameter х (defined by solution ionic strength) at the following magnitudes of other parameters (see equation 12):  =1025м-3; r0 = 1010-10 м ;  = 6; T = 250 C Figure 26 shows a few theoretical curves calculated for the (DNA-chitosan) CLCDs under various conditions. Although the calculations performed are approximate and ignore

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parameters such as the polymeric nature of the chitosan molecules, possible conformational change of the chitosan molecules in solutions of different ionic strength, etc., the above calculations have several consequences: (i) the value of d changes while decreasing the distance between amino groups in the chitosan molecule and becomes zero at specific distances between them; (ii) parameter d increases when the ionic strength of solutions necessary for formation of the ds (DNA-chitosan) CLCDs decreases.

Figure 26. The theoretical dependences of the parameter d calculated for CLCD formed by (DNA-Chi) complexes on average distance, b, between positively charged amino groups in chitosan molecules.

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Curves 1 - 3 correspond to x values at different ionic strengths; 1- 0.263; 2 - 0.3; 3 - 0.38.

Assuming that parameter d is associated with the pitch of the cholesteric helical structure according to equation (13), the decrease of the pitch of the cholesteric structure of (DNA-chitosan) LCDs indicates that the twist of the cholesteric structure could occur as the solution ionic strength decreases. In this case one may expect an increase in the amplitude of intense band for this structure. It should be noted that, the pitch of the cholesteric structure is associated not only with d, but also with 0 (equation (13). It is obvious that the theory is not yet sufficiently perfect to predict all peculiarities of intense bands of the CLCDs resulting from molecules of (DNA-chitosan) complexes. However, the theory does allow one to predict the tendency of changes in amplitude of intense bands upon alteration in the b value or solution ionic strength. Figure 25 shows data describing the abnormal band in the CD spectra of (DNA-chitosan) cholesteric dispersions obtained under different conditions. Comparing these curves, we can note the following: 1) The sign of the abnormal band in the CD spectrum of the cholesteric phase of the (DNA-chitosan) complexes is changed when the b value, i.e. the distance between charged amino groups in the chitosan molecule, decreases. The data from [105]

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indirectly testify to the alteration in the band sign, i.e. the direction of the helical twist of the DNA-chitosan cholesteric, with change in the distance between the charged groups on the DNA surface. 2) At a constant distance between amino groups, in particular at b = 5.0 or 12 A°, the decrease in ionic strength of the solution where the (DNA-chitosan) cholesteric phase arises is indeed accompanied by an increase in the amplitude of the negative CD band of this phase (compare curves 5 and 1 in Figure 25). This result agrees positively experimental data [109], which shows that the shorter the pitch of the cholesteric helical structure for the particles of DNA LCDs, the higher the amplitude of the intense band in the CD spectrum. 3) Under certain conditions, (DNA-chitosan) complexes could produce phases having no abnormal band in the CD spectrum. Indeed, the formation of dispersions from (DNA-chitosan) complexes at pH ~ 8, in spite of the onset of an ―apparent‖ optical density, is not accompanied by changes in the shape of the CD band characteristic of the initial B-form of DNA and the emergence of an abnormal CD band under these conditions. This fact is of interest from two points of view. First, it indicates that scattering itself does not cause the appearance of the abnormal band in the CD spectrum. Second, it indicates that the character of the spatial packing of the (DNA-chitosan) complexes in particles of dispersions is associated with a strict equilibrium of the different types of interaction forces operating between these molecules. Thus, in spite of the limitations of the performed calculations, the main theoretical consequences of agree with the experimental results obtained for the (DNA–chitosan) CLCDs. The data above indicate not only the existence of numerous types of packing of molecules of (DNA-chitosan) complexes in LCDs, but it also shows that the physicochemical properties of these dispersions readily change upon alteration of the properties of both the chitosan molecules and the solution used for their preparation.

PART 3. THE CD SPECTRA AT ―LIQUID-RIGID‖ STRUCTURAL TRANSITION IN THE PARTICLES OF THE DOUBLE-STRANDED DNA CLCD In the system used for the ds DNA CLCD formation, with the stage of mixing of DNA and PEG solutions, the packing mode of ds DNA molecules in particles of dispersion is determined at the ―moment of their recognition‖ during the approaching DNA molecules neutralized by counterions negative charges on phosphate groups. After formation of the particles of ds DNA CLCD the mutual orientation of the ds DNA in these particles is constrained, although DNA molecules retain some diffusion degrees of freedom in quasinematic layers [110]. This means that the osmotic pressure of PEG solution, determined by PEG concentration, controls the packing mode of neighboring, linear, rigid, native ds DNA molecules in particles [51, 80]. The constant osmotic pressure of the solution determines not only a constant spatial structure of the ds DNA CLCD particles and, consequently, a fixed distance between ds DNA molecules in the quasinematic layers, but a

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fixed value of the amplitude of the intense band in the CD spectrum in the DNA absorption region. This information is the background for the elaboration of the approaches to transformation of the ―liquid‖ structure of particles of DNA CLCD into ―rigid‖ structure [111]. Returning to the quasinematic layer of ds DNA molecules within the CLCD particle (Figure 7), one can say that there is an interesting problem, which can be formulated as follows. ‖Is it possible to transform the ―liquid‖ structure of this layer to its ―rigid‖ state so that the spatial structure of the particles of the CLCD does not change and that the created structure would be able to exist in the absence of the osmotic pressure of PEG solution?‖ The theoretical description of the basic properties of ds DNA CLCDs allows one to suppose that there are two possible ways to answer this question: i) to cross-link neighboring DNA molecules located both in the same and neighboring quasinematic layers in the particles of the initial CLCD; ii) to increase the interaction between ds DNA molecules (or their fragments) by the action of chemical compounds on these molecules so that would lead to decrease in the solubility of the ds DNA molecules and the transition of CLCD particle into a rigid state.

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3.1. The CD Spectra of the ―Rigid‖ CLCDs Containing Nanobridges between Neighboring Double-Stranded DNA Molecules From the theoretical point of view, it is obvious that in order to form the cross-links between both neighboring ds DNA molecules in the same quasinematic layer (Figure 7) and ds DNA molecules in neighboring layers, these molecules should have the terminal sites for cross-links formation. This process requires, first, the presence of terminal sites located mainly on the surface of the ds DNA molecules. Theoretically, such a terminal site can be metal ions specifically fixed in a groove (grooves) on the DNA surface capable both of forming complexes with the DNA nitrogen bases and attaching other ligands that can be additionally introduced into the system. Besides, one can use as terminal sites the reactive groups in the content of planar compounds, which form the complexes with ds DNA molecules. Second, taking into account the steric location of the DNA reactive groups (in particular, the N-7 atoms of purines) in the grooves on the surface of the ds DNA molecules, it is evident that two neighboring ds DNA molecules can be cross-linked only if the spatial orientations of these groups are coordinated (i.e., the neighboring ds DNA molecules must be sterically ―phased‖ to realize the cross-linking of the same reactive groups). Finally, the theory predicts that when the forming cross-links between ds DNA molecules contain chromophores and these cross-links are specifically oriented in respect to the long axes of ds DNA molecules in quasinematic layers, one can expect an appearance of an intense band in the CD spectrum located in absorption region of the chromophores. All these points mean that the formation of cross-links is a delicate process that requires a number of conditions. Hence, the problem is reduced to the formation of artificial cross-links with adjustable properties between neighboring ds DNA molecules fixed (due to constant osmotic pressure of the used PEG-containing solution) at an interhelical distances of about 3.5 nm in quasinematic layers in structure of CLCD particles without significant change in the total spatial organization of CLCD particles. (Taking into account the length of possible cross-

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links one can consider them as ―nanobridges‖ between ds DNA molecules). This way was formulated in 1996 [112] and final results were obtained only recently because of collaboration among scientific teams from the Russia, Italy and Germany [113-116]. To solve the formulated problem, antibiotics of the antracycline group were used. These compounds, owing to their chemical structure, can form chelate complexes with cations of 2+

divalent metals, in particular, with Cu ions. Anthracycline chelate complexes can contain up to 10 repeating units; i.e., under certain conditions, anthracyclines can form extended planar

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2+

structures with Cu ions [114]. Formation of cross-links (nanobridges) was realized [116,117] according to the following scheme: initially, the ds DNA CLCD was obtained by mixing equal volumes of water-salt DNA and PEG solutions. Fixed volumes of daunomycin (DAU) solution were subsequently added to the DNA CLCD. Finally, this mixture was treated with a small volume of CuCl2 solution while stirring. Figure 27 the CD spectra of an initial DNA CLCD (curve 1). This dispersion was treated with DAU (curve 2), and then by CuCl2 solutions (curves 3). The amplitude of the intense negative band at λ ~ 270 nm indicates the left-handed twist of the spatial structure of CLCD and remains practically unchanged at any reasonable DAU concentration added to the CLCD. An addition of DAU to the DNA CLCD is accompanied by an appearance of a new band located in the absorption region of DAU chromophores (λ ~ 500 nm). The amplitude of this band is growing at an increase of DAU concentration, reaching the equilibrium value at the DAU concentration, which corresponds to the maximal degree of the DNA saturation by DAU molecules, and does not alter upon further growth of DAU concentration. (Note that the equilibrium amplitude of the band in the CD spectrum characteristic of (linear ds DNA-DAU) complex (not liquid-crystalline!) does not exceed a few units of ΔA). The negative sign of the band at λ ~ 500 nm reflects an intercalation of DAU molecules between the nitrogen base pairs of DNA molecules, fixed at particular distance due to the osmotic pressure of a PEG solution. One can see that the addition of CuCl2 solution to the DNA CLCD treated by DAU and having an equilibrium value of the amplitude of the band at λ ~ 500 nm results in a many-fold increase (amplification) of both this band and the band located in the UV-region of the 5

spectrum (curve 3). For instance, under the conditions used (the ds DNA mol. mass is 8 x10 Da and the DNA concentration is 5 μg/ml), the maximum amplitude of the band at λ ~ 500 nm is very high and equals approximately 2,500 (in ΔA units). The amplification of both of these bands begins only after the achieving a ―critical‖ concentration of copper ions in solution.

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Figure 27. The CD spectra of initial CLCD DNA (curve1) and of the same CLCD sequentially treated with daunomycin (curve 2) and CuCl2 (curve 3). CDNA= 5.4 μg/ml; CDau= 18.7x10–6 M; CCuCl2 = 10x10–6 M; 0.3 M NaCl; 170 mg/ml PEG;

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∆Α = (ΑL - ΑR) х 1х10-5 opt.un

The amplification of the bands at λ ~ 500 nm and λ ~ 270 nm indicates not only the formation of (Cu2+ -DAU) complexes, but also an appearance of an anisotropic arrangement of (Cu2+ - DAU) complexes both in proximity to DNA molecules and between the neighboring DNA molecules [114-116]. The direction of the long axis of cross-links formed by (Cu2+ - DAU) complexes, proves to be perpendicular to the direction of the long axis of DNA molecules. 2+

The number of Cu ions contained in the cross-links (nanobridges) under conditions that were used for formation of the ds DNA CLCD was estimated directly by the low-temperature 2+

magnetometry [118]. If Cu ion forms a chelate complex with four reactive oxygen atoms 9

this ion is in d state, which exhibits nonzero magnetic moment. The results obtained by the low-temperature magnetometry [118] and by the theoretical calculations [119] show that nanobridge between neighboring ds DNA molecules contains six copper ions, and nanobridge 2+

2+

2+

2+

(-Cu - DAU - Cu -…-Cu -DAU -Cu -) possess the structure shown in Figure 28.

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Figure 28. The scheme of nanobridge formation between ds DNA molecules. A – the structure of cross-link between two neighboring DNA molecules (view along the long axis of the molecules); B - the structure of chelate complexe of anthracyclines with Cu2+ ions (shown in blue); C – nanobridges between two neighboring DNA molecules (nanobridges are turned on 90o for convenience).

The nanobridges are composed of alternating molecules of anthracycline antibiotic and copper ions which are linked to the neighboring DNA molecules. Because the nanobridges arise both between neighboring ds DNA of the same quasinematic layer and between ds DNA molecules of neighboring layers, the formation of nanobridges, in principle, means that, instead of the osmotic pressure of PEG-containing solution, another factor of the spatial structure stabilization arises, specifically, the number and stability of nanobridges. The formed structure was named ―rigid‖ nanoconstruction, NaC (Figure 28). The results of small-angle X-ray scattering for NaCs, showed that formation of nanobridges between ds DNA molecules does not violate the initial spatial packing of these molecules; moreover, it leads to its stabilization. This means that a new structure would persist even in the absence of high osmotic pressure of the PEG-containing solution. In this case a possibility originates to investigate the properties of this structure not only by theoretical, but experimental techniques. For instance, an opportunity is opened to visualize

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the particles of ds DNA CLCD existing after their transformation into a spatially fixed structure and directly assess the size of the formed structures. For this purpose, the formed particles were immobilized on the surface of a nuclear membrane filter [115, 116] and the AFM (atomic force microscopy) images of particles were registered (Figure 29, A and B). The shape of the particles is close to elongated cylinders. Estimation of the size of more than 100 particles demonstrates that the sizes varied from 100-200 nm to 800 nm with 400-500 nm as the average (Figure 29, C), which is in good agreement with the data on the particle size calculated theoretically for the initial ds DNA CLCD particles in the solutions with a constant osmotic pressure. This means that the initial size of the CLCD particles was not changed in the course of the nanodesign process used. Hence, as a result of the formation of nanobridges composed of alternating anthracycline antibiotic and copper ions, which cross-link the ds DNA molecules located both in the same and neighboring quasinematic layers in the structure of particles of CLCD particles, a new 3D spatial structure arises. This process is accompanied by dramatic changes in the properties of CLCD particles.

Figure 29. The AFM images of nanoconstructions based on ds DNA molecules. A (2-D) and B (3-D) images of particles immobilized on nuclear membrane filter (PETF); C - Size distribution of of nanoconstruction particles; CDNA = 3 μg/ml; CPEG = 17 mg/ml; CDau = 7.2x10–6 M; CCuCl2= 1.9x10–6 M.

The created rigid NaC has unique properties. First, unlike the initial CLCD particles, the characteristic of the NaCs have both an amplified negative band in the CD spectrum in the DNA absorption region and an amplified band in the absorption region of antibiotic chromophores. Secondly, the diffusion mobility of the ds DNA molecules and the formed

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nanobridges as well as the chromophores in their content are practically absent; a ―liquid‖ packing mode of neighboring ds DNA molecules in CLCD particles disappeared; the diffusion mobility of neighboring ds DNA molecules ―froze‖ and the particle acquired the properties of a solid material. Thirdly, the main factor stabilizing the spatial structure of NaCs is the number and ―strength‖ of nanobridges rather than the osmotic pressure of the water-salt PEG-containing solution. Fourthly, the NaC is characterized by two thermal structural transitions: one of them corresponds to the melting of nanobridges and the other, to the melting of the ds DNA cholesteric structure. Finally, the NaC not only retained a high local concentration of DNA molecules (reaching 400 mg/ml), but it also acquired a high concentration of the antitumor antibiotic - (DAU). Therefore, the first reason to explain the amplification of the two bands located in different regions of CD spectrum of the ds DNA CLCDs after their consecutive treatment by DAU and CuCl2 is an appearance of nanobridges between neighboring ds DNA molecules, accompanied by the formation of a rigid spatial structure. The prerequisites for formation of nanobridges are the fixed distance between ds DNA molecules in the particles of CLCD,

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2+

determined by the PEG-concentration, the planar structure of (Cu - DAU) complex, and the steric ―phasing‖ (displacement and rotation around the long DNA axis) of neighboring DNA molecules because the reactive groups are located in the grooves on the surface of the DNA molecules [114, 116]. These requirements clearly show that the creation of rigid NaC is a very delicate stereochemical process, which can be realized only under rather strict conditions [120]. Taking into account the results of the above theoretical calculations, we can suppose as well, that besides the first explanation, there is an additional reason for simultaneous amplification of both bands in the CD spectrum of the ds DNA CLCDs. This is a change in the twist of neighboring quasinematic layers of CLCDs because they contain DAU molecules bonded with ds DNA and carrying positively charged amino groups. In this case an amplification of both bands in the CD spectrum of the ds DNA CLCDs can reflect the decrease in the P-value of cholesteric structure. A concrete role of this contribution was not analyzed until now. In conclusion one can add that it is quite clear that destruction of the integrity of nanobridges between ds DNA molecules under the action of various chemical or biologically relevant compounds will result in disintegration of spatial structure of DNA NaCs. This process should be accompanied by the decrease in the value of the easy detected CD band located in region of absorption of structural elements of nanobridges. This means that ds DNA NaCs can be used as a microscopic size multifunctional sensing unit (chip) for biological or chemical needs.

3.2. The CD Spectra of the ―Rigid‖ CLCDs Formed by (DNA-Gadolinium) Complexes It was experimentally shown that [121, 122] the steric limitations, resulting both from dense packing the ds DNA molecules in quasinematic layers and fixed osmotic pressure of PEG solution, prevent full separation of chains of the ds DNA molecules ordered in particles of the CLCDs. This means that the action of various compounds on ds DNA must not only

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induce the alterations in the secondary structure of these molecules, but also ―transform‖ into the changes in the interaction mode of neighboring DNA molecules (fragments) in quasinematic layers. For instance, the ―cross-linking‖ neighboring ds DNA molecules can change the mode of interaction between these molecules in the same and in the neighboring quasinematic layers. The theory [64] predicts, and experimental data in PART 2 show that in this case the parameters of the spatial structure of CLCD particles can be changed and, consequently, the magnitude of the intense band in the CD spectrum of CLCD is altered as well. Besides, under these conditions the particles of the ds DNA CLCD can acquire a ―rigid‖ instead of a ―liquid‖ structure, and the created structure would be able to exist in the absence of the osmotic pressure of a PEG solution. One of the simplest approaches to modification of the interaction between the ds DNA molecules in quasinematic layers is the neutralization of their negative charges under the action of counterions. Here two parameters are becoming important - the efficiency of interaction between counterions and the DNA phosphate groups, carrying negative charges, and the solubility of the (DNA-counterion) complex in water-salt solutions. The low solubility of these complexes would lead to the increase of the interaction between ds DNA molecules. This information allowed us to formulate the basic problem as follows. ―The action of the chemical substances on the ds DNAs ordered in quasinematic layers of particles of CLCD to diminish the solubility of these molecules so that the interaction between neighboring ds DNA molecules (or fragments of neighboring DNA molecules) would lead to the transition of these particles into ―rigid‖ state‖. It is known that there are plenty of positively charged ions and polycations that are able to neutralize the negative charges of phosphate groups in ds DNA molecules, causing a decrease in their solubility [47]. However, the cations of rare earth elements are of special interest from the standpoint of decrease of solubility of the ds DNA molecules in quasinematic layers. First, these cations can neutralize the negative charges of DNA phosphate groups in a wide range of conditions, and the complexes of rare earth elements with phosphates are practically insoluble [123-126]. Besides, the rare earth cations, interacting with the nitrogen bases of initial, linear, ds DNA molecules, cause local changes in the secondary structure of these molecules, which are analogous to the known B→Z transition [127, 128]. Last but not least, some of these cations, in particular, gadolinium, have found a wide practical application [129, 130]. Consequently, we used salts of rare earth elements and recently succeeded in solving the problem formulated above [128, 131-133]. Figure 30 compares the CD spectrum of CLCD of the initial ds DNA to the CD spectra of this CLCD treated with GdCl3 solution. One can see that the amplitude of an intense negative band the CD spectrum characteristic of the initial ds DNA CLCD (curve 1) is changed and its maximum is displaced to the ―red‖ region of the spectrum as a result of treatment of this CLCD with GdCl3 (curves 2-5).

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Figure 30. The CD spectra of the ds DNA CLCD in the absence (curve 1) and presence (curves 2-5) of GdCl3 in solution. 1 – initial CLCD of ds DNA; 2 – 0.025 mM; 3 – 0.5 mM; 4 – 1 mM; 5 – 2.92 mM GdCl3. CDNA = 10 μg/ml; CNaCl = 0.3 M; CPEG = 170 mg/ml;

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A = (ΑL - ΑR) х 1х10-5 opt.un.

The gadolinium-concentration dependence of the amplitude (ΔA270) of an intense negative band in the CD spectrum of the DNA CLCD particles [128] is shown in Figure 31. One can see that the amplitude is only slightly changed at low concentrations of GdCl3 (rtotal ~ 0.5). The intriguing questions are why the amplitude of the intense band in the CD spectra of ds DNA CLCD decreases, but insignificantly, at low concentrations (r 20) of gadolinium. In analyzing the observed effect, it is necessary to consider the following: as it was shown [131, 134-136], when the rare earth cations are bound to linear ds DNA molecules, the noticeable alterations in the CD spectra of these molecules are observed at rtotal ≤ 0.5. This demonstrates the loss of the regular character of the secondary structure typical of linear ds DNA (Figure 31). Such alterations can be associated with the local conformational transition, for instance, of B→Z type. The violation of the regular character of the secondary structure of linear ds DNA, which is accompanied by a change in the shape of their CD spectra, is specific for the complex formation with several metals [135,136].

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Figure 31. The dependence of the amplitude of the abnormal negative band in the CD spectra of the CLCD formed by (DNA-Gd3+) complexes upon rtotal value. CDNA = 10 mkg/ml; CNaCl = 0.3 M; CPEG = 170 mg/ml. The region of low rtotal values is cross-hatched. Insert: Comparison of the CD and X-ray data: (1) the dependence of the relative (Amax - A/Amax) amplitude of the band (nm) in the CD spectra of linear ds DNA, complexed with Gd3+ on rtotalvalue;

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(2) the dependence of the relative amplitude of the Bragg peak of the CLCD formed by (DNA–Gd3+) complexes on rtotal value. rtotal – is the ratio of total GdCl3 molar concentration to the molar concentration of the DNA nitrogen bases.

One can expect that if the fragments of the neighboring molecules of the complexes of linear ds DNA are treated with gadolinium, or even if these molecules packed in particles of the CLCD acquire a heterogeneous secondary structure, and translational order of these molecules, containing fragments with altered structures is broken, the small-angle reflection on X-ray patterns of the LC phases, formed by these particles after their low-speed sedimentation, will disappear. The X-ray analysis has indeed shown, that the treatment of the ds DNA CLCD by gadolinium destroys the typical parallel position of ds DNA molecules and leads to a formation of disordered regions even within low gadolinium concentration range [133]. To confirm this, model simulations of different types of structural organizations of the ds DNA CLCD treated with gadolinium were performed. Two possible structural changes affecting the scattering patterns were considered: a disorder of parallel packing, and a bend of the ds DNA rods in the site(s) of gadolinium binding to ds DNA molecules. Theoretical calculations allow one to conclude: i) the increase in the degree of disorder in the packing the ds DNA molecules leads to a decrease in the amplitude on the corresponding model X-ray scattering curves. The disordering results in a decrease of the Bragg peak on the scattering

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curve and even to disappearance of its maximum; ii) the bend of the ds DNA molecules as a result of gadolinium binding is accompanied by the same effect: increasing the number of bends causes a decrease in the amplitude of the Bragg peak and the complete disappearance of the maximum. Comparison of curves 1 and 2, presented in the insert to Figure 31, reflect both the diminishing in the amplitude of low-intensity band in the CD spectra of linear ds DNA (curve 1) and the decrease in the amplitude of X-ray scattering peak (curve 2). This unequivocally means that low concentration of gadolinium induce the alteration of the secondary structure of linear ds DNA molecules as well as of these molecules fixed in the content of particles of CLCD. The curves 1 and 2 confirm that the binding of low concentrations of gadolinium to ds DNA molecules packed in particles of the CLCD leads to a local alteration in homogeneity of the secondary structure of the DNA. The ―modified‖ ds DNA molecules are separated into alternating fragments differing in conformations (e.g., B–Z–Z–B–B– Z–B–Z– etc. for DNA). The junctions between B-DNA and Z-DNA fragments also contain extruded bases [137], providing the sites with modified local properties. In the case of creating these ―modified‖ DNA molecules, the altered CD spectra of the ds DNA CLCD, treated with gadolinium, are observed (Figure 30, curve 2). Figure 31 shows that at high gadolinium concentration in solution the CD picture is changed dramatically. A relative sharp increase in the amplitude of the intense negative band in the CD spectrum of the CLCD of the (DNA-Gd) complexes occurs at a large excess of gadolinium cations in the solution (rt > 20) and its maximum is shifted by 10 nm toward long wavelengths. Under saturating gadolinium concentrations the negative charges of the phosphate groups of DNA are neutralized by positively charged gadolinium cations. According to data obtained by various physical methods [125,131], in the presence of large excess of gadolinium cations, these cations can displace the sodium ions, initially bounded to the phosphate groups of the ds DNA. (It is worth noting, that when Gd3+ ions are bound to polyphosphates, poorly soluble Gd-polyphosphates are formed (solubility constant is equal to about 10–12 M) [124, 138]. Since ds DNA molecules have a ―polyphosphate‖ origin, these molecules in the presence of saturating gadolinium concentrations become poorly soluble as well as in PEG-containing water-salt solutions. One can stress that the observed increase in the amplitude of the negative band in the CD spectrum of the ds DNA CLCD treated by gadolinium (Figure 31) is similar to change in the CD spectra of this CLCD upon ―cross-linking‖ of neighboring DNA molecules due to the formation of nanobridges between them. This permits one to suppose that nonuniform distribution of fragments with heterogeneous secondary structure results in irregular attraction between these fragments in the content of the neighboring DNA molecules. The physical origin of this attraction mediated by a strong correlation interaction is related to either electrostatic or entropic contributions. Besides, such interaction is probably influenced by the interlocking gadolinium cations distributed over the ds DNA surface and termed as ―counterion cross-links‖. Here one should stress that the intermolecular interactions are quite different for the DNA molecules with different counterions and conformations [139]. Hence, under high gadolinium concentrations, the stable spatial structure of particles of CLCDs is obtained and the presence of PEG is not required to stabilize the structure of these particles. Moreover, gadolinium ions, neutralizing the charges of the phosphate groups of the DNA, create an excess positive surface charge on particles of the CLCD and aggregation of these particles becomes impossible. This means that, as a result of interaction of gadolinium

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ions with the ds DNA in the content of the CLCD particles, these particles lose their ability to coalescence. Therefore, particles of the CLCD of the ds DNA whose phosphate groups are neutralized by gadolinium ions become poorly soluble and can exist in the absence of a high osmotic pressure in the PEG-containing solution (induced by high PEG concentration). This means that the osmotic pressure of the water-salt PEG-containing solution is not necessary for supporting the cholesteric mode packing molecules of the ds (DNA-gadolinium) complexes in particles of the CLCD. If poorly soluble CLCD particles, consisting of the (DNAgadolinium) complexes, are formed then the immobilization of these particles on the surface of the nuclear membrane filter becomes possible and the size and shape of these particles can be investigated. (It is necessary to stress again, that the particles of the CLCD of the initial ds DNA do not exist in the absence of high osmotic pressure of the solvent. Therefore, their fixation on a nuclear membrane filter and visualization is impossible under these conditions).

Figure 32. The AFM images of the particles of CLCD formed by (DNA - Gd+3) complexes immobilized onto the surface of the nuclear membrane filter (PETP). CDNA= 1.07 μg/ml; CNaCl = 0.03 M; CPEG =17 mg/ml; CGdCl3 =0.23 mM. (The dark spots are ―pores‖ in the nuclear membrane filter. Two sites on the PETP filter are shown.).

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Figure 32 displays the AFM images of the filter-immobilized (DNA-gadolinium) CLCD particles. After immobilization the membrane filter was washed with water to prevent NaCl crystallization and/or PEG film formation. One can see that the particles exist as independent objects. Figure 33 demonstrates the size distribution of these particles as well as the pores in the filter. The mean size of particles is 450-500 nm, i.e. the mean diameter of the ds DNA CLCD particles after treatment with gadolinium is comparable with the mean diameter of initial ds DNA CLCD particles. The latter fact is a very important one, because it means that the mean DNA packing density is not changed by gadolinium interaction, i.e., the chromophore density in such dispersions remains high enough to sustain their abnormal optical activity.

Figure 33. The size distribution of the ds DNA CLCD particles, treated by GdCl3 (1), and the pores (2) in the membrane filter. Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

CDNA= 1.07 μg/ml; CNaCl = 0.03 M; CPEG =17 mg/ml; CGdCl3 = 0.23 mM.

The results of low-temperature magnetometric studies showed [131] that at rtotal > 20, one gadolinium cation is bounded approximately to one DNA phosphate group, i.e., each phosphate group of DNA molecules, carrying one ―effective‖ negative charge, is neutralized by the Gd3+ ion, that carries three positive charges. Hence, at a high extent of gadolinium binding to the DNA, not only the negative charges of phosphate groups are neutralized by the Gd cations, but also the altered surface charge distribution makes an additional contribution to the chiral interaction between adjacent (DNA-gadolinium) complexes in the particles [30,140]. The gadolinium cations, when present at high concentration, are capable of overcompensating the DNA charges, and the DNA charge inversion can take place, inducing a change in the spatial structure of the CLCD. The synergic effect of the local alterations of the secondary structure and the charge inversion of the DNA molecule changes [30,113, 140142] the mode of spatial packing of these molecules in the particles of CLCD. This can alter the helical twisting of the cholesteric structure, i.e., facilitate the change of the cholesteric pitch, P. Application of the theory [64] that describes the abnormal optical properties of the particles of the CLCD formed by ds DNA molecules reveals a few interesting facts. It is known that the coefficients of transmittance (L,R) of waves with left (L)-circular and right

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(R)-circular polarization (i.e. the abnormal optical activity) are described by the equation (3) PART 2). This expression was used for description of the optical properties of the ds DNA CLCD particles treated by GdCl3, in particular, for evaluation of the correlation between an intense negative band in the CD spectra of the ds DNA CLCD and P value of the cholesteric structure formed by DNA molecules in the content of these CLCD. Assuming that in the case of the ds DNA CLCD the diameter of particles, D, is about 350-550 nm, the initial P value is about 3 μm and the initial ΔA value is about 400x10-5 optical units, the theoretical curve for the (ΔA-P) relationship was calculated at the beginning (Figure 34, curves 1 and 3). These curves clearly show that the decrease in P value is accompanied by the increase in ΔA value, i.e. the smaller the pitch of a cholesteric structure, i.e., the greater the twist, the more intense is the amplitude of an abnormal band in the CD spectrum. The experimental meanings of ΔA, i.e. the observed amplitudes of the abnormal band in the CD spectra of the CLCD formed by ds DNA and treated with GdCl3, correspond fairly well to the theoretical curve (Figure 34, curve 2). Comparison of the experimental results and the theoretical calculation confirms the supposition about correlation between the decrease in P value and the increase of an abnormal optical activity of the CLCD particles treated by the gadolinium salt. Then, taking into account the known concentration of gadolinium, a correlation between the P values and gadolinium concentration in used solutions was estimated (Figure 35).

Figure 34. The theoretical dependences of the maximal amplitude, A, of the band in the CD spectra of the DNA CLCD, treated with GdCl3, on the pitch, P, value. The black points correspond to the experimentally measured A values. Curve 1 - D - 350 nm; curve 2 – D - 450 nm; curve 3 - D - 550 nm; λ = 270 nm; CDNA =10 μg/ml; CNaCl = 0.3 M; CPEG = 170 mg/ml; ∆Α ( 270 nm) = (ΑL - ΑR) х 1х10-5 opt.un.

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Figure 35. The theoretical dependences of the P value of the cholesteric structures for the ds DNA CLCD particles upon the GdCl3 concentration. CDNA =10 μg/ml; CNaCl = 0.3 M; CPEG = 170 mg/ml.;

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Curve 1- D - 350 nm; curve 2 - D - 450 nm; curve 3 - D - 550nm.

Figure 34 and Figure 35 demonstrate that the ―P-effect‖, i.e. an amplification of the intense band in the CD spectra as a result of the alteration of the helical twist of the cholesteric structure of the ds DNA CLCD, indeed exists in the system under study. Hence, the suggestion about the change in the angle of twist between quasinematic layers of the ds DNA molecules containing irregular fragments with ―modified‖ secondary structure and fixed in the structure of CLCD is supported by results of theoretical calculations. One must remember that is well known that molecular motions of classical lowmolecular compounds are free, and hence, the corresponding X-ray scattering peaks, for liquid crystals formed by these molecules, are almost absent. The theories describing an appearance of abnormal optical activity of low-molecular cholesterics [61, 106, 143] assume that the sufficient conditions for abnormal optical activity are the ―orientation‖ order of chromophores of molecules in quasinematic layers of molecules and their helical twisting. The theory usually does not connect the mode of ―local‖, crystallographic order of neighboring low molecular compounds and the ―long-range‖, orientation order of their chromophores in the liquid-crystalline structure [144]. It is important to emphasize that the problem of correlation between the local heterogeneous conformation of the ds DNA secondary structure and the character of dense packing these molecules in liquid-crystalline phases remains a subject of active theoretical investigations [10, 30, 140, 145,146]. The observed change in the twisting of the cholesteric structure can occur in the form of a phase transition. It is worth noting that the possibility of the phase transition between two

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cholesteric forms was recently analyzed by V. Golo [94]. However, such a transition in our case can be quite diffuse (Figure 31) due to the smallness of the system elements. The results presented allow us to draw a hypothetical scheme of transition from a ―liquid‖ to a ―rigid‖ structure of the ds DNA CLCDs induced by gadolinium cations (Figure 36). One can see (right structure), that here the spatial ordering of neighboring DNA molecules is practically absent; despite ordered location of nitrogen bases in quasinematic layers. However, under these conditions, strong interaction between the fragments of neighboring DNA molecules can result not only in stabilization, but also in decrease of solubility of the whole structure. The ―rigid‖ structure appears and it can exist in the absence of an osmotic pressure from the solvent. Besides, under these conditions the twist angle between neighboring quasinematic layers is increased (the P value is decreased, right structure). Rigid structures can be named as nanoconstructions (NaCs) based on the (DNA-gadolinium) complexes.

Figure 36. The scheme of transition from ―liquid‖ to ―rigid‖ state of the particle of the CLCD induced by high Gd3+ concentration. The spatial ordering the neighboring ds DNA molecules in qusinematic layers is practically absent (right structure). Besides, under these conditions the twist angle between the neighboring DNA quasinematic layers is increased (the P-value is decreased, right structure). However, under these conditions, strong interaction between the fragments of neighboring DNA molecules results not only in stabilization, but in a decrease of solubility of whole structure. The ―rigid‖ structure is appeared and it can exist in absence of osmotic pressure of the solvent.

Thus, the combination of two different effects determines the unique properties of rigid CLCD of (DNA-gadolinium) structures. The first effect is an appearance of local heterogeneities in the secondary structure of the ds DNA molecules interacting with

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gadolinium. This process is accompanied by a small decrease in the amplitude of the intense band in the CD spectra, by the ―nematization‖ of the secondary structure of ds DNA molecules in quasinematic layers, and by the disappearance of the small-angle X-ray scattering of CLCD formed by (DNA-gadolinium) complexes. The second effect, operating at high concentrations of gadolinium cations, is the twisting of the quasinematic layers containing the ds DNA nitrogen bases, which is accompanied by amplification of the negative band in the CD spectrum of NaCs formed by (DNA-gadolinium) complexes. Hence, the CD spectra ds DNA ―liquid‖ CLCDs as well as ds DNA ―rigid‖ nanoconstructions (both these structures can be named as ―biomaterials‖ independent of the way of their formation) can be used for resolving various tasks in science and technology.

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CONCLUSION The results presented in this Chapter illustrate an existence of two, principally different, problems related to description of the ds DNA CLCD and their CD spectra. First, it is the formation of the CLCDs as a result of close approaching anisotropic, ds DNA molecules or their complexes with various compounds. In our case, the mode of interaction between neighboring DNA molecules determines the creation of, as a minimum, both left- and right-handed twisted helicoidal structures, despite the existence of fixed, righthanded helical structure of initial DNA molecules (B-form). Hence, estimation of the correlation between the mode of interactions of ds DNA molecules in water-salt or water-salt polymer-containing solutions responsible for chirality on the ―microscopic‖ scale and the types of structures of ―macroscopic‖ liquid-crystalline phases is still a challenge in the physics of LCs. Secondly, it is an appearance of abnormal (intense) band in the CD spectra in the ds DNA CLCD CD spectra. Here, the mode of orientation of the DNA nitrogen bases (or compounds incorporated between them) in respect to the director of the quasinematic layer determines both an appearance and a sign of an intense band in the CD spectra. In our case the peculiarities of the ds DNA helical structure are not correlated directly with these optical effects. The theory for the optical properties of the ds DNA cholesteric phase is a serious theoretical problem due to the presence of the various chiral elements, and the interaction between them as well as the inhomogeneous character of the distribution of these elements in the ds DNA, and hence, in the quasinematic layer structure. These two problems are entangled in the case of the ds DNA liquid-crystalline dispersions. Many interesting questions in this area are still not answered. Despite this, the CD spectra permit one to control the formation of the CLCD particles from rigid, linear, ds molecules, and to detect very fine changes in the properties of both the ds DNA and the dispersion particles induced by action of various factors, including ―liquid-rigid‖ transitions. This means that the CD spectra of the ds DNA CLCDs can be used to solve medical or biotechnological tasks.

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ACKNOWLEDGMENT The authors want to express their deep gratitude to the private company ―New energetical technologies‖ (Moscow) both for the interest to investigations in the area of the ds DNA liquid crystals and partial financial support.

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Chapter 2

VIBRATIONAL CIRCULAR DICHROISM STUDIES OF BIOLOGICAL MACROMOLECULES AND THEIR COMPLEXES Alexander M. Polyanichko*1, Valery V. Andrushchenko‡2, Petr Bouř≠2 and Helmut Wieser£3 1

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Faculty of Physics, Saint-Petersburg State University, and Institute of Cytology, Russian Academy of Sciences, Saint-Petersburg, Russian Federation 2 Institute of Organic Chemistry and Biochemistry, Academy of Sciences, Praha, Czech Republic 3 Department of Chemistry, University of Calgary, Calgary, Canada

Dedicated to Dr. Maria Krasteva ABSTRACT Vibrational circular dichroism (VCD) being a relatively new spectroscopic technique is quite promising for studying of biological molecules and their complexes. It combines conformational sensitivity of electronic circular dichroism (CD, or ECD) with extensive local mode information provided by the vibrational spectroscopy. Another advantage of VCD over ECD is its applicability to complexes of biological macromolecules, which would cause considerable light scattering in the UV region. This makes VCD a particularly useful tool for the investigation and characterization of various molecular structures. Here, we overview the theoretical background, discuss some practical aspects * Faculty of Physics, Saint-Petersburg State University, 1 Ulyanovskaya Str., Saint-Petersburg, 198504, Russian Federation; e-mail: [email protected] ‡ Institute of Organic Chemistry and Biochemistry, Academy of Sciences, Flemingovo nám. 2, 16610, Praha 6, Czech Republic; e-mail: [email protected] ≠ Institute of Organic Chemistry and Biochemistry, Academy of Sciences, Flemingovo nám. 2, 16610, Praha 6, Czech Republic; e-mail: Bouř@uochb.cas.cz £ Department of Chemistry, University of Calgary, 2500 University Drive, Calgary, T2N 1N4, AB, Canada; e-mail: [email protected]

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Alexander M. Polyanichko, Valery V. Andrushchenko, Petr Bouř et al. of VCD application to biological molecules, and list major spectral features encountered in the most common types of DNA and protein secondary structures. We also describe VCD applications to structural and conformational analysis of biological macromolecules and their complexes, including those with metal ions and drugs. In the end of the chapter, we outline some of the current state of the art methodology for computations of VCD spectra of large biopolymers.

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1. INTRODUCTION Modern structural biology is one of the most rapidly growing branches of science. The major question here is how the structure of biological molecules corresponds to the functions they perform in living cells. Many of such molecules are large polymers, or macromolecules, which can be conventionally characterized by three different levels of structural organization, namely primary, secondary and tertiary structures. Currently, even more complex organization is studied, comprising many macromolecules, which reflects the fact that the functioning of biological molecules very often depends on proper formation of threedimensional complexes with each other, i. e. on the quaternary structure. The precise structural organization of such complexes becomes the key element, which determines not only the efficiency but even the possibility of a particular biochemical process. Clearly, understanding of the mechanisms of functioning of a biological system is not possible without understanding its structural organization and structural transformations on the molecular scale. In this respect, no matter whether you call it biophysics, biochemistry or molecular biology, you require some structural data to start with. Recent developments in such structural techniques as X-ray crystallography and especially NMR spectroscopy provided researchers with a tremendous amount of structural data, which finally brought structural biology to a qualitatively new level. However, resolving a structure of a reasonably large biological molecule, let alone complexes of several of them, still remains a tricky and not quite a routine task. Besides, X-ray and NMR normally are not applicable if one wants to follow kinetics of structural and conformational changes, which limits the use of these techniques only for the investigation of final or stable intermediate stages of the reactions. To overcome these limitations a number of spectroscopic approaches have been used. Optical methods are convenient and quite popular tools for investigations of structural properties of biological molecules. Among all of them a special place is given to chiroptical techniques, which are sensitive to a three-dimensional organization of molecules. A media containing chiral molecules will have different indices of refraction, and hence the velocity, for left and right circularly polarized light. As a result, one can observe a rotation of the plane of polarization of linearly polarized light transmitted through the media, which is easy to understand bearing in mind that light with linear polarization can be described as a superposition of left and right circularly polarized light. In the region where chiral molecules absorb light the absorption of its left and right polarized components will be different, and one says that we observe circular dichroism (CD). As a general rule, in the vicinity of an optically active chromophore both circular birefringence and circular dichroism occur, resulting in transformation of linear polarization of incident light to elliptic polarization of outgoing light.

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The technique measuring the difference between absorbance of left and right circularly polarized light ∆A = AL – AR as a function of wavelength, λ, is also called the circular dichroism, or CD spectroscopy. Alternatively, CD can be described as difference between molar extinction coefficients for left εL and right εR circularly polarized light ∆ε = εL – εR. The relation between ε and A is given by the Beer‘s law: A = ε∙c∙l, where c is molar concentration of the sample and l is the optical path length in centimeters. Very often, especially for proteins, CD spectra are represented in terms of ellipticity θ, or molar ellipticity [θ], which can be estimated as [θ] ≈ 3300∙∆ε (Moscowitz, 1962). In the case of polymer molecules such as nucleic acids and proteins, CD is very sensitive to the mutual orientation of the monomers, and hence to the overall structure. For example, nitrogen bases of nucleic acids are not chiral. However, a strong CD signal specific for different types of secondary structures (Figure 1) of both DNA and RNA can be observed in the UV region between 180 and 300 nm, originating mostly from dipole-dipole through-space interactions in the bases (Tinoco, 1963; Cantor and Schimmel, 1980). As a result, looking, at the CD spectrum of nucleic acids one can readily determine whether it is in A-, B-, or Z-form. Because of that, CD spectroscopy, and electronic CD (ECD) in particular, is one of the most used spectroscopic techniques for investigations of biological macromolecules, especially proteins and nucleic acids.

Figure 1. Typical ECD spectra of B-DNA (black line), A-DNA in 80% ethanol (blue line), and A-DNA in 80% TFE (trifluoroethanol, red line).

Proteins are another example of a native polymer, which consists of different chiral monomers. The only exception among the amino acids is glycine, which is not chiral. One of

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the most important characteristics of protein molecules is their three-dimensional organization – secondary and tertiary structures (Schulz and Schirmer, 1996). Some of them, like α-helix and β-sheet, demonstrate high levels of structural organization, while others like random coil are less ordered. An asymmetrical secondary structure also contributes to the optical activity of a polymer resulting in very characteristic spectral patterns for each type of a secondary structure (Figure 2). By analyzing CD spectra of proteins one can judge the percentage of αhelix and β-sheet conformations in their structure. This structural analysis is very quick and constitutes a considerable advantage of ECD against other methods.

Figure 2. Model ECD spectra of the polypeptides with the shapes typical for different types of secondary structures: α-helix (curve 1), β-sheet (curve 2), and random coil (curve 3).

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Optically active transitions in proteins can arise both from peptide bonds and side chain chromophores. Traditionally called n* and * electronic transitions in peptide bonds result in several spectral features, which manifest themselves in the UV region between 140 and 225 nm. These transitions are different for the random coil, α-helix and β-sheet structures. Experimentally, the spectral features below 180 nm are very difficult to detect, and a vacuum technique must be used. To lower the detection limit, a new promising technique based on utilization of synchrotron radiation has been developed recently (Miles and Wallace, 2006). Synchrotron Radiation Circular Dichroism (SRCD) allows studying optical activity in an extended spectral range, typically starting from 150 nm with a higher signal-to-noise ratio. Nevertheless, the conventional CD spectrometers equipped with UV lamp still remain the most widespread and useful routine spectroscopic tools for structural analysis, providing researchers with initial structural information about proteins, DNA, and variety of their complexes. ECD has another serious limiting factor even for qualitative analysis, which is the light scattering. The shape of CD spectra can be attributed to a particular structure of molecules only if no light scattering occurs in the solutions. Otherwise, the observed spectral changes do not bear any structural information (Dorman and Maestre, 1973; Maestre and Reich, 1980; Tinoco et al., 1980b; Bustamante et al., 1983; Phillips et al., 1986; Tinoco et al., 1987). As a result, one can study only individual molecules or relatively small complexes. To reduce the scattering one can either reduce the size of the particles in the solution, or increase the wavelength of the light. The latter implies a shift from the UV to a different spectral region, such as visible or infrared. Infrared (IR) spectra arise from vibrational transitions of chemical bonds, and spectroscopy in IR region is often called vibrational. The vibrational spectra of biomolecules can be observed using absorption of IR light, reflection, emission (Arrondo et al., 1993; Goormaghtigh et al., 1994; Haris and Chapman, 1994; Siebert, 1995), Raman scattering (Spiro and Gaber, 1977; Callender and Deng, 1994; Robert, 1996; Carey, 1998, 1999; Deng and Callender, 1999), Raman optical activity (ROA) (Barron et al., 1973; Barron et al., 1996b; Blanch et al., 2003; Barron et al., 2004; Zhu et al., 2005; Barron et al., 2006; Barron et al., 2007), infrared or vibrational circular dichroism spectroscopy (VCD). The vibrational circular dichroism is a relatively new approach for investigating the structure of biological macromolecules (Stephens, 1985; Keiderling, 1990; Nafie, 1997; Polavarapu, 1998). Being a chiroptical technique like its counterpart in the UV region, VCD is also very sensitive to structural changes in the macromolecules, but in addition it is considerably more informative for structural analysis compared to ECD. Arising from various vibrations of the chemical groups, the VCD spectrum may contain numerous reasonably well separated spectral bands, providing more specific and extensive information about the molecular structure. The frequency of the vibration and the probability of IR absorption depend on the strength and polarity of the vibrating bonds, and the spectra are thus influenced by intra- and intermolecular effects. For example, unlike ECD, VCD spectra reveal not only DNA conformations, i.e., A-, B-, or Z-form, but also the mutual orientation of the different chemical groups within the DNA as well as their interaction with other molecules or ions. Vibrational spectroscopy is exceptionally sensitive to changes in bond strength (Deng and Callender, 1999; Barth and Zscherp, 2002). As bond energy and bond length are directly related, bond distortions in the course of a catalytic reaction can be monitored with astonishing accuracy. As an example, it was reported that pyruvate binding to lactate

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dehydrogenase, which leads to a fairly large downshift of 35 cm-1 of the pyruvate C=O IR band, corresponds to a change in bond length of only 0.02 Ǻ (Callender and Deng, 1994)! Thus, a wealth of information about structure and environment of nucleic acid bases and sugar-phosphate backbone, amino acid side chains, bound ligands or cofactors, and the protein backbone can be deduced from the spectral parameters, namely band position, bandwidth, and the absorption coefficient. This makes vibrational spectroscopy a valuable tool for investigations of DNA (Keiderling and Pančoška, 1993; Keiderling, 1996; Andrushchenko et al., 2003a; Urbanová, 2009) and protein structure (reviewed in (Haris and Chapman, 1994; Jackson and Mantsch, 1995; Siebert, 1995; Arrondo and Goni, 1999; Barth and Zscherp, 2002)), of the molecular mechanism of protein reactions (reviewed in (Rothschild, 1992; Gerwert, 1993; Mäntele, 1993; Slayton and Anfinrud, 1997; Fahmy et al., 2000; Vogel and Siebert, 2000)), and of protein folding (reviewed in (Callender et al., 1998; Dyer et al., 1998; Arrondo and Goni, 1999)). Thus, the key advantage of vibrational spectroscopy over UV measurements is the larger amount of information the former can provide. Recent advances in the interpretation of VCD made it not only a reliable tool for analyzing chiral compounds and biomolecular conformations but also for determination of absolute configurations in the solution phase (Stephens and Devlin, 2000; Stephens et al., 2001; Devlin et al., 2002a; Devlin et al., 2002b; Stephens et al., 2005; Urbanová et al., 2005; Stephens et al., 2007; Stephens et al., 2008). Based on comparison of experimental VCD spectra with those theoretically calculated it was possible to determine absolute configurations of bioorganic molecules, complicated carbohydrates, and even larger helical molecules. Some ‗bioinspired‘ applications of VCD were recently reviewed elsewhere (Urbanová, 2009). In this chapter we discuss some practical aspects of VCD application to the studies of biological molecules, and the major spectral features of the most common types of DNA and proteins secondary structures. We also describe VCD applications to structural and conformational analysis of biological macromolecules and their complexes, including those with metal ions and drugs. In the end of the chapter we outlined the current state of the art methodology for computations of VCD spectra of large biopolymers.

2. ORIGIN OF VIBRATIONAL SPECTRA Infrared spectra arise from changes in energy due to the various vibrational or rotational transitions in molecules. The wavelengths of radiation with corresponding energy range from 700 nm to 1 mm, or using a wavenumber scale, which is traditionally preferred in IR spectroscopy, it ranges from ~14 000 cm-1 to 10 cm-1 respectively. The most used spectral region lies in between 4 000 cm-1 and 200 cm-1 and is called ‗middle IR‘ or ‗mid-IR‘. The frequencies beyond this region, i.e. above 4 000 cm-1 and below 200 cm-1 are called ‗near IR‘ and ‗far IR‘, respectively. An absorbed IR radiation causes a change in dipole moment of a molecule. Visa versa, in order to absorb IR radiation, a molecule has to change its dipole moment during a vibrational motion, at least in the dipole approximation. Hence, the IR radiation absorbed by a molecule is converted into energy of molecular vibration or rotation, e.g. resulting in increasing amplitude of the corresponding motion. IR spectra originate from various vibrational

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transitions in a molecule. A simple mechanical consideration gives for N-atomic molecule 3N degrees of freedom. Among them, 3N-6 degrees of freedom correspond to fundamental vibrations, which occur in a nonlinear molecule (3N-5 for a linear one), the rest are rotations and translations not visible in IR.

Figure 3. Some types of normal vibrations in a non-linear molecule. The arrows represent atom displacements in the plane of the plot, while ―+‖ and ―-― symbols represent displacements out of the plane of the plot: νAS – asymmetric stretching; νS – symmetric stretching; δS – symmetric in-plane bending (scissoring);δAS – asymmetric in-plane bending (rocking, ρ); ω – symmetric out-of-plane bending (wagging); τ – asymmetric out-of-plane bending (twisting).

Basically, there are two well-distinguished types of vibrations in a molecule, stretching and bending. A stretching vibration causes change in the length of a chemical bond, while bending vibrations are characterized by a change in the angle between two bonds. As a Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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general rule, bending vibrations occur at lower frequencies than corresponding stretching vibrations. The possible vibrations in a 3-atomic molecule like water etc. are shown in Figure 3. Vibrations of the neighboring bonds can interact with each other, resulting in coupling of vibrations. A simple mechanical model of a harmonic oscillator gives the relation between vibration frequencies and the bond strength and atomic masses. Thus, each functional group in a complex molecule will also have more or less characteristic vibrational frequencies, which contribute to the IR spectrum. The group frequency analysis makes vibrational spectroscopy useful and popular tool for structural studies. Recent developments in theoretical calculations turned even relatively new vibrational spectroscopy methods, such as VCD, into reliable and powerful instruments for spectroscopic analysis. Instrumental and theoretical advances in VCD spectroscopy enable determining the absolute configuration and conformations of small chiral molecules in solution. Continued growth of computing power and the rapid development in theory ensures that VCD analysis will become an essential technique for various studies, from supramolecular chemistry to structural biology.

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3. THEORETICAL BACKGROUND OF VCD SPECTROSCOPY The main advantage of chiral spectroscopic techniques over their non-chiral counterparts is the ability to distinguish enantiomers. Chiral molecules are not superimposable on their mirror images. They exhibit a different interaction with left and right circularly polarized radiation, i.e. they are ―optically active‖. The optical activity originates in a three-dimensional arrangement of molecular constituents, hence the spectroscopic results directly correlate to the structure. Enantiomer (mirror-image pair) molecules, for example, display circular dichroism spectra of equal intensity but opposite sign. Typical VCD spectra observed for (+)--pinene and its opposite enantiomer (-)--pinene are shown in Figure 10 (see Experimental techniques section below). As seen from the Figure, a VCD spectrum represents a series of negative and positive bands, arising from the parental absorption bands. VCD spectra of opposite enantiomers, as expected, appear as mirror images; the spectral features have opposite signs but equal intensity. The VCD is a difference in absorbance of left versus right circularly polarized infrared light (Figure 4). Because the differential signal A is approximately three to five orders of magnitude lower than the absorbance itself, either AL or AR, it is experimentally challenging to obtain good VCD spectra with high signal-to-noise ratio. This difficulty obscured routine applications of the method until recent years, when a reasonable progress in the instrumentation has been made. At the same time, theoretical basis for VCD has been developed for more than 40 years and has been extensively discussed in the literature (Deutsche and Moscowit, 1968, 1970; Holzwarth and Chabay, 1972; Stephens, 1985; Nafie and Freedman, 1987; Rauk and Freedman, 1994). Here, we will only briefly outline the main theoretical aspects of VCD spectroscopy.

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Figure 4. The circular dichroism phenomenon.

Experimentally the difference in absorption (A) of an optically active molecule is measured as a function of the wavenumber ( ) :

A( )  AL ( )  AR ( )

(1)

where AL and AR are the absorbances of the left and right circularly polarized infrared radiation, respectively. The intensity of a VCD band is proportional to the rotational strength, R: 

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 0

A( )



d  R

(2)

We can also express this with the molar extinction coefficient  as

R  2.29 *10 39



band

 ( )



d

(3)

Rotational strength is defined as the imaginary part of the scalar product of the electric   transition dipole moment,  , and the magnetic transition dipole moment, m :

  R  Im  m

(4)

Hence, positive VCD features appear when the two transition moments form angles smaller than 900, while negative VCD features will arise for angles greater than 900, as illustrated in Figure 5. It is clear that although the absorption intensity may not be zero  (  0), the VCD intensity will still vanish in two cases: (1) when magnetic transition dipole

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

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moment is equal to zero ( m =0) or (2) when the two transition moments are orthogonal to    each other (   m ), since in both cases the scalar product will be zero. Obviously, for  =0 (zero absorption intensity) no VCD intensity will arise either. In other words, absorption band is not always accompanied by a VCD band, while appearance of VCD always indicates existence of an absorption band. In an achiral molecule, the average scalar product is equal to zero. Although such a molecule may have an absorption spectrum, it does not show any VCD features. Knowledge of the relative orientations of the electric and magnetic dipole transition moments is thus essential for predicting the sign of the VCD band for a particular vibration.





Figure 5. Appearance of a VCD signal as a scalar product of the electric (  ) and magnetic ( m ) dipole transition moments. Positive VCD features appears when the two transition moments form angles smaller than 90˚; negative VCD features arise for the angles greater than 90˚; no VCD signal appears when the two transition moments are orthogonal.

Nucleic acids are not chiral themselves, however they produce relatively intense VCD signal (Annamalai and Keiderling, 1987; Gulotta et al., 1989). It was shown that circular dichroism signal (both ECD and VCD) in nucleic acids originates not from chirality of their ribose and deoxyribose constituents (the bases are not chiral), but mostly from a throughspace dipolar coupling of transitions (electronic or vibrational, respectively) as described by

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the exciton theory (Tinoco, 1963). A typical VCD spectral feature in this case has the bisignate bandshape (consists of a positive and a negative components of equal magnitudes) and is called a ―couplet‖. Conventionally, a VCD couplet is called positive if the lower wavenumber component is positive (Polavarapu and Zhao, 2000). An example VCD spectrum of calf thymus DNA is shown in Figure 6. 7

A x 10

-5

VCD 0

-7 Nitrogen base vibrations

Sugar-phosphate vibrations

Absorption

A

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0.4

0.2

0.0 1700

1600

1100

1000

Wavenumber/cm

900

800

-1

Figure 6. VCD spectrum of calf thymus DNA (top panel), and the corresponding IR absorption spectrum (bottom panel). The strongest VCD couplets arise from the C=O and P=O stretching vibration of the nitrogen bases and phosphate groups, respectively.

Appearance of a couplet instead of a set of well separated positive and negative bands, usually observed in VCD spectra of small organic molecules (e.g., -pinene), is typical to the coupled oscillator (CO) mechanism (Tinoco, 1963; Holzwarth and Chabay, 1972; Rauk and Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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Freedman, 1994). According to the CO formalism, while a single oscillator would produce a single absorption band, two and more identical chirally oriented oscillators would couple and give rise to the in- and out-of-phase vibrations with corresponding VCD signals of equal intensity but opposite in sign (Tinoco, 1963; Nafie and Freedman, 1987; Zhong et al., 1990; Bouř and Keiderling, 1992; Andrushchenko and Bouř, 2008). For periodic systems, such as helical nucleic acids, the both vibrations occur at close wavenumbers. Absorptions arising from these vibrations are usually not resolved experimentally due to large natural bandwidth and appear as a single band giving rise to closely laying VCD signals of opposite sign, forming a couplet. The VCD phenomenon is characterized by locality, which means that the strongest through-space coupling takes place between the neighboring chromophores, and sharply decreases with the distance (Zhong et al., 1990; Birke and Diem, 1995; Andrushchenko et al., 2002b). The signal intensity also depends on the mutual orientation and the number of participating chromophores. Thus, total VCD signal is determined both at the local level by neighboring dipoles and by long-range exciton modes (Andrushchenko and Bouř, 2008). Conditions favorable for a strong dipole coupling occur when the chromophores are arranged in a regular order. This can be realized, for example, when nucleobases and parts of the sugar-phosphate backbone are stacked upon one another in a helical structure (Tinoco, 1963). Therefore, appearance of a strong VCD signal is usually associated with the helical structure of nucleic acids (Zhong et al., 1990; Birke and Diem, 1995). Although amino acids are chiral themselves, VCD signal of proteins or peptides also arises mostly due to a regular arrangement of the monomeric chromophores (mainly carbonyl bonds of amide groups). This results in specific VCD patterns originating from different peptide conformations, such as αhelix and β-sheet (Keiderling, 1996). High sensitivity of VCD signal to the changes in the coupling of vibrations leads to a high sensitivity of VCD spectra to changes in a geometrical structure of the macromolecules. Distortions of the ordered structure usually results in a decrease of VCD intensity (Yang and Keiderling, 1993; Birke and Diem, 1995; Diem, 1995; Keiderling, 1996; Andrushchenko et al., 2003c; Andrushchenko and Bouř, 2008). For example, loss of stacking among the nucleobases and among sugar-phosphate residues of the backbone in DNA completely obliterates VCD signal (Yang and Keiderling, 1993; Andrushchenko et al., 2003c).

4. VCD INSTRUMENTATION As it was mentioned above, the difference in absorbance, ∆A = AL – AR, which determines the VCD, is normally by 3-5 orders of magnitude weaker than the corresponding absorbance. Such weak signals can be measured only with spectrometers developed specifically for this purpose or, in some cases, with specially designed attachments to regular IR spectrometers. Studying biological samples, such as proteins or nucleic acids, is especially difficult, and high concentrations are needed to increase the VCD signal of a sample considerably. Recent developments in VCD instrumentation have remarkably extended the application area. The majority of the VCD instruments currently in use are based on the Fourier transform (FT) IR spectrometer. However, dispersive instruments can also be used. They are usually slower and for a limited range of wavenumbers only, but provide signal-to-

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noise ratio comparable to that of FT instruments. The detailed comparison of different types of the VCD instruments has been published elsewhere (Nafie and Vidrine, 1982; Polavarapu, 1985; Nafie, 1988; Keiderling, 1990, 1996; Nafie, 1997; Keiderling, 2001; Nafie et al., 2002; Lakhani et al., 2009). Below we describe the instrumentation and the experimental approach we routinely use for DNA and protein applications in our laboratory at the University of Calgary. The usual way to measure a CD signal is to alternate left- and right-circularly polarized light passing through the sample with subsequent phase-sensitive detection and lock-in amplification of the signal. To produce left- and right-circularly polarized light with desired frequency photo-elastic modulators (PEM) are used. They usually provide sine-wave modulation and are used in conjunction with a dispersive monochromator (Holzwarth and Chabay, 1972; Holzwarth et al., 1974; Nafie et al., 1975; Nafie and Diem, 1979b; Diem et al., 1988; Xie and Diem, 1996) or FT interferometer (Nafie and Diem, 1979a; Nafie et al., 1979; Maloň and Keiderling, 1988; Keiderling, 1990; Tsankov et al., 1995). In our laboratory we use the FT-VCD instrument (Figure 7) first described by D. Tsankov et al. (Tsankov et al., 1995). This instrument is based on the Bomem MB100 interferometer with external setup of the additional VCD optics and electronics. A parallel beam exits the interferometer through a side-port window, passes through a linear polarizer, and then a ZnSe PEM. The PEM modulates the polarization of a beam at 37.5 kHz. The linear polarizer is placed immediately before the PEM and is set at 45 with respect to the modular axis of the PEM crystal to allow equal intensities of linearly polarized light to reach the orthogonal axes of the crystal. Thus the radiation applied to a sample is doubly modulated, since it is first modulated by the interferometer, and then by the PEM unit.

Figure 7. Schematic representation of the VCD instrument setup (Tsankov et al., 1995). PEM is the Photo-Elastic Modulator, ADC is the Analog-to-Digital Converter.

After the PEM, radiation passes through the sample, and the transmitted light is focused with a lens onto an external detector. The detector we use is a type A MCT (HgCdTe) cooled Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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with liquid nitrogen. It was specifically chosen for its low noise. An optical filter can be placed either immediately before the linear polarizer, or immediately before the detector, to prevent detector saturation. The optical filter is a long wave pass filter, which only permits radiation below 1800 cm-1 to reach the detector. The spectral range is further limited by the ZnSe optics, which have low transmission below 800 cm-1, and the MCT detector, which measures only to 750 cm-1. The signal measured by the detector is first amplified by a pre-amplifier, and then follows one of two paths. In the first one the electronic signal is fed directly to the analogue-to-digital converter (ADC). In the second path, the signal goes through a high pass filter, to remove the lower Fourier frequencies, then it is demodulated by the lock-in amplifier tuned to the frequency of the PEM, passed through a low pass filter, and finally fed to the ADC. The first path results in a normal transmission interferogram designated ―DC‖, and the second path produces a differential transmission interferogram designated ―AC‖. This method of acquiring VCD spectra is referred to as double modulation Fourier transform (DM-FT) spectroscopy (Cheng et al., 1975; Nafie and Vidrine, 1982). Having two separate signals, AC and DC, allows one to measure a small difference signal as the amplitude of a periodically varying AC signal, which is more accurate compared to the small difference between two large independent DC signals. Difficulties arise from the two different modulation frequencies, which need to be demodulated in order to perform the necessary data analysis. When the PEM modulation frequency is at least by one order of magnitude greater than the largest Fourier frequency the varying VCD signal can be extracted using the lock-in amplifier tuned to the PEM frequency (Figure 7).

Figure 8. Raw VCD spectra of 40% solutions in CCl4 of (–)-α-pinene (blue), (+)-α-pinene (red), and their sum (black) in a BaF2 cell with 50 μm optical path length (50 DC / 500 AC scans). Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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The AC and DC transmission interferograms are collected and stored in separate blocks and then Fourier transformed to yield the single beam intensity spectra, Iac and Idc, respectively. The ratio of these two spectra yields the so called raw VCD spectrum (Figure 8) according to the relationship (Nafie and Vidrine, 1982):

I AC ( ) 1  2  J1[ 0 ( )]  e2V  ln(10)  A( ) I DC ( ) 2

(5)

where

J1[ 0 ( )] is the first order Bessel function;

 0 ( ) is the maximum retardation level of the PEM at wavenumber;

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V is the velocity of the interferometer‘s mirror; τ is the time constant of the lock-in amplifier; A( ) is the raw VCD spectrum. The raw VCD is multiplied by a constant, which is related to the efficiency of the modulator for producing circularly polarized radiation, and the exponential attenuation factor of the lock-in amplifier. To determine the value of this constant a calibration measurement is required, in which the sample is replaced by a quarter-wave plate and a second linear polarizer. To obtain the calibration spectrum, the fast axis of the quarter-wave plate is positioned parallel to the modulator axis of the PEM (at 45 to the first polarizer). Two VCD spectra are acquired. In the first one the second polarizer is perpendicular to the first polarizer, in the second it is parallel. When these two spectra are overlaid and the points of intersection are connected with a line, the obtained envelope represents the efficiency of circular polarization (Figure 9). Traditionally, most VCD spectra are recorded with dispersive spectrometers in the C-H and C=O stretching regions, or with FT-IR spectrometers in the mid-IR region. FT-IR/VCD instruments, which measure in the mid-IR, are generally limited to the range between 1800800 cm-1. However, it would be useful to measure VCD spectra below this limit, to take advantage of the characteristic skeletal vibrations. There have been two reports of extensions to wavenumbers below 800 cm-1. In the first report by Polavarapu (Polavarapu, 1984, 1989; Polavarapu et al., 1990) a type B MCT detector and ZnSe optics were used to measure FTIR/VCD spectra down to 600 cm-1. In the second report by Devlin and Stephens a dispersive instrument with ZnSe optics and a SiAs detector was used (Devlin and Stephens, 1987). Both measurements were limited by the ZnSe optics. We have attempted to extend the spectral range of our instrument by replacing the type A detector and most of the ZnSe with CdTe and KRS-5 optics. Although this attempt was not quite successful, it showed that further improvements are possible with developing a new prototype PEM for VCD measurements. It should have a larger crystal, i.e. a PEM with a larger aperture, overall higher percent transmission and, if possible, verification of the homogeneity of the crystal. Further improvements might be achieved with a smaller range optical filter, or a more sensitive detector.

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Figure 9. Calibration spectra obtained for parallel and perpendicular orientations of the polarizer to the modulator crystal axes. The points of two spectra intersections produce the envelop curve (grey polygonal line) representing the efficiency of circular polarization after the modulator.

Recently, VCD spectra with continuous coverage from 800 cm-1 in the mid-infrared region (MIR) to 10 000 cm-1 in the near-infrared region (NIR) were reported (Cao et al., 2004; Guo et al., 2006). Commercially available dual-source Fourier transform MIR and NIR VCD spectrometers were equipped with appropriate light sources, optics and detectors, and were modified for dual-polarization-modulation (DPM) operation. The combination of liquid nitrogen and thermoelectric cooled HgCdTe (MCT) as well as InGaAs and germanium detectors operating at room temperature permitted collection of the desired absorbance and VCD spectra across the range of fundamental, combination and overtone vibrational frequencies. This study demonstrated that with modern FT-VCD spectrometers modified for DPM operation, VCD spectra can be measured continuously across a wide spectral range from the MIR to nearly the visible region with an unsurpassed combination of signal-to-noise ratio and spectral resolution. Currently, several commercial instruments from BioTools (USA), Bruker (Germany) and Jasco (Japan) are available on a market, providing the range of 4000-750 cm-1. The noise level for these instruments is reported to be less than 1·10-5 absorbance units at 4 cm-1 resolution, and the acquisition time is less than 20 minutes.

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5. EXPERIMENTAL TECHNIQUES VCD spectra can be difficult to measure. The usual problems are the relatively weak VCD signal, low signal-to-noise ratio (S/N), and the presence of polarization artifacts, which give rise to apparent peaks that do not originate from the sample but rather from the optical arrangement and the non-linearities of the various optical elements. The situation can be improved using a dual-polarization-modulation technique when two PEMs are used instead of one (Nafie, 2000; Nafie et al., 2002). It was found in our laboratory that the raw VCD spectra are most sensitive to reflections from the internal edges of the sample cell and to the position of the detector window (Tsankov et al., 1995; McCann, 1998). Similar results were obtained by Maloň and Keiderling (Maloň and Keiderling, 1988). Consequently, we use a liquid cell with a large aperture to contain our samples. Furthermore, in an effort to expand the spectral range of our instrument with the aid of different optical filters, it became necessary to move the optical filter directly in front of the first linear polarizer. This optical arrangement permits the exchange of optical filters with minor changes to the observed VCD spectra. The alignment of the VCD spectrometer is routinely checked by measuring the VCD spectra of (+) and (–)--pinene or a solution of camphor in CCl4. Both provide good S/N with a short scanning time. The procedure for measuring the VCD spectrum of a chiral sample is presented here using -pinene as an example. After measuring the ‗calibration spectra‘ as described above, the DC and AC spectra of an appropriate solvent can be measured. Their AC/DC ratio yields the raw VCD spectrum. To obtain the absorbance spectrum of a sample, α-pinene in our case, it is necessary to measure the DC spectrum of the sample, and determine the ratio of the DC spectrum of the solvent to the DC spectrum of the sample. The logarithm of this ratio, log10(DCsolvent/DCsample), yields the absorption spectrum of the sample (Figure 10). The maximum absorbance should not be too high, normally below 0.8, otherwise strong peaks may saturate the detector, and produce additional noise in the VCD spectra. The ratio of the AC and DC spectra provides the raw VCD spectrum of α-pinene. This procedure can be repeated for the second enantiomer. If a pair of enantiomers does not adequately exhibit sufficiently opposite VCD patterns, a raw VCD can be corrected by the VCD spectrum of its enantiomer. However, enantiomer correction can be performed only when both enantiomers are available, which is not common for the majority of biomolecules. Therefore, an alternative and more general way to correct a spectrum is a solvent correction. In this case, the final or ‗baseline corrected‘ VCD spectrum can be calculated by subtracting the VCD spectrum of the solvent from the VCD spectrum of the sample followed by the appropriate calibration procedure (Figure 10). The reliability of the measured VCD spectrum is normally estimated as a ‗noise spectrum‘ representing the error estimate calculated for each experimental point of the spectrum (Figure 10). The simple way to obtain the noise estimate is to calculate the spectrum from the average difference in several sequential AC scans. It is possible to further improve the S/N using double source Fourier transform polarization modulation. The improvement in signal-to-noise ratio of up to two (or a factor of four in scan-time reduction for the same signal-to-noise ratio) compared to single source operation was reported by Nafie et al. (Nafie et al., 2004). As mentioned above, the main technical challenges in VCD spectroscopy of biomolecules arise from the weak signal, which results in a poor S/N. There are two different

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ways to improve the situation. First, to reduce the random noise one can accumulate a large number of scans. The random noise and its average tend to zero out with an infinite number of scans, while the actual signal gives a finite value. According to a theory signal-to-noise is proportional to square root of the number of scans, meaning that increasing the number of accumulations, and hence the acquisition time, four times will only double the S/N ratio.

Figure 10. Calibration corrected absorption (top), and VCD (bottom) with its noise estimate (grey line at the bottom of the lower panel) spectra of 40% solutions in CCl4 of (–)-α-pinene (blue) and (+)-αpinene (red) in a BaF2 cell with 50 μm optical path length (50 DC / 500 AC scans).

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The second way to increase the signal comes from the Beer–Lambert–Bouguer law. Since ∆A = ∆ε∙c∙l, one can increase either the sample concentration or the optical path length to increase the signal level and reduce the acquisition time. Indeed, usual sample concentration for proteins and nucleic acids in VCD experiment reaches 30-60 mg/ml, and is 100-1000 times higher than that for a typical ECD measurement. At such concentrations, many proteins are inclined to aggregate. Besides, if one wants to study biomolecules in their natural environment, i.e. in aqueous solutions, one cannot increase the concentration of the sample too much, even if the molecules are soluble, otherwise the sample will become a gel. On the other hand, increasing the optical path length too much will also increase the contribution of the solvent, while hiding spectral features of the sample, and saturating the detector.

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Figure 11. The ‗grooved‘ demountable cell.

Solvents not absorbing in Mid-IR, such as CCl4 or CDCl3, have been widely used for small organic chiral molecules, but they are not suitable for most biomolecules. Instead, water, deuterium oxide or DMSO-d6 have been chosen frequently as solvents for biomolecules (Taniguchi et al., 2004). DNA and protein samples are typically prepared at 3050 mg/ml concentration in D2O (Pančoška et al., 1989; Andrushchenko et al., 2001; Polyanichko and Wieser, 2005). Lower concentrations can be used for experiments utilizing the modern commercial VCD instruments. The measurements are typically carried out in standard CaF2 or BaF2 cells with optical path length of 25-50 μm. CaF2 windows, though less soluble, preclude measurement below 1000 cm-1, whereas BaF2 affords for a wider spectral range, down to ~750 cm-1. For highly viscous samples it might be necessary to use demountable cells. The resulting absorbance of the sample between 1600-1700 cm-1 corresponding to the vibrations of C=O groups at the above conditions is typically ~ 0.2÷0.4 (depending on the sample) for DNA, and ~ 0.5 for proteins, and it gives reasonable VCD signals. According to our experience, better results can be achieved with custom made ‗grooved‘ demountable cells with a fixed path length (Kal'vin and Vel'yaminov, 1987), which consist of a flat cover window (made of standard CaF2 disk) and a second window of the same material, with the center deepened to form a recessed parallel surface surrounded by a trough to accommodate the possible excess of the sample (Figure 11). This design allows preventing evaporation for hours at room temperature. If measurements at higher

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temperatures and/or long-time experiments are required, then the sealing surface of the windows can be covered with mineral oil. The cell of similar design was reported to prevent both evaporation of the solvent at high temperatures (e.g. 95 °C), and changes of the isotope content (when working with D2O solutions), for up to several weeks (Fabian and Mäntele, 2002). Normally only a few microliters of the sample are required to fill the cell. Importantly, this type of cells can be very easily filled with a solution, assembled and disassembled, cleaned between measurements, and it provides a constant pathlength, which is very difficult to achieve with conventional thin teflon spacers. Nowadays, such cells are commercially available with various pathlengths, e.g. from Biotools Inc. (USA). Unfortunately, H2O itself not only absorbs very strongly in the IR region, but its absorbance bands also overlap strongly with the N—H and C=O vibrations, which are crucial for biomolecular studies. As a result, to improve S/N ratio, one has to decrease the optical path length, rather than increasing it, which then requires even higher sample concentrations. When it is important to exclude a solvent contribution completely, it may be possible to measure VCD of dried film samples (Pohle and Fritzsche, 1980; Shanmugam and Polavarapu, 2004b, 2004a, 2005). However, VCD measurement in films should be carried out with a caution since a number of factors can cause artifacts, and may lead to misinterpretations of the spectra. As a result, many DNA and most protein VCD experiments have been carried out in D2O solutions instead. In such a case it is important to completely exchange hydrogen atoms of the sample molecules with deuterium, to exclude the contribution from HOH and HOD absorbance, which can reduce S/N considerably. Exceptions are deuterium-exchange experiments, which provide additional information about labile hydrogen atoms of biomolecules. Although VCD can provide the structural information, the limitations encourage search for complementary techniques. For VCD, such a technique is undoubtedly the Raman optical activity (ROA), which is based on inelastic light scattering of the left and right circularly polarized light (Barron et al., 1996a; Nafie, 1997; Barron, 2004). Both VCD and ROA are sensitive to three-dimensional structure but in slightly different ways. ROA seems to be more local than VCD, as it is not so sensitive to the dipole coupling between nearby groups observed as VCD couplets. A complementary technique is also ECD. It allows one to obtain spectra in aqueous solutions at very low concentrations (10-30 μg/ml). However, higher sample concentrations, comparable to those employed in VCD experiments, can be also measured using cells with optical path length from 0.05 mm to several millimeters. Nevertheless we believe that a combination of VCD with any other technique (including NMR) is highly desirable in all cases when it brings additional insight into the problem.

6. VCD SPECTROSCOPY OF POLYPEPTIDES AND PROTEINS During the last decade infrared spectroscopy became a common tool in studies dealing with the structure of peptides, proteins and enzymes, membrane-bound proteins, and more complex systems. IR spectroscopy is capable of providing information about particular chemical groups within a large molecule, functioning of an enzyme reaction center, about side-chain vibrations in amino acid residues, or about hydrogen bonding in a system. Additionally, it provides information about polypeptide secondary structure. Historically it

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became one of the first methods providing structure of peptides and proteins in aqueous solutions from the analysis of the vibrations of peptide bonds. These vibrations conventionally correspond to the nine regions in IR spectra named amide A, amide B and amides I-VII (Polavarapu and Zhao, 2000; Fabian and Mäntele, 2002): 

 

   

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

amide A region (around 3300 cm-1) and amide B (around 3100 cm-1) correspond to the N-H stretching vibration of the amide group in resonance with 1st overtone of amide II; amide I region (1610–1695 cm-1) corresponds to the C=O stretching; amide II (1480–1575 cm-1) is the region where predominantly the N-H bending coupled to the C-N stretching vibration of the amide group appears; amide III (1300–1100 cm-1), with C-N stretching and N-H bending, as for amide II; amide IV region (625-675 cm-1) corresponds to the O=C-N bending vibration, mixed with other modes; amide V region (640-800 cm-1) is attributed to the out-of-plane N-H bending vibration; amide VI region (535-605 cm-1) is attributed to the out-of-plane C=O bending vibration; amide VII (around 200 cm-1) is a region of skeletal torsion.

Among all amide bands the strongest and most useful is amide I, originating from the C=O stretching vibration of the amide group, slightly coupled to in-plane bending of N-H and stretching of the C-N bonds (Fabian and Mäntele, 2002). In water solutions this band overlaps with a strong H-O-H water bending signal. In practice, it is thus easier to obtain protein spectra in D2O instead of H2O. D2O has a transparency window in 1800-1400 cm-1. The substitution of the solvent leads to proton-deuterium exchange in proteins, affecting corresponding vibrational modes in peptide bonds. As a result, the amplitude of N-H bending decreases, while its frequency downshifts by nearly 100 cm-1 to 1450 cm-1 (amide II'). Amide I bands are almost unaffected by the deuteration, showing only 5-10 cm-1 shift in frequency. The amide I' and amide II' vibrations, along with the side-chain modes in the region between 1400-1800 cm-1, are the primary targets of VCD spectroscopy. Although VCD spectroscopy is sensitive to the three-dimensional structure of biopolymers, it does not provide information about absolute atomic coordinates. However, often the question of interest is not a molecular structure at the atomic resolution, but the overall conformation and conformational transitions of a molecule. To assign certain spectral features to a particular protein conformation, to α-helix or β-sheet, for example, one can first study the samples of known and well-characterized structures determined by other methods. The first VCD signal of a polypeptide was observed in the amide I, II and A regions (Singh and Keiderling, 1981). Shortly after that, the VCD spectra for a variety of polypeptides were compared in amide A (N—H stretch) and amide I (C=O stretch) vibrations (Lal and Nafie, 1982). The analysis of the spectra obtained in these experiments led to the conclusion that the spectral pattern in the both regions was sensitive to α-helicity, and not to the absolute configuration of the constituent amino acids. The amide I vibrations became the most characteristic and most easily accessible of all VCD bands.

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Empirical VCD studies resulted in the identification of several characteristic VCD features based on the correlation of VCD spectra with known secondary structures of peptides and proteins (see (Polavarapu and Zhao, 2000; Keiderling, 2001) and references therein). The most common secondary structures of proteins, such as α-helix, β-sheet and random coil, were easily detectable in VCD spectra. In addition, VCD appeared to be sensitive to 310helices, β-turns, β-hairpins and π-helices, which became sometimes also spectroscopically distinguishable in proteins. A brief summary of reported correlations between the VCD patterns and the main secondary structures is given below (Figure 12). α-Helix. For right-handed α-helices the following characteristic spectral features have been identified (Singh and Keiderling, 1981; Sen and Keiderling, 1984; Yasui et al., 1986a; Yasui et al., 1987; Maloň et al., 1988; Baumruk et al., 1994): a negative couplet in the amide A region at ~3300 cm-1 and a negative-positive couplet in the amide I region at ~1655 cm-1; a negative band in the amide II region at ~1550 cm-1, a larger negative VCD signal at 1520 cm-1 for which the absorption band has only weak intensity; and a positive band in the amide III region (1350-1250 cm-1). Similar experiments in D2O showed that the substitution of amide N—H hydrogens with deuterium results in an isotopic shift of the amide II negative VCD band to below 1450 cm-1, while the amide I VCD couplet often changes to a w-shape like negative-positive-negative triplet. The above VCD features are considered to be characteristic of right-handed α-helical structures, as confirmed in a number of experiments with different peptides and polypeptides, which are known to adopt the α-helix. β-Sheet. VCD spectra of β-sheet polypeptides are very difficult to obtain due to weak signal and extensive peptide precipitation at high concentrations required for the measurements. The shape of amide I couplet in the reported spectra, although distinctly different from the α-helical pattern, was considerably influenced by aggregation. Generally, two separate negative bands in the amide I region are considered to be characteristic features of the antiparallel β-sheet structure. In addition, two reasonably resolved negative VCD features in amide II and III regions were reported. If a protein contains a mixture of α-helical and β-sheet fragments, the VCD spectra also show a mixture of α-helical and β-sheet bands resulting in a characteristic w-shaped spectral pattern (Yasui and Keiderling, 1986; Baumruk et al., 1994; Yoder et al., 1997). Random coil. The random coil structure is represented in VCD spectra by a positivenegative VCD couplet in the amide A region, and a negative-positive couplet with a relatively intense negative part in the amide I region. Weak VCD signals are seen in the amide II region with a positive band at 1520 cm-1. The amide I couplet occurs at lower wavenumbers with opposite sign compared to an α-helix, and it appears to be insensitive to the deuteration. Surprisingly, the shape of this spectral pattern is similar to that of poly-L-proline II (Dukor and Keiderling, 1991), which adopts a left-handed 310 helical conformation. This is consistent with the concept that these random coil structures, although not of long-range order, have some local structural order, and can be viewed as the ―polyproline II‖ conformation. Such structures have locally ordered regions with left-handed helices similar to poly-L-proline helices (Paterlini et al., 1986). This idea was many times confirmed experimentally, which also showed that this kind of order in a molecule can be destroyed by heating (Keiderling, 2001). Computational studies in conjunction with VCD measurements also confirmed these results (Birke et al., 1992). A random coil structure without any local ordering might be

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referred to as an ―unordered random coil‖, for which the VCD in the amide I region vanishes (Polavarapu and Zhao, 2000). 310-Helix. The 310-helix (Yasui et al., 1986a; Yasui et al., 1986b) is represented by a conservative negative-positive VCD couplet in the amide A region. Amide I VCD appears as a couplet with the positive band stronger than the negative one. But the amide I couplet is much weaker than the corresponding VCD features in amide II region, where 310-helices give negative VCD which is attributed to the absorption at ~1520 cm-1. This is different from that seen in α-helical structures, where the absorption peak is at ~1550 cm-1 and the negative VCD peak is at ~1520 cm-1. Besides, α-helical structures produce much stronger VCD signal in the amide I region than the corresponding amide II mode.

Figure 12. VCD spectra of the polypeptides in amide I and amide II regions with shapes typical for αhelix (panel α), β-sheet (panel β), and random coil (panel γ).

Examples of less common protein structures studied by VCD (Polavarapu and Zhao, 2000) demonstrate the ability of VCD spectroscopy to distinguish not only the major peptide conformations, but also those with only small differences in local structure (Keiderling, 2001). VCD studies of oligopeptides yielded an interesting and a very important experimental as well as theoretical results, which describe the general dependence of VCD signal on

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polypeptide length (discussed in more details in (Keiderling, 2001)). Investigating VCD patterns of oligopeptides adopting different conformations and with different degree of polymerization, n, the authors have shown that basic VCD band shapes for amide I, II, and A vibrations were normally established by n = 4. This result, together with the above ‗random coil‘ example, indicates that short-range interactions are dominant in VCD. An important application of VCD is also the determination of the absolute configuration of synthetic or natural compounds. Generally, to determine the absolute configuration it is necessary to compare the experimental VCD spectrum of an enantiomerically pure sample with a theoretically calculated one. As it was mentioned above, this is very complicated for biomolecules. However, several reports have been published recently describing similar approach to VCD studies of model peptides (Yasui et al., 1986a; Yasui et al., 1986b; Bouř and Keiderling, 1993; Bouř et al., 1997). The detailed analysis of the experimental and theoretically calculated data allowed the authors to analyze peptide structure based on the information about dihedral angles ψ and φ calculated theoretically.

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6.1. VCD Spectrum-to-Structure Correlations for Proteins The fact that peptide fragments as long as 3 to 4 amino acid residues have distinctive VCD features implies that the spectra contain very specific information, and hence should be very different for different proteins. Indeed, although some general patterns have been established for protein VCD including those for α-helices, β-sheets, 310-helices, random-coils, and some other helices and turns, their spectral features demonstrate significant shifts in frequencies and bandshapes. This makes VCD spectra more informative then ECD or FTIR ones, but the analysis of the spectra may be still complicated. The variations in VCD spectra are particularly typical for the amide I region. For example, for a protein containing both αhelix and β-sheet fragments the VCD measured in D2O demonstrate characteristic even though relatively weak negative-positive-negative patterns, which are qualitatively reproducible in different proteins with considerable quantitative variations. Such variations make it difficult to perform accurate quantitative analysis, although one can easily establish the type of secondary structure, which dominates in the protein (Gupta and Keiderling, 1992; Pančoška et al., 1993; Keiderling et al., 1994). To estimate structural composition of a protein quantitatively based on its VCD spectrum, several approaches are used. Most of them are based on representation of a given spectrum as a linear combination of spectra from a so-called ―training set‖, which combines VCD spectra of several proteins with known structure. This approach is essentially similar to the one used for ECD analysis, which gives reasonably good results for the proteins similar (in terms of amino acid composition, charges etc.) to the proteins from the training set. The combination of VCD with ECD and FTIR helps to further improve the results of this analysis (Keiderling, 2001). Alternatively, an approach based on factor analysis has been also developed (Keiderling and Pančoška, 1993; Pančoška et al., 1995; Pančoška et al., 1999). In this approach the first sub-spectrum typically represents the most common elements of all the experimental spectra in the set. The second represents the major deviations in the set from the average. Each successive sub-spectrum then becomes less significant, and eventually represents a noise. Such a model allowed the authors to describe the protein spectra in terms

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of a relatively small number of coefficients. Their results indicated that as many as six orthogonal sub-spectra were required to reconstruct a VCD spectrum of any protein.

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6.2. Isotopic Labeling in VCD Experiments Statistical and model spectra approaches to protein secondary structure analysis are not the only ways to improve VCD spectroscopy of proteins. It is also fruitful to employ modern biochemical tools such as site-directed mutagenesis. However, changes in the amino acid sequence may interfere with the protein structure and function. Isotopic labeling by stable isotopes avoids such perturbations. The isotopic replacement of an atom in a chemical group may change the frequency of a vibration. Ligands, cofactors and protein side-chains, as well as backbone groups can be labeled. Labeling ligands has proven to be a very powerful method in IR spectroscopy when the interactions between ligands and proteins are investigated (Alben and Caughey, 1968; Belasco and Knowles, 1980; Potter et al., 1987). The isotopic labeling is frequently used to obtain information about interactions between particular residues in peptides and proteins (Silva et al., 2000; Kubelka and Keiderling, 2001; Silva et al., 2003; Barber-Armstrong et al., 2004; Huang et al., 2004; Pandyra et al., 2005). For example, substitution of 13C into a single amide C=O shifts the amide I vibration in an αhelix by ~40 cm-1 towards lower wavenumbers. Thus the 13C labeled carbonyl groups can be resolved from the 12C ones, although the isotopic effect is overlapped with the coupling. The exact value of such a shift depends on particular structures and number of isotopic substitutions. IR studies of 13C labeled peptides demonstrated that the isotopic frequency shift could not be determined without additional assumptions about the overall structure of the peptide. In VCD spectra each of 13C-shifted bands has a unique conformationally sensitive shape, which makes definitive conformational assignments possible for a specific fragment of a molecule. By combining theoretical calculations with experimental results Huang et al. showed that considering only transition dipole coupling is not enough to explain experimental effects (Huang et al., 2004). The authors also provided experimental and theoretical evidence that 13C labeled vibrations are almost decoupled from the rest of the peptide and thereby the 13 C labeling provides a useful local probe for stereochemical VCD studies. This result opens up the broad area of possible applications of isotope labeling in peptide studies. Besides applications to short peptide studies, isotope labeled VCD measurements can be used to study protein-protein interactions. Uniform isotope labeling of calmodulin with 13C shifted its amide I VCD band by ~43 cm-1 to lower wavenumbers, which opened up a spectral window to simultaneously visualize a bound target protein (Pandyra et al., 2005). This study became the first example of how isotope labeling enables VCD studies of protein–protein interactions.

6.3. Protein-Metal Ion Interactions Probed by VCD Metal ions play an essential role in about one third of enzymes (Glusker, 1991; Silva and Williams, 2001). These ions can modify electron flow in a substrate or enzyme, thus effectively controlling an enzyme-catalyzed reaction. They can serve to bind and orient substrates with respect to functional groups in the active site, and they can provide a site for redox activity if the metal has several valence states. Very often, the appropriate metal ion

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catalyzes a biochemical reaction, acting as a co-factor of a metalloenzyme, without which the reaction would proceed very slowly. Many enzymes have the side-chain functional groups arranged in a way designed specifically to bind the required metal ion. Sometimes, this arrangement is very intricate and implies appropriate hydrophobic or hydrophilic environment in the binding site. Metal ions may be bound by main-chain amino and carbonyl groups, but specific binding is achieved by the amino acid side chains, particularly the carboxylate groups of aspartic and glutamic acid, and the ring nitrogen atom of histidine. Other amino acids, side chains of which can bind metal ions include tryptophan (ring nitrogen), cysteine (thiol), methionine (thioether), serine, threonine, tyrosine (hydroxyl groups), asparagine, and glutamine (carbonyl groups, less often amino groups) (Glusker, 1991). Each metal ion has its own chemistry (for more details see for instance (Sigel and Sigel, 1973)). An example of the differing reactivities of metal cations is provided by their ability to bind or lose water molecules. The exchange of coordinated water with bulk solvent by various cations has been categorized into four groups (Glusker, 1991; Silva and Williams, 2001). Those for which the exchange rate is greater than 108 per second include alkali and alkaline earth metal ions (except beryllium and magnesium), together with Cu2+, Cd2+, and Hg2+. Intermediate rate constants (from 104 to 108 per second) are found for Mg2+ and some of the divalent first-row transition metal ions. Those with slow rate constants (from 1 to 104 per second) include Be2+ and certain trivalent first-row transition metal ions. The inert group with rates from 10-6 to 10-2 per second contains Cr3+, Co3+, Rh3+, Ir3+, and Pt2+. One of the factors involved in rates of exchange is the charge-to-radius ratio; if this ratio is high the exchange rate is low. Metal ions are known to be important co-factors not only for enzymes, but also for proteins performing transport and structural functions. Hemoglobin is a well-known example of the crucial role of iron. More recent studies revealed biological importance of many other metal ions and metal complexes in functioning of various protein systems (Santagata et al., 1998; Shockett and Schatz, 1999; Hadden et al., 2002; Ikura et al., 2002; Noble and Maxwell, 2002; Yamagata et al., 2002), or, visa versa, proteins play an important role in the functioning of metal complexes such as metal based drugs (Sharma and Piwnica-Worms, 1999; Boulikas and Vougiouka, 2003; Onyido et al., 2004; Wang and Lippard, 2005). Similarly to other spectroscopic techniques, infrared spectroscopy provides an opportunity to study conformational changes in macromolecules in the presence of metal ions and small ligands. Sometimes VCD also allows identification of specific interactions between the ligands and particular chemical groups in a protein especially when used in a combination with other techniques. In both cases, the conclusions about interactions and conformational changes in a complex are based on the interpretation of the changes in the VCD spectra of the proteins (Barron et al., 1996a; Urbanová et al., 2001; Pandyra et al., 2005). Another approach of studying biologically relevant metal complexes and metalloproteins is based on the analysis of VCD bands arising from low-lying electronic f→f or d→d transitions at a metal center (Freedman and Nafie, 1993). In some cases, such transitions can be detected indirectly due to the interaction between vibrational and electronic states (Cheng et al., 1975; Nafie et al., 1976; Barnett et al., 1980). In other experiments, the coupled oscillator model was used to determine the solution conformation of the tripodal peptide L,L,L-tris(N-Boc-leucylamidoethyl)-amine (Paterlini et al., 1992), and to interpret VCD spectra of bis(acetylacetonato)(L-alaninato)cobalt(III) (Young et al., 1985). Similar studies

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were performed with metal complexes with alanine, β-alanine, glycine, proline, and threonine ligands containing Ni(II), Co(II), Cr(III), Cu(II), and Pd(II) (Young et al., 1985; Freedman et al., 1987; Young et al., 1987). In all cases, the authors demonstrated that the VCD features are characteristic of the configuration of the complex and the ligand conformations. Further investigations of transition metal complexes combined measurements and theoretical calculations based on density functional theory (He et al., 2001; Freedman et al., 2002; Bodack et al., 2004). VCD has been employed also to the investigations of heme proteins (Bormett et al., 1994). Using site-directed mutagenesis the authors were able to examine the environment of the iron ion in heme proteins by analyzing the vibrational circular dichroism spectra of the stretching vibrations of azide and cyanide ligated to the Fe3+ atoms of hemoglobin and myoglobin. It was shown that VCD is extremely sensitive to the chiral environment of the ligands and can be used to examine ligand binding in heme and non-heme metalloenzymes. The results of the experiment indicated that VCD was more sensitive to protein ligation substrates than IR absorption. The ligand VCD spectra were sensitive to steric and hydrogen bonding interactions of the ligand with surrounding amino acid residues, and to the attachment of other ligands to the metal. This work has demonstrated that VCD was a sensitive technique for examining the structure of metalloenzymes.

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7. VCD SPECTROSCOPY OF NUCLEIC ACIDS AND THEIR COMPLEXES Structural organization of nucleic acids has been extensively studied since 1950s. Development of such powerful techniques as X-ray diffraction and NMR provided the ability to solve some of the nucleic acid structures with atomic resolution. However, as it was mentioned above, in living cells nucleic acids perform their functions in aqueous media being a part of large supramolecular complexes. Under these conditions vibrational spectroscopy provides the effective tools for structural studies, including infrared absorption spectroscopy, vibrational circular dichroism (VCD), Raman spectroscopy and Raman optical activity (ROA). They are applicable to studies of biological molecules in solution with no limitations placed on the molecular size. Using those techniques it was possible to follow conformational transitions in nucleic acids (A, B, Z, parallel/antiparallel, double helical/triple helical, etc.), determine the type of base-pairing (Watson-Crick, Hoogsteen, etc.), sugar conformations, torsion angles etc. (see (Tsuboi, 1969; Taillandier and Liquier, 1992; Keiderling, 1996; Taillandier and Liquier, 2002) and references therein). The first experimental applications of vibrational circular dichroism spectroscopy to study nucleic acids were reported about 20 years ago, when VCD spectra of several poly(ribonucleic acid) samples were first obtained (Annamalai and Keiderling, 1987). The following years demonstrated a rapid growth in the number of related studies, including theoretical and experimental studies of RNA (Xiang et al., 1993; Yang and Keiderling, 1993), conformational analysis of DNA (Gulotta et al., 1989; Zhong et al., 1990; Birke et al., 1993; Wang et al., 1994a; Wang et al., 1994b) and non-canonical nucleic acid structures (Annamalai and Keiderling, 1987; Andrushchenko and Bouř, 2010). The main goal of those experiments was to understand the nature of nucleic acid VCD and to determine the characteristic spectral profiles for different conformations, similar to those in ECD. Despite

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the fact that the majority of the data obtained were qualitative rather than quantitative, the very first VCD studies of nucleic acids combined experimental spectroscopy and theoretical calculations, which to a large extent determined the future progress of the technique. The approach proved to be sensitive to nucleic acid conformations, although the corresponding spectral changes appeared to be less prominent compared to ECD, or VCD of polypeptides. Originating from a dipole-dipole coupling of neighboring chromophores VCD reflects local structural order in polymer chains. The VCD spectra of nucleic acids consist of two most informative regions: between 1800-1500 cm-1 and 1150-800 cm-1. The former primarily corresponds to the in-plane double bond stretching vibrations of the bases, while the latter is attributed to the vibrations of the sugar-phosphate backbone (Figure 6 and Table 1). It was shown that the intensity of VCD spectra and band shapes corresponding to base vibrations in the region between 1600-1700 cm-1 depend on structural order, base pairing, stacking interactions and nucleotide sequence (Annamalai and Keiderling, 1987; Maharaj et al., 1995; Tsankov et al., 2007). The magnitude of the VCD signal in this region is generally higher for highly ordered samples. Based on the data obtained for different oligonucleotide samples it was concluded that the VCD spectra in this region can be used for identification of single-, double- and multistranded structures. For the majority of the single-stranded RNA samples VCD was characterized by a strong positive couplet between 1700-1600 cm-1, arising from C=O stretches or ring vibrations of the bases. Mononucleotides possessed small or no VCD signal (Annamalai and Keiderling, 1987). In general, A-DNA and RNA VCD spectra are quite similar in this region, being slightly different from B-DNA due to the changes in helical parameters (Keiderling, 1996).

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Table 1. Main vibrations contributing to VCD spectra of nucleic acids Band position, cm-1 1700(-) 1698(-)/1665(+) 1671(+)/1656(-) 1666(+) 1640(+) 1619(-) 1504(-) 1088(-)/1068(+) 1087(+)/1075(-) 1120(-)/1080(+) 1060(+) 1034(-)/1008(+) 972(-)/957(+) 936(-)/896(+)

Assignment C(2)=O of thymine C(6)=O (G) coupled with C(2)=O (C) and C(4)=O (T) C(6)=O (G) in Z-form of (dG-dC)20 Stretching vibrations of C=O groups in guanine and cytosine Mostly C(6)=O (C); C(4)=O (T) coupled with C(6)=O (G) Ring vibrations of adenine C=N stretching in cytosine Symmetric stretching vibrations of PO2- in B-DNA Symmetric stretching vibrations of PO2- in Z-form of (dG-dC)20 Symmetric stretching vibrations of PO2- in A-dsRNA C-O sugar Deoxyribose ring vibration C-C sugar stretching vibration Sugar ring vibrations. DNA B-form markers

The VCD attributed to symmetric phosphate vibrations is represented by a strong couplet at around 1080 cm-1. It was shown to be more sensitive to the secondary structure of nucleic acids rather than to their sequence. The VCD for right-handed A- and B-DNA in this region is represented by a positive couplet, while it changes to a negative one for left-handed Z-form (Wang et al., 1994b). The ribose vibrational modes in RNA overlap phosphate vibrations in this region. The overlapping is additive, resulting in broadening and slight frequency shift towards the higher wavenumbers (Keiderling, 1996). At the same time, antisymmetric P-O vibrations in the range between 1300-1200 cm-1 do not show detectable VCD (Annamalai and Keiderling, 1987).

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Speaking about studies of biological molecules, we should mention one more important advantage of VCD over other techniques. The possibility to carry out VCD experiments in a solution allows to easily vary temperature, pH, ionic strength, and ionic content of the environment. As a result, VCD provides a unique opportunity to study conformational stability and follow structural changes of the molecules at biologically relevant conditions. Rapid development of the VCD instrumentation along with theoretical approaches (Andrushchenko and Bouř, 2010) made this technique very useful for structural investigation of biological molecules and their complexes. Although, it might be still a challenging task to interpret the large amount of structural information the VCD spectra provide, we believe that further progress in computational methods will greatly improve and simplify the VCD analysis in coming years.

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7.1. VCD Studies of Conformational Transitions in Nucleic Acids The first VCD experiments that questioned the applicability of the technique to the investigation of nucleic acid conformations were performed by the group of Keiderling, who studied synthetic ribonucleic acids (Annamalai and Keiderling, 1987). Double-stranded RNA samples gave the first VCD spectra of the A-form. Very soon, VCD spectra of B-Z conformational transition in DNA were obtained by the group of Diem (Gulotta et al., 1989). Within the next few years these two groups successfully applied VCD to study B-family DNA structures (Zhong et al., 1990), B-A conformational transition in DNA (Wang and Keiderling, 1992), thermal stability of oligonucleotide sequences in B- and Z-conformations (Birke et al., 1993), B-Z transitions in inosine-containing oligonucleotides (Wang and Keiderling, 1993) and triple-helical nucleic acids (Yang and Keiderling, 1993; Wang et al., 1994a). These experiments have demonstrated that the VCD spectroscopy is applicable to discriminate A-, B- and Z- conformations. However, it was shown that the difference in VCD spectra between A- and B-forms of DNA in solution were not sufficient for the conformational analysis. The major obstacle here is the sample preparation procedure. It is known, that the B→A conformational transition requires DNA dehydration (Saenger, 1984), which can be achieved by partial (70% to 85%) substitution of water by alcohol in solution (Ivanov et al., 1974). However, it is not easy to obtain concentrated DNA solutions suitable for VCD measurements at these conditions, due to DNA precipitation in the presence of alcohol. Besides, limitations in solvent transparency in IR region do not allow increasing pathlength. The situation can be improved by using triflouroethanol (TFE) instead of ethanol, but even then only vibrations in DNA bases are available for observation in VCD. Since the base vibrations in DNA are influenced only by the neighboring bases, but not by the sugars, the VCD spectra of B- and A-forms of DNA do not differ much, reflecting mainly the difference in AT/GC content of the samples (Wang and Keiderling, 1992). Hence, inability to observe vibrations of the phosphate backbone resulted in the lack of structural information in B→A transition analysis. There are two possible ways to overcome these limitations: (i) achieve DNA dehydration by drying samples and work with films for example, and (ii) use double stranded RNA (dsRNA) instead of DNA. The first way is not quite biologically relevant, not speaking about the serious experimental difficulties handling films in VCD experiment. Instead, IR absorption spectroscopy, particularly attenuated total reflectance

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(ATR-IR) can be recommended for film samples, which is also sensitive to the nucleic acid conformations (Taillandier and Liquier, 2002). The second way allows using aqueous solutions for double-stranded RNAs always adopting A-form geometry in solution. The VCD experiments with dsRNA revealed intensity and band position differences in phosphate region between 1150-1000 cm-1, which were in a good agreement with theoretically calculated spectra (Wang et al., 1994b). Although this approach enables simultaneous observation of VCD in both the base and the phosphate spectral regions, it does not allow to observe the B→A transition directly. Instead, the results from different experiments have to be compared, involving dsDNA for B-form and dsRNA for A-form geometries. Thus, while VCD experiments allow studying B→A transition in nucleic acids, they are not ‗straightforward‘ and have not become a routing procedure yet. The situation is completely different for the transition to Z-form geometry. From the very beginning it was determined that VCD signal in the region of 1550-1750 cm-1 is sensitive to the handedness of the polymer helix (Gulotta et al., 1989). The characteristic B-form VCD couplet in this region changes its sign and exhibits a significant frequency down shift in the spectra of Z-DNA. Similar behavior was observed in the phosphate region, where the VCD couplet centered at ~1100 cm-1 also has the opposite sign and reduced magnitude (Figure 13) compared to the spectra of the B-form (Wang et al., 1994b). Analysis of VCD spectra allowed to reveal several earlier misinterpretations of ECD spectra (Wang and Keiderling, 1992; Keiderling, 1996). Usually, the B→Z conformational transition in DNA solutions is induced by adding some salts at relatively high concentrations to GC-rich sequences (Keiderling, 1996; Andrushchenko et al., 2003a). Sometimes it leads to DNA aggregation, and as a result, to poor reproducibility. However, the major spectral features mentioned above, such as reduction in magnitude and reverse sign in both base and phosphate spectral regions are confirmed by independent measurements in several laboratories. The typical VCD spectra of (dG-dC)20 in B- and Z-conformations are shown in Figure 14 along with the proposed assignments (Table 2) based on the earlier results, obtained in our group (Andrushchenko et al., 1999; Andrushchenko et al., 2002b; Andrushchenko et al., 2003a).

Figure 13. Idealized VCD spectra of B-form (bold line with stronger VCD signal) and Z-form (thin line) of DNA in the phosphate region. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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Figure 14. VCD spectra of (dG-dC)20 in B-form (solid line) and Z-form (dashed line).

Table 2. Band assignments for VCD spectra of (dG-dC)20 in B- and Z-forms B-form (cm-1) 1691(-)/1678(+) 1633(+)/1654(-) 1637(+) 1573(+) 1570(+)/1556(-) 1527(+)/1521(-) 1506(+)/1498(-) 1089(-)/1070(+) 973(-)/958(+)

Z-form (cm-1) 1671(+)/1656(-) 1637(-)/1627(+)

1561(-)/1540(+) 1502(-)/1492(+) 1087(+)/1075(-) 969(+)/946(-)

Assignment С(6)=O stretch (G) C(2)=O stretch (C) C=C stretch (C) + C=O stretch (G) C-ND2 stretch (G) C=N stretch (G) C-ND2 bend + def (C) C=N stretch (C) Symmetric PO-2 stretch Deoxyribose C-C stretch

Another example of nucleic acid conformational analysis where VCD provides insight into important structural details is studying of non-canonical base pairing, DNA triplexes and Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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quadruplexes (Frank-Kamenetskii and Mirkin, 1995; Burge et al., 2006). The sensitivity of VCD to multi-stranded structures was demonstrated in a study of poly(rA)*poly(rU) dsRNA melting (Yang and Keiderling, 1993). The authors found two distinct phase transitions. It was shown that on the first stage transition from a double- to a triple-stranded form occurred, which was followed by a triple- to single-strand transition on the second stage. Similar results were obtained in the presence of Ni2+ (Andrushchenko et al., 2002a). The typical VCD spectra of a double- and a triple-stranded forms of poly(rA)*poly(rU) RNAs at room temperature are shown in Figure 15.

Figure 15. VCD spectra of double- and triple-stranded RNA.

The four-stranded intercalated DNA structure exemplified by the oligonucleotide d(C)12 at acidic pH was also studied by VCD spectroscopy (Tsankov et al., 2006). It was found that formation of the four-stranded intercalated structure of the cytosine dodecamer at acidic pH (so called i-DNA motif) showed distinct changes in VCD compared to the single-stranded conformation at neutral pH. The protonation at N3 and the formation of the C+·C base pairs lead to substantial π-electron density redistribution, which affected most bands in the spectra. The most striking feature found was the reversed sign of the main C(2)=O stretching couplet of the protonated species. It implies specific reorientation of neighboring base pairs, which affects the stacking interactions of the carbonyl groups. It was concluded, that in order to avoid the repulsion between the charged pyrimidine rings and therefore their destabilizing effect on the whole molecule, the i-DNA motif adopts a structure in which the six-membered aromatic rings do not overlap directly. Instead, the exocyclic carbonyl and amino groups stack in an antiparallel orientation, thereby affecting the sign of the VCD couplet. The spectra in the sugar-phosphate backbone region of i-DNA were also studied and were found significantly different from the double-stranded configuration. Based on the spectral analysis it was shown that such a specific backbone conformation is yet another characteristic feature of the four-stranded intercalation motif. The close distance between base paired backbones,

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where the interstrand P–P distances are shorter than the intrastrand distances between the adjacent phosphorus atoms, favors the formation of interstrand CH···O bonds. It was shown, that an extensive network of CH···O bonds involving C1', C4' and O4' was established, which twists the backbone in such a way that multiple through space vibrational coupling occurs among neighboring sugar-phosphate residues resulting in unusual VCD signals in this spectral region (Tsankov et al., 2006).

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7.2. Interaction with Metal Ions Metal ions are present in practically all biological systems, and participate in many biological processes. They can stabilize and destabilize biological structures. They are found in intimate association with nucleic acids in their natural environment. Together with water molecules in the hydration shell they determine DNA conformation (Saenger, 1984). Vibrational spectroscopy in general, and absorption infrared spectroscopy in particular, have been extensively used to probe the effects of metal ions on nucleic acid structure (Alex and Dupuis, 1989; Tajmir-Riahi and Messaoudi, 1992; Tajmir-Riahi et al., 1993a, 1993c, 1993b; Ahmad et al., 1996, 2003; Arakawa et al., 2000). Applications of vibrational circular dichroism spectroscopy helped to reveal some important aspects of metal ion interaction with nucleic acids that were not evident from IR. The VCD spectroscopy has been successfully applied for investigation of oligonucleotide and high molecular weight DNA complexes with metal ions. These included conformational transitions of nucleic acids, namely, B- to Z-form, duplex-triplex-single strand, DNA condensation and aggregation induced by metal ions. VCD has been also applied to study the interaction of an antitumor drug cisdiamminedichloroplatinum(II) (cis-DDP or cisplatin) with DNA. More recently VCD revealed some structural aspects on the interaction of nuclear proteins with DNA in the presence of divalent metal ions, such as Ca2+, Mg2+ and Mn2+. More details on these and other VCD investigations dealing with interactions between metal ions and nucleic acids can be found elsewhere (Andrushchenko et al., 1999; Andrushchenko et al., 2001; Andrushchenko et al., 2002a; Andrushchenko et al., 2003a; Andrushchenko et al., 2003b; Andrushchenko et al., 2003c; Tsankov et al., 2003a; Tsankov et al., 2003b; Polianichko et al., 2004; Polyanichko et al., 2004; Polyanichko et al., 2006). A very important aspect of metal ion effect on DNA is a facilitation of DNA condensation and aggregation. Divalent metal ions, especially at increased temperatures, can induce DNA aggregation (Bloomfield, 1996). Trivalent and higher valence ions as well as divalent ions at certain conditions can induce DNA condensation into highly condensed particles in vitro (Bloomfield, 1997). The condensation process plays a very important role in DNA packing in living cells as well as in the process of gene delivery for gene therapy. During condensation a DNA molecule transforms (or several molecules assemble) into very dense higher ordered three-dimensional structures, enabling DNA to reduce its volume by 104–106 times (Arscott et al., 1990). In the process of aggregation, DNA also forms supramolecular structures. But in contrast to condensation these structures are not highly ordered and are relatively loose. The supramolecular structures formed upon DNA condensation produce so called ψ-type ECD spectra (PSI – Polymer and Salt Induced). The shape of the ψ-type spectra originates from a higher-ordered arrangement of DNA in large condensed particles. However, considerable light scattering present in such systems makes

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conventional structural and spectroscopic techniques inapplicable to study DNA structure within these supramolecular complexes (Bustamante et al., 1980b, 1980a; Tinoco et al., 1980a; Bustamante et al., 1981, 1982, 1983; Hall et al., 1983; Tinoco et al., 1983; Bustamante et al., 1984; Bustamante et al., 1985; Keller et al., 1985b, 1985a). Figure 16 shows typical VCD and IR spectra obtained for B-DNA in aqueous solution and for the same DNA condensed by Cr3+ ions. It was revealed (Andrushchenko et al., 2001) that condensed DNA produces a ψ-type VCD spectrum, which is characterized by manifold (2-10 times) increase in intensity of the VCD signal at the unchanged absorption intensity, similarly to ECD ψ-type spectra. Presence of the B-form marker bands in the IR spectra along with the strong VCD signal indicate that the secondary structure of DNA before and after the condensation remains within the B-form family with no noticeable DNA denaturation. It can therefore be confirmed unambiguously and without need for any additional tools and experiments that the DNA secondary structure of the ψ-type condensates remains in the Bform (Andrushchenko et al., 2001; Andrushchenko et al., 2003a; Andrushchenko et al., 2003c).

Figure 16. VCD (left panel) and IR absorption (right panel) spectra of DNA before (bottom) and after (top) the condensation induced by Cr3+ ions. The spectra in each panel are shown on the same scale. The top spectra are shifted along Y-axes for clarity. The wavenumbers of the B-form marker bands are shown for the IR spectra.

Another example of VCD application to the investigation of metal-(nucleic acid) interactions is the interaction of Mn2+ with DNA in solution (Andrushchenko et al., 1999; Andrushchenko et al., 2003c; Polyanichko et al., 2004; Polyanichko et al., 2006). A combination of VCD and ECD approaches revealed several stages of the interaction between manganese and calf thymus DNA (Polyanichko et al., 2004). Conformational transition towards the C-form of DNA was observed in solution at the molar ratio of Mn2+ to DNAphosphates in the range of 0.1-1.5. It was shown, that manganese interacted both with the phosphates and with the bases of DNA at higher Mn2+ content. However, it is unlikely that direct chelation between manganese and DNA bases occurred. Instead, it was suggested that

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the interaction between manganese ions and DNA was mediated by water molecules. This interaction leads to destabilization of the DNA double helix and partial breaking of the hydrogen bonds between the bases in the pairs. At high Mn2+ concentrations DNA aggregation was observed. It was also shown that there are two possible effects of manganese ions on DNA structure: (1) neutralization of the negative charge of the phosphate backbone and stabilization of the double helical structure, and (2) prevention of DNA renaturation by interaction with the sites of the bases involved in base pairing. These results are in a good agreement with the results of thermal denaturation of DNA in the presence of manganese ions studied by VCD (Andrushchenko et al., 2003c). It was demonstrated that Mn2+ ions bind mainly to N7(G) and to phosphate groups. Mn2+ chelation between N7(G) and a closest phosphate group of the same strand was suggested. This type of binding results in opening the GC base pairs involved and decreasing the stability of a DNA double helix. Consequently, the N3 sites of cytosine may participate in metal ion binding to a small extent. At elevated temperatures, DNA denaturation with a significant decrease of the melting temperature of DNA was observed. It was attributed to a decrease of DNA stability induced by Mn2+. VCD demonstrated sensitivity to DNA condensation and aggregation as well as an ability to distinguish between these two processes. No condensation or aggregation of DNA was observed at room temperature at any of the metal ion concentrations studied. DNA condensation was revealed in a very narrow range of experimental conditions at around 2.4 [Mn]/[P] and about 55°C (Figure 17). DNA aggregation was observed in the presence of Mn2+ ions at elevated temperatures during or after denaturation. VCD spectroscopy turned out to be useful for studying DNA condensation and aggregation due to its ability to distinguish between these two processes, and for providing information about DNA secondary structure in a condensed or aggregated state.

Figure 17. VCD spectra of DNA with 2.4 [Mn]/[P] at room temperature (bottom), at 55˚C (middle, condensed DNA) and at 70˚C (top, aggregated DNA). The spectra are shifted along Y-axes for clarity.

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7.3. Interaction with Drugs Previous decades gave rise to the extensive studies of the interactions between nucleic acids and various antitumor drugs and antibiotics. Biological activity of the majority of such compounds is based on the interaction with nucleic acids inducing various distortions in their structure, which block the expression of corresponding genes. The mechanisms of these interactions can be different ranging from the intercalation to irreversible coordination groove binding. However, these are the molecular mechanisms of the interactions, which determine the biological functioning of such compounds. Hence, structure sensitive experimental techniques probing biomolecules in their natural environment are the preferred choice for the investigation of the mechanisms of the biological activity of the drugs. Vibrational circular dichroism has been tested recently on the complexes of DNA with daunomycin and cis-diamminedichloroplatinum(II) (Tsankov et al., 2003a; Tsankov et al., 2003b; Pandyra et al., 2006). The latter is a well known antitumor drug cisplatin, whose primary target is thought to be DNA in a cell nucleus (Stros et al., 1994; Rajski and Williams, 1998; Jamieson and Lippard, 1999; Reedijk, 1999; Wong and Giandomenico, 1999; Cohen and Lippard, 2001). Cisplatin is able to form several types of adducts with DNA, involving coordination to N7(G) and N7(A). However, NMR has been the only technique for decades, capable of determining certain structures of the stable adducts. That is why it is still uncertain what happens to the drug in between the injection into the blood stream and the final formation of the adduct. VCD might help to follow the intermediate states (aquatation of the drug; interactions with intermediate carriers; intermediate stages of the interaction with DNA etc.) and the specificity of the final adduct formation. The potential applicability of VCD to these studies was tested by Tsankov et al. on the examples of the interaction of the cisplatin with oligonucleotides (Tsankov et al., 2003a; Tsankov et al., 2003b). In two relatively recent publications the authors have probed the feasibility, accuracy and practical value of VCD for this purpose. In the case of the octamer d(CCTG*G*TCC)•d(GGACCAGG) cisplatin binding induced considerable changes in VCD spectra, which were attributed to the isomerization from an intrastrand to an interstrand crosslink (Tsankov et al., 2003a). The authors pointed out that it was not entirely clear from that particular experiment what structure emerged, but the spectra were affected to a considerable extent in both the base vibration (1750-1500 cm-1) and phosphate vibration (1100-900 cm-1) regions. Specifically, the fourth base step between G4pG5 is connected to platinum via the N7 atoms of guanine where the most prominent changes occurred in the spectra. The absorption and VCD spectra of the same octamer with and without cisplatin were also modeled by ab initio simulations using density functional computations and a Cartesian coordinate-based transfer of molecular property tensors from smaller DNA fragments (Andrushchenko et al., 2007). To determine, whether the spontaneous conversion from an intrastrand to an interstrand oligomer takes place independently of the chain length, similar dodecamer was complexed with cisplatin and studied by VCD (Tsankov et al., 2003b). Of all the differences that were noted by the authors, the most pertinent observation was that the platination effect expressed by the changes in VCD mostly arised from the vibrations of the guanines with the attached platinum atoms, namely G*6 and G*7. Furthermore, the spectra did not indicate any isomerization of the complex, contrary to what was observed for the octamer. Thus it was concluded that VCD was able to contribute to understanding of molecular mechanisms of biological activity of various drugs.

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7.4. DNA-Protein Interactions Functioning of DNA in a living cell is dependent on a great variety of DNA-binding proteins. Nuclear proteins in chromatin interact with DNA, forming intricate protein–DNA complexes. DNA-binding proteins normally co-operate to assemble higher-order nucleoprotein structures, in which multiple protein–DNA and protein-protein contacts increase the specificity and stability of the complexes. Their supramolecular structure is usually determined by the functions they perform in vivo and vice versa. Studying such systems may provide information about conformational changes in DNA and proteins in the complex, about mechanisms of interactions, and about the structural organization of large supramolecular complexes. The great advantage of vibrational spectroscopy is that it allows studying multiple aspects of molecular structure and dynamics. Interpretation of the IR and VCD spectra of DNA-protein complexes is complicated by the fact that the carbonyl and in-plane ring vibrational modes of the bases are partly overlapped with the amide I and II regions of proteins (Figure 18) (Keiderling and Pančoška, 1993; Fabian and Mäntele, 2002; Taillandier and Liquier, 2002). To overcome this limitation one can use a uniform isotopic substitution of carbon atoms in protein molecules. This results in an isotopic shift of amide vibrational modes towards lower frequencies, which will separate them from the vibrations of DNA bases, and will allow one to study structural changes both in DNA and in proteins. The vibrational modes of the sugarphosphate backbone remain clearly distinguishable in the spectra of complexes. The latter provides valuable information about the conformation of nucleic acids in the complex. The interpretation of VCD spectra of such complex systems is a challenging task. However, there were several attempts applying VCD spectroscopy to study DNA-protein complexes exemplified by the complexes of DNA with non-histone chromatin protein HMGB1 and linker histone H1 (Polyanichko et al., 2004; Polyanichko and Wieser, 2005; Polyanichko et al., 2006; Polyanichko and Wieser, 2010). Histone H1 is one of the best studied chromatin proteins (Diez-Caballero et al., 1981; Zlatanova and Yaneva, 1991; Widom, 1998; Travers, 1999; Chikhirzhina and Vorob'ev, 2002). It binds to linker DNA at the entrance or exit of the nucleosome. This interaction takes place through the major groove of DNA and results in DNA-bending around the protein molecule. HMGB proteins are the family of chromatin proteins that contain the structural-functional motif (HMGB1 domain) specific for the High Mobility Group proteins 1 and 2. The abundant members of this family perform structural and various regulatory functions (Bustin and Reeves, 1996; Bustin, 1999; Thomas, 2001; Thomas and Travers, 2001) and are well known for their unusual DNAbinding properties characteristic for the motif (Bustin, 1999). HMGB proteins interact with DNA in its minor groove; they are able to recognize a variety of structural distortions in the DNA double helix and unusual structures such as Holliday junctions (Pohler et al., 1998; Webb and Thomas, 1999; Ohno et al., 2000) and DNA cruciforms (Bianchi et al., 1989; Gariglio et al., 1997). HMGB proteins are also able to induce bends in DNA upon interaction (Bustin and Reeves, 1996; Bianchi and Beltrame, 1998). Although the particular role of these proteins remains unclear, they were assigned mostly structural functions (Segall et al., 1994; Gariglio et al., 1997). Reflecting this ability, they were also called architectural factors of chromatin (Bianchi et al., 1989; Bianchi and Beltrame, 1998; Webb and Thomas, 1999; Ohno et al., 2000; Thomas, 2001).

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Figure 18. VCD (bottom panel) and IR absorbance (top panel) spectra of calf thymus DNA (solid lines) and Histone H1 from calf thymus (dotted line). Overlapping of protein amide I' and DNA carbonyl absorbances can be seen around 1650 cm-1. The strong absorption in DNA spectrum in the range of 1500-1400 cm-1, overlapping with amide II' in the protein spectrum, arises from H-O-D vibrations due to the incomplete deuterium exchange of the sample.

In some cases HMGB proteins act together with other proteins, which function as a part of rather large DNA–protein complexes (Kohlstaedt et al., 1987; Kohlstaedt and Cole, 1994; Baxevanis et al., 1995; Zlatanova and van Holde, 1998; Sutrias-Grau et al., 1999). Protein– protein interactions affect strongly DNA-binding properties of HMGB1 especially in complex

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DNA–protein systems (Polyanichko et al., 2002; Lichota and Grasser, 2003; Zhang et al., 2003; Chikhirzhina et al., 2010). The study of HMGB1-DNA interaction in the presence of histone H1 was performed using a combination of ECD, FTIR, and VCD spectroscopic techniques (Polyanichko and Wieser, 2005). The analysis of the data obtained showed that in the presence of both proteins interaction mainly occurred in the DNA minor groove, which was attributed to HMGB1 binding. Being positively charged, histone H1 facilitated binding of HMGB1 to DNA by interacting with the negatively charged groups of the sugar–phosphate backbone and binding to Asp and Glu amino acid residues of HMGB1. Acting together, HMGB1 and H1 stimulated the formation of supramolecular DNA–protein structures. The structural organization of the ternary complexes depended not only on the properties of the protein–DNA interactions but also on the interactions between HMGB1 and H1 molecules (Polyanichko and Wieser, 2005, 2010). When discussing the mechanisms of DNA–HMGB1 complex formation, it is of interest to consider how the ions of various metals influence DNA–protein interactions, a question that is little understood despite its importance for HMGB1–DNA interactions (Yoshida, 1983; Stros et al., 1990; Stros et al., 1994; Bottger et al., 1998; Haberland et al., 1999; Lucius et al., 2001). The results of VCD experiments not only confirmed the high level of structural order in DNA/HMGB-domain complexes but also suggested somewhat unexpected conclusions concerning the role of calcium ions in DNA compaction in its complexes with the HMGB1 protein (Polianichko et al., 2004). The detailed analysis of FTIR, VCD, and ECD spectral features of the complexes revealed that the presence of Ca2+ inhibited the formation of compact structured DNA–protein complexes. Apparently calcium ions in similar systems are not involved in additional DNA structuring but, on the contrary, serve as a limiting factor of such processes. Speaking about supramolecular organization of the DNA-protein complexes we mentioned the limited abilities of other structurally sensitive spectroscopic techniques, such as ECD, and here becomes apparent another advantage of the VCD approach. As we discussed earlier in this chapter, VCD allows studying much larger complexes than UV or visible spectroscopy does. There is no other spectroscopic technique currently available, which is readily applicable to such systems. Although the interpretation of VCD spectra of complex systems is not a straightforward procedure yet, we believe that the rapid development of theoretical and calculational approaches will considerably improve the situation.

8. THEORETICAL CALCULATIONS AND SPECTRA PREDICTION 8.1. Background In the previous sections of this chapter we demonstrated the whole array of the experimental applications of VCD spectroscopy to various biomolecular studies during the last two decades or so. However, as it was emphasized earlier, while VCD spectra provide significantly richer information about molecular structure and interactions than ECD spectra, they are also more complex and difficult for empirical interpretation due to a large number of often overlapped bands. Thus, an urgent need for proper spectra interpretation has emerged

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along with practical applications of VCD. Indeed, establishing relationship between spectra and molecular structure can provide insights not only into the structure, but also into other molecular properties such as conformational behavior, interaction with the solvent and other molecules, or even biological activity (Hamm et al., 1995; Hick, 2002). Historically, mostly empirical assignments of spectral features have been initially performed. However, despite the vast information gathered up to date about the IR absorption band assignments for nucleic acids, some of them are ambiguous or missing due to natural broadening of the spectral lines, band overlap, coupling and mixing of the vibrations of different functional groups (Tsuboi, 1969; Taillandier et al., 1985). Even less information is available about the assignments of VCD bands (Keiderling, 1996; Andrushchenko et al., 2003a). Considering the limitations of empirical assignments, significant attention has been put towards theoretical computations of VCD spectra. Fortunately, because vibrational transitions occur within the ground state of the molecule, it becomes more straightforward to perform VCD computations compared to ECD. In addition to simplifying the VCD spectra assignment, such calculations can also provide extensive information on the energetics of different conformers and other properties of the studied systems, obtained from the first principles. First attempts to perform VCD simulations were based on empirical and semiempirical models, such as the coupled oscillator (CO) model (Tinoco, 1963; Holzwarth and Chabay, 1972; Gulotta et al., 1989; Zhong et al., 1990; Xiang et al., 1993; Wang et al., 1994b). Later, extensions of the CO model were developed, such as the DeVoe polarizability theory (Devoe, 1965, 1971; Self and Moore, 1997, 1998). Despite the relative simplicity, the empirical models were helpful in assigning some of the VCD features in nucleic acid spectra, and could provide a basis for their understanding. However, such an approach was mainly limited to the C=O stretching region, was not applicable generally, and provided only very basic and simplistic information about the system. Since the development of the theory of VCD computations by Stephens (Stephens, 1985) it became obvious that ab initio-based calculations could become a more reliable and universal tool providing in-depths details on the systems under study. Possibility and advantages of the ab initio calculations of VCD spectra have been first recognized and pioneered by Stephens (Kawiecki et al., 1991) and Polavarapu (Polavarapu et al., 1991) soon after the theory of VCD phenomenon has been developed. Generally, with the aid of ab initio spectral calculations, assignments of the vibrational transitions can be performed, overlapped bands can be resolved, and the extent of the vibrational coupling can be determined. Furthermore, the first principle computations also enable prediction of spectra for unknown structures, allow to obtain insight into the nature of interactions with other molecules and solvent, and to estimate energetically favorable conformations. In order to calculate VCD frequencies and intensities within the harmonic approximation, the following molecular property tensors have to be computed (Stephens, 1985): i.

force constants (Hessian, second derivatives of energy):

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∂2E fiα, jβ = ∂riα∂rjβ (6) ii.

atomic polar tensor (dipole derivatives):

Pα ,iβ = iii.

(7)

atomic axial tensor (magnetic dipole derivatives):

Aα ,iβ =

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∂μα ∂riβ ∂mα ∂piβ

(8)

The force constants f are related to two atoms (i, j), while the tensors A and P can be thought of as properties of individual atoms i with positions ri and momenta pi. Due to the advances in computer technologies and ab initio methodology, simulations of VCD spectra within the harmonic approximation for small rigid molecules became relatively straightforward and implemented in a number of quantum chemistry software packages, such as Gaussian (Devlin et al., 2002a), ADF (Baerends et al., 2010), Dalton (Angeli et al., 2005). All these implementations are based on the magnetic field perturbation theory (MFP) of Stephens (Stephens, 1985) combined with density functional theory (DFT) and fielddependent (gauche invariant) atomic orbitals (GIAO) (Cheeseman et al., 1996). Applications of VCD spectral simulations for small molecules have been very successful. In combination with experimental VCD spectra absolute configurations could be determined without the need for much more expensive and time-consuming techniques (e.g., X-ray diffraction) (Freedman et al., 2003; Petrovic and Polavarapu, 2007; Stephens et al., 2008; Abbate et al., 2009; Uncuta et al., 2009). However, the size and conformational flexibility of biopolymers significantly impedes the direct ab initio modeling of VCD spectra. In some cases, suitably chosen fragments of large biopolymers can provide enough information on a local structure and main spectral features of the molecule due to locality of the VCD phenomenon (Bouř and Keiderling, 1993; Birke and Diem, 1995; Silva et al., 2000). In general, more universal methods are required, allowing to reliably model spectra for the whole biopolymer without loosing the accuracy of the ab initio approach. The Cartesian coordinate tensor transfer (CCT) techniques discussed below were developed for this purpose (Bouř et al., 1997), as they allow to transfer the most common molecular property tensors (force field, dipole derivatives, atomic axial tensors) from smaller fragments to larger biomolecules. The transfer in Cartesian coordinates (including translations and rotations) is computationally easier and requires less human input

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than with non-linear internal coordinates. This technique allows expanding relatively accurate ab initio spectral simulations to large molecules, with several thousands of atoms. It has been successfully applied for simulations of VCD spectra of polypeptides (Silva et al., 2000; Bouř et al., 2002a) and nucleic acids (Andrushchenko et al., 2002b, 2004; Bouř et al., 2005; Andrushchenko et al., 2007). In the following we will briefly describe the methodological approach and present a few examples of VCD spectra calculations for different nucleic acid structures using the CCT method. Computations of polypeptide spectra are generally done according to the similar algorithm and therefore will not be described here. More thorough review devoted to this computational approach can be found elsewhere (Andrushchenko and Bouř, 2010).

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8.2. Overview of the Methodology The overall procedure used in the Cartesian coordinate tensor transfer technique consists of splitting of a large molecule into fragments, ab initio calculation of atomic tensors for all the fragments, and a following transfer of the tensors back to the original large molecule. This procedure allows avoiding a direct ab initio spectra simulation for the whole large molecule, which may not be feasible at the present state of the computational technologies. It has been shown that if the fragments are properly chosen, the CCT method provides IR absorption and VCD spectra virtually indistinguishable from the fully ab initio results (Kubelka, 2002). The method is based on the mentioned earlier locality of the VCD phenomenon (Birke and Diem, 1995), however it also allows to include some long-range interactions. Utilization of this technique also enables parallelization of the computational tasks, which further speeds up the spectra modeling. The typical steps used in CCT technique are shown in Figure 19 on the example of an arbitrary octanucleotide. The original structure of the octamer (or any other oligomer) is either an X-ray or NMR structure, usually obtained from Protein Data Bank (PDB). If such a structure is not available and it represents a canonical A- or B-form nucleic acid conformation, the starting geometry can be generated by molecular modeling packages, e.g. Insight II (formerly Biosym; now part of Discovery Studio) (1995; 2001-2009), Tinker (Ponder, 2000), Amber (Case et al., 2006) etc. Such a canonical structure for the B-form of an octamer duplex is exemplified in Figure 20a. The octamer structure is split into fragments (Figure 20b and Figure 20c, also schematically represented as blocks in Figure 19), large enough to preserve the important for VCD short-range interactions, but still manageable for direct ab initio computations at sufficiently high level of theory. The VCD signal in nucleic acids mainly arises from the dipolar interaction between two stacked base pairs and analogous interactions of the phosphate and sugar residues of the backbone (Zhong et al., 1990; Birke and Diem, 1995). Therefore, the basic ―optical‖ unit in a nucleic acid, determining the basic VCD pattern, typically consists of two stacked base pairs (Figure 20b) and two sugarphosphate pairs (Figure 20c). Considering this, the fragments would contain one or more of such basic units.

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Figure 19. Schematic representation of the Cartesian coordinate tensor transfer (CCT) technique as applied to a DNA octanucleotide. Separate fragments used for ab initio calculations are shown as blocks. Letters inside the blocks correspond to: G - guanine, C - cytosine, A - adenine, T – thymine, S – sugar moiety, P – phosphate group. The transfer is done in the following steps: a) target octamer is split into fragments for ab initio calculations, initially its atomic tensors are filled with zeroes (white areas); b) atomic tensors describing some of the inter-base interactions computed ab initio for the stacked base pair dimer fragments are transferred to the target octamer (orange blocks); c) missing inter-base pair interactions (white areas between orange blocks in figure ―b‖) are added by transferring tensors for three more base pair dimers (shaded green blocks), covering all inter-base pair interactions; d) atomic tensors computed ab initio for the sugar-phosphate dimers are transferred to the target octamer (blue blocks); e) missing sugar-phosphate interactions are added by transferring six more sugar-phosphate dimers (shaded violet blocks). Only interactions between the bases and the sugar-phosphate backbone are omitted (white areas in figure ―e‖) as they are less important for the spectra simulations, but they may also be included as needed by a set of additional ab initio computations of the whole nucleotide fragments.

Figure 20. Canonical B-form of GGACCAGG duplex octamer used as target template for atomic tensor transfer (a); geometry of a stacked base pair dimer fragment (TA)*(GC) (b); geometry of a sugarphosphate dimer (c).

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As a next step, the fragments are optimized at an ab initio level using available quantum chemistry packages, e.g. Gaussian (Devlin et al., 2002a). The optimization is required to relax the initial geometry and bring it close to an energy minimum. This must be done because frequency calculations within the harmonic approximation are meaningful only for such minimum (equilibrium) geometries (Devlin et al., 2002a). During the unrestricted optimization the initial conformation found in the X-ray, NMR, or canonical structure might be distorted, thus producing unrealistic results. One way to prevent such larger geometrical changes of the fragments during the optimization is to constrain all torsion angles in a fragment as well as the distances between the bases and their mutual orientation in a base pair. Usually freezing of the torsion angles mainly affects low frequency modes outside the experimentally accessible range of interest. At the same time, bond lengths and angles mostly contributing to the higher-frequency mid-IR spectral range are allowed to relax. However, such constrains often may not allow for a complete relaxation of the higher-energy smallamplitude movements. Alternatively to the geometrical constrains, more gentle normal mode optimization (NMO) method can be utilized (Bouř and Keiderling, 2002b). With this method, only the normal modes with the lowest frequencies (typically   (-300, 300 cm-1) where imaginary frequencies are considered as negative) are frozen. These modes are mostly connected with torsional, rotational and translational movements of large groups of atoms, and usually do not contribute to measurable spectral range. At the same time, the higher frequency vibrational motions observable in experimental spectra are relaxed completely, unlike for the intrinsic coordinate constraining. In such implementation the NMO procedure typically causes only a minimal change of the fragment geometry. An additional advantage of the NMO method is a much faster and more stable convergence for optimization of noncovalently bound systems, such as, e.g., nitrogen bases in DNA or water clusters (Bouř, 2002c; Bouř, 2005). The range of the fixed normal modes can be chosen arbitrarily or a complete relaxation of the geometry can be performed in order to use the technique for a complete optimization of weakly interacting molecules. DFT electronic methods can be conveniently used for the quantum chemical computations, combined with a sufficiently large basis set including polarization and, preferably, diffuse functions. For the optimized fragments the harmonic force field and intensity tensors are usually calculated at the same level of theory as that used for the optimization. All tensors from each fragment are then transferred in Cartesian coordinates to the original octamer (target structure), atom by atom according to the published procedure (Bouř et al., 1997) (Figure 19), using standard translation and rotation transformations. The transfer (rotation and translation) is defined by minimizing a root-mean square overlap of chemically similar atoms in the fragments and in the target molecule.(Bouř et al., 1997) As a result, the initial zero octamer tensors (white areas inside the blocks in Figure 19a) are replaced atom by atom with the tensors from the fragments computed at ab initio level (colored areas in Figure 19bFigure 19e). In this way the inter-base pair, sugar-sugar and phosphate-phosphate interactions for the neighboring fragments in the whole octamer are accounted for. In the procedure depicted in Figure 19 only interactions between the bases and the sugar-phosphate backbone remain omitted (remaining white areas in Figure 19e). However, they may also be included as needed by a set of additional ab initio computations of the whole nucleotide fragments.

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From the transferred molecular properties (tensors), the IR absorption and VCD spectra are computed for the whole target structure. Usually, realistic spectra are simulated by the convolution of calculated intensities with Lorentzian bands ranging from 5 to 10 cm-1 in width. Considering that experimental VCD spectra of nucleic acids are usually measured in D2O, spectra of deuterated species are simulated by replacing of all the acidic hydrogens in the molecule by deuteria, which does not require an extra electronic calculation.

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8.3. Examples of Nucleic Acid VCD Spectra Modeling The natural conformation of DNA is a right-handed B-form double helix (Figure 20a and Figure 21b) (Watson and Crick, 1953). However, some conditions, e.g. high amounts of metal ions or ethanol, can lead to a B to Z conformational transition in DNA fragments rich with alternating (dG-dC)n sequences (Figure 21c) (Pohl and Jovin, 1972). Let alone the biological importance of Z-form DNA, such a transition is especially interesting from the point of view of chiral spectroscopic methods. While the B-form represents a right-handed helix, the Z-form is a left-handed helix. Opposite helical sense results in a different arrangement of the chromophores and different coupling between them. It has been observed, that the opposite helicity leads to the opposite sign of the circular dichroism signal (both ECD and VCD) for the two conformations (Pohl and Jovin, 1972; Gulotta et al., 1989). Hence, different handedness of the DNA helix is analogous to the enantiomer symmetry in small molecules with respect to CD spectroscopy. This phenomenon has been also interesting from the theoretical point of view as a way to verify the proposed VCD models and methods for VCD spectra calculations, as well as to gain a better insight into the origin of VCD. The empirical coupled oscillator model could faithfully reproduce the opposite VCD couplet sign for B- and Z-forms of DNA (Gulotta et al., 1989). It was also a good starting point to check the applicability of CCT technique for computing nucleic acid spectra, as this method has been originally tested only on polypeptide systems (Silva et al., 2000; Bouř et al., 2002a). The spectra of (dG-dC)4 octamer (Andrushchenko et al., 2002b), computed employing CCT approach are compared to the experimental spectra of (dG-dC)20 (Andrushchenko et al., 1999) in Figure 21a. It has been shown that experimental VCD spectra of (dG-dC)4, (dGdC)20 and poly(dG-dC) are essentially the same, which makes such a comparison valid (Gulotta et al., 1989; Maharaj et al., 1995; Andrushchenko et al., 1999). The corresponding B- and Z-form structures of (dG-dC)4 octamer are shown in Figure 21b and Figure 21c, respectively. Both the experimental and the computed spectra are dominated by VCD features arising from the C=O stretching vibrations of guanine bases (Andrushchenko et al., 1999; Andrushchenko et al., 2002b). The experimental spectrum of B-form shows a positive VCD couplet at 1691(-)/1678(+) cm-1, which changes to the negative one at 1671(+)/1656(-) cm-1 upon the B-Z transition. The computed spectrum of the B-form octamer also exhibits a positive VCD couplet at 1710(-)/1695(+) cm-1, while in the calculated spectrum of Z-form the main couplet flips the sign to negative at 1707(+)/1693(-) cm-1. Thus, the CCT method, based on the quantum chemical description of the VCD phenomenon, could correctly reproduce the experimentally observed change in the VCD signal for right- and left-handed helical polymers.

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Figure 21. Calculated VCD spectra of B- and Z-forms of (dG-dC)4 octamer compared with the corresponding experimental spectra of (dG-dC)20 (a); structures of (dG-dC)4 in B-form (b) and Z-form (c) used for the calculations. No scaling has been used for the computed spectra.

Another representative example of the CCT method application for nucleic acid VCD spectra modeling could be a single-stranded (rA)8 RNA octamer. Due to high aromaticity of adenine bases and their strong stacking, single-stranded oligo- and poly(rA) molecules can form a relatively stable helical structure in solution in the presence of metal ions, neutralizing the phosphate negative charges (Saenger, 1984). The presence of a helical structure in poly(rA) was observed experimentally by a strong VCD signal (Yang and Keiderling, 1993; Andrushchenko et al., 2002a; Petrovic and Polavarapu, 2005). Computationally, modeling for single-stranded nucleic acids is less demanding than for double-helical structures as the fragments used for ab initio calculations have smaller size.

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Figure 22. Calculated VCD (top panel) and IR absorption (bottom panel) spectra of (rA) 8 compared with the corresponding experimental spectra of poly(rA) (a); structure of (rA)8 single stranded octamer used for the calculations (b). No scaling has been used for the computed spectra.

The computed IR and VCD spectra of (rA)8 (Andrushchenko et al., 2004) and the corresponding experimental spectra of poly(rA) (Tsankov, 2001, unpublished results) are shown in Figure 22 together with the structure of the computed system. The most intense VCD feature in the experimental spectrum is a positive couplet at 1633(-)/1623(+) cm-1, corresponding to IR absorption band at 1627 cm-1 arising from the adenine ring vibrations (Tsuboi, 1969; Ohms and Ackermann, 1990; Yang and Keiderling, 1993; Andrushchenko et al., 2002a). This couplet is closely reproduced by the computations in terms of both the band shape and the position as it appears at 1620(-)/1612(+) cm-1. The computed IR absorption band at 1617 cm-1 also reproduces well the experimental band at 1627 cm-1. Moreover, even weaker experimental IR absorption at 1572 cm-1 is faithfully modeled at 1574 cm-1, also originating from the adenine ring vibrations. The corresponding to this absorption negative VCD band is calculated at 1574(-) cm-1, however the experimental VCD signal arising from this absorption although can be suggested at 1572(-) cm-1, is significantly impeded by the high noise level in the experimental spectrum. Good agreement between the computed and the experimental spectra in the nitrogen base vibrational region at around 1500-1600 cm-1 is due to high aromaticity of the adenine base and its hydrophobicity, demonstrating relatively insignificant effect of the solvent on the adenine ring vibrations. Furthermore, strong stacking

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interaction between adenine bases reduces their flexibility and the solution structure closely resembles the geometry obtained by crystallographic methods. Strong influence of the solvent on the computed wavenumbers of highly susceptible to solvent interaction carbonyl groups is demonstrated in the next example, which deals with the spectra simulations for double-stranded RNA octamer (rA)8*(rU)8. The computed VCD and IR absorption spectra of (rA)8*(rU)8 (Andrushchenko et al., 2004) are compared with the corresponding experimental spectra of poly(rA)*poly(rU) (Andrushchenko et al., 2002a) in Figure 23a, the structure of the modeled system is shown in Figure 23b.

Figure 23. Calculated VCD (top panel) and IR absorption (bottom panel) spectra of (rA) 8 compared with the corresponding experimental spectra of poly(rA)*poly(rU) (a); structure of (rA)8*(rU)8 double stranded octamer used for the calculations (b). No scaling has been used for the computed spectra.

As in the above example, agreement between the computed and the experimental IR and VCD features arising mostly from the adenine ring is fairly good due to the same reasons. Thus, the experimental absorption at 1631 cm-1 is calculated at the close wavenumber of 1633 cm-1. The corresponding positive VCD couplet at 1635(-)/1623(+) cm-1, although overestimated in intensity, is faithfully reproduced by the computations at 1636(-)/1628(+) cm-1. However, the fine agreement starts to deteriorate as more environmentally susceptible uracil base gets involved. The experimental absorption band at 1669 cm-1, attributed to the C(4)=O vibrations of uracil is computed at 1696 cm-1, and thus shifted by about 25 cm-1 to higher wavenumbers. The corresponding positive VCD couplet measured at 1677(-)/1665(+) cm-1 appears in the calculated spectrum at 1697(-)/1690(+) cm-1, also shifted to higher wavenumbers in concert with the parental absorption. The deviations with the experiment are even larger for the C(2)=O spectral features. The absorption band occurs experimentally at

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1689 cm-1 with a weak negative VCD band at 1705 cm-1, but it is calculated at 1740 cm-1 with the corresponding VCD band of opposite sign at 1740 cm-1. The described difficulties in modeling of stretching vibrations for highly polar groups, such as C=O, arise because of substantial influence of solvent on the vibrations of these groups. For the carbonyl groups involved in the hydrogen bonding with another base (e.g., C(4)=O of uracil in this example) the solvent influence is weaker, which results in fair modeling. However, if the carbonyl group is fully accessible by the solvent (such as C(2)=O of uracil), its influence on the vibrational modes becomes dominant and the calculations without explicit or at least implicit hydration models produce unrealistic results. Our test computations on a single A···U base pair with the simplest accounting for the explicit solvent resulted in downshift of the C(2)=O band as much as 25 cm-1 (Andrushchenko et al., 2004). Unlike in the previous examples, relatively good agreement is also observed in the sugarphosphate region of the spectra between 1200 and 1000 cm-1 (Figure 23a). This documents the advantage of the NMO method as opposed to the geometrical constrains of the torsion angles, which was used for the B- and Z-form spectra simulations. Furthermore, this result also suggests higher rigidity of the sugar-phosphate backbone in the duplex as compared to the single-stranded system. In the above examples we have shown how the spectra of known nucleic acid structures can be modeled and how the calculated spectra relate to the experimental ones. But is it possible to gain any information about unknown structures combining VCD experiment with the calculations? As it was mentioned before, a combination of the experimental VCD spectroscopy with the ab initio computations was very successful for determination of the absolute configuration of small molecules, which could in many cases replace the more resource demanding X-ray crystallography. Unfortunately, at the present state of the computational technologies such a precise structural determination is not possible for large biopolymers. However, the spectra modeling combined with the experiment can help to gain insight into many structural features of large molecules. One of such examples shows a dependence of the VCD signal pattern on the helical twist angle of (CGC)*(GCG) base pair trimer (Bouř et al., 2005) and is demonstrated in Figure 24. The deviations ranging from -50 to +200 from the canonical B-form helical twist angle 0 (see Figure 24b for the helical twist angle definition), were introduced to (CGC)*(GCG) trimer. The VCD and IR absorption spectra for different values of the helical twist angle are compared with the corresponding experimental spectra of (dC-dG)4 octamer (Maharaj et al., 1995) in Figure 24a. It is seen that the structure with the deviation of +200 from the canonical twist angle shows the best agreement of the simulated spectra with the experiment ones. This gives a hint that the actual solution geometry of the (dC-dG)4 octamer, for which the experimental VCD spectra were obtained, might deviate from the crystallographycally derived canonical B-DNA structure, with its central part more twisted than in the crystal structure. While the precision of such simulations is limited and the conclusions drawn might be somewhat speculative, this example illustrates the possibilities open for the combined VCD experimental-computational approach in structural studies of large biopolymers.

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Figure 24. Calculated VCD (right panel) and IR absorption (left panel) spectra of (CGC)*(GCG) base pair trimer computed for different deviations from the canonical B-form helical twist angle 0 compared with the corresponding experimental spectra of (dC-dG)4 octamer (Maharaj et al., 1995) (a); structure of (CGC)*(GCG) trimer used for the calculations with a definition of the helical twist angle  (b).

In this section of the chapter we outlined the current state of the art methodology, which we were using for computations of VCD spectra of large biopolymers. We tried to give a feel how accurate the computations of VCD spectra of nucleic acids can be, what to expect from such calculations, and what kind of difficulties can be faced. The CCT methodology described is being constantly improved and developed in our laboratory in Prague. Recently, we have extended the approach to be able to include both solvent and dynamical effects, which significantly improved the computed results and their agreement with the experimental data.

CONCLUSION VCD is a relatively new spectroscopic technique. However, during the last decade it has undergone rapid instrumentational and theoretical development, so that it quickly maturated and became an efficient analytical tool available to study the chirality of both small molecules and macromolecules. VCD has proven to be applicable also for studying of large complexes and more complicated biological and physical-chemical systems. In our opinion, the popularity of the technique will further increase in the coming years. This in turn will facilitate its further development, e.g. more sensitive or time-resolved measurements. Commercial VCD spectrometers (now available from BioTools Inc., Brucker Optics Inc. and

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JASCO International Co., Ltd.) will likely become as common as ECD instruments in many laboratories. The instrumental development is very tightly coupled with the VCD interpretation tools, based primarily on combined molecular dynamics and quantum mechanics computations. VCD facilitates the investigation of biological macromolecules in different physicalchemical conditions, such as ionic strength, pH, different solvents as well as in solid state. The method provides rich structural information not only about conformations in general, but also about orientations and interactions among different parts of macromolecules, and particular chemical groups within them. Aside from these advantages, there are obviously many limitations. In any case, the best approach is to use a combination of several complementary techniques rather than look for a perfect single one. Sometimes VCD is able to provide unique results, but in most cases VCD is a good source of additional information, which might not be available from other types of experiments.

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ACKNOWLEDGMENTS We would like express our deep gratitude to Dr. M. Urbanová for valuable discussions. The authors gratefully acknowledge the financial support from the Russian Foundation for Basic Research (grant 12-08-01134), The Government of St. Petersburg, Federal program, ‘Scientific and pedagogical labour force for an innovative Russia’ (A.M. Polyanichko); from the Alberta Heritage Foundation for Medical Research (AHFMR, Canada), Institute of Organic Chemistry and Biochemistry (IOCB, Czech Republic) and the Grant Agency of the Czech Republic (grant P208/10/0559) (V.V. Andrushchenko); from the Academy of Sciences of the Czech Republic (grants M200550902 and IAA400550702) (P. Bouř), and from the Natural Sciences and Engineering Research Council (NSERC) of Canada (H. Wieser). Reviewed by Dr. Marie Urbanová

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Wang, D.; Lippard, S. J. Nat Rev Drug Discov 2005, 4, 307-320. Wang, L.; Keiderling, T. A. Biochemistry 1992, 31, 10265-10271. Wang, L.; Keiderling, T. A. Nucleic Acids Res. 1993, 21, 4127-4132. Wang, L.; Pančoška, P.; Keiderling, T. A. Biochemistry 1994a, 33, 8428-8435. Wang, L.; Yang, L.; Keiderling, T. A. Biophys. J. 1994b, 67, 2460-2467. Watson, J. D.; Crick, F. H. C. Nature 1953, 171, 737-738. Webb, M.; Thomas, J. O. J. Mol. Biol. 1999, 294, 373-387. Widom, J. Annu. Rev. Biophys. Biomol. Struct. 1998, 27, 285-327. Wong, E.; Giandomenico, C. M. Chem. Rev. 1999, 99, 2451-2466. Xiang, T.; Goss, D. J.; Diem, M. Biophys. J. 1993, 65, 1255-1261. Xie, P.; Diem, M. Appl. Spectrosc. 1996, 50, 675-680. Yamagata, A.; Kakuta, Y.; Masui, R.; Fukuyama, K. Proc. Natl. Acad. Sci. U. S. A. 2002, 99, 5908-5912. Yang, L.; Keiderling, T. A. Biopolymers 1993, 33, 315-327. Yasui, S. C.; Keiderling, T. A. J. Am. Chem. Soc. 1986, 108, 5576-5581. Yasui, S. C.; Keiderling, T. A.; Bonora, G. M.; Toniolo, C. Biopolymers 1986a, 25, 79-89. Yasui, S. C.; Keiderling, T. A.; Formaggio, F.; Bonora, G. M.; Toniolo, C. J. Am. Chem. Soc. 1986b, 108, 4988-4993. Yasui, S. C.; Keiderling, T. A.; Katakai, R. Biopolymers 1987, 26, 1407-1412. Yoder, G.; Pančoška, P.; Keiderling, T. A. Biochemistry 1997, 36, 15123-15133. Yoshida, M. Biochem. Biophys. Res. Commun. 1983, 116, 217-221. Young, D. A.; Lipp, E. D.; Nafie, L. A. J. Am. Chem. Soc. 1985, 107, 6205-6213. Young, D. A.; Freedman, T. B.; Nafie, L. A. J. Am. Chem. Soc. 1987, 109, 7674-7677. Zhang, S. B.; Huang, J.; Zhao, H.; Zhang, Y.; Hou, C. H.; Cheng, X. D.; Jiang, C.; Li, M. Q.; Hu, J.; Qian, R. L. Cell Res. 2003, 13, 351-359. Zhong, W. X.; Gulotta, M.; Goss, D. J.; Diem, M. Biochemistry 1990, 29, 7485-7491. Zhu, F. J.; Isaacs, N. W.; Hecht, L.; Barron, L. D. Structure 2005, 13, 1409-1419. Zlatanova, J.; Yaneva, J. DNA Cell Biol. 1991, 10, 239-248. Zlatanova, J.; van Holde, K. BioEssays 1998, 20, 584-588.

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In: Circular Dichroism: Theory and Spectroscopy ISBN: 978-1-61122-522-8 c 2012 Nova Science Publishers, Inc. Editor: David S. Rodgers

Chapter 3

M AGNETIC C IRCULAR D ICHROISM IN E LECTRON M ICROSCOPY J´an Rusz1,∗, Stefano Rubino2, Klaus Leifer2 , Hans Lidbaum2 , Peter M. Oppeneer1 , Anders Johansson1 and Olle Eriksson1 1 Department of Physics and Astronomy, Uppsala University, Box 516, SE-75120 Uppsala, Sweden 2 Department of Engineering Sciences, Uppsala University, Box 534, SE-75121 Uppsala, Sweden

Abstract

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Magnetic circular dichroism experiments are traditionally a domain of the photon or x-ray physics. Particularly, x-ray magnetic circular dichroism (XMCD) experiments are an invaluable tool for obtaining the element-specific spin and orbital moments of studied samples. Until recently, there was no known equivalent of XMCD in the electron microscope. However, Schattschneider et al. [1] have demonstrated that it is possible to observe an analogous effect in electron energy loss spectra in a transmission electron microscope. A rapid development of the method has followed. Shortly after the discovery of this phenomenon named electron magnetic circular dichroism (EMCD) a first-principles theory has been formulated [2] and a set of sum rules has been derived [3, 4]. EMCD sum rules allow extraction of the spin and orbital moments in a way similar to their XMCD counterparts. On the experimental side, the spatial resolution was gradually improved from 200 nm in the prototype experiment, through 30 nm [5, 6] down to 2 nm [7] using converged electron beams. Different experimental geometries have been implemented as well, providing alternative methods of recording a full datacube of energy, spatial and/or angular parameters. The first quantitative EMCD experiment using sum rules was reported by Lidbaum et al. [8]. Recent focus has been directed towards fine-tuning the quantitative EMCD experiments, studying the influence of the plural scattering of probe electrons on the extracted orbital-to-spin moment ratios. The first measurements of the EMCD in the image mode are reported—they should allow in the future to observe spatial variations of atom-specific moments. Finally, progresses in simulations and theory of the ∗

E-mail address: [email protected]

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Jan Rusz, Stefano Rubino, Klaus Leifer et al. EMCD effect are described. Active research is devoted to the development of the EMCD technique into a routine complementary tool to XMCD with an advantage of bulk sensitivity and superior spatial resolution.

Keywords: circular dichroism, transmission electron microscope, dynamical diffraction, electron energy loss spectroscopy, magnetism, sum rules

1.

Introduction

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Olle Eriksson The development of novel methods which allow for the characterization of magnetic materials has been an active research area for the past decades. Among the more recently established techniques, one may identify spin-polarized scanning tunneling microscopy (SPSTM) [9], where it is possible to probe the magnetic moment of single atoms adsorbed on a surface [10]. No other experimental technique can display the same spatial resolution, when it comes to magnetization measurements. Another recently developed experimental technique is x-ray magnetic circular dichroism (XMCD) [11, 12], which has the unique feature that it provides element specific information. Hence, unlike SP-STM, it is possible to measure the spin- and orbital moments of each element among a mixture of atomic species. There have until now been several thousands of reports on the usage of the XMCD technique, enabling valuable information about the magnetism (spin and orbital moment, as well as magnetic anisotropy) of magnetic nano-objects like spin-valves, GMR- (giant magneto resistance) and TMR (tunneling magneto resistance) devices, magnetic thin-films and multilayers [13]. The use of the XMCD technique relies heavily on theoretical analysis, especially the so called sum rules [14, 15], which allow to draw conclusions about the spin- and orbital moments via an analysis of an experimental dichroic signal. Unfortunately XMCD is not directly a useful tool for antiferromagnetic materials, since the dichroic signal is absent for such systems. However, using the (much weaker) dichroic signal of x-ray magnetic linear dichroism (XMLD) [16, 17] it is possible to get element specific information also about antiferromagnets. Hence, it is now possible to detect details of a magnetic material which a few years back was unforeseeable. However, among the drawbacks of the XMCD and XMLD techniques one easily identifies the poor spatial resolution they provide, as well as the need for an enormously expensive and bulky synchrotron radiation facility. The possibly most recent experimental and theoretical breakthrough, in the development of novel experimental tools for magnetic materials, is the EMCD (electron magnetic circular dichroism) technique [1]. Here the dichroic signal of electron energy-loss spectra (EELS) is used for detecting a magnetic signal in the sample. The advantages of this technique is that it requires a relatively cheap instrument; a transmission electron microscope. Furthermore, the spatial resolution is one or two orders of magnitude higher compared to XMCD/XMLD, and it is a less surface sensitive probe. There are obvious similarities between EMCD and XMCD. For instance, both rely on electronic excitations from core states to unoccupied valence states. Hence, both methods enable detection of element specific information. In addition, both methods require accurate theoretical models, in the form of sum rules, which for EMCD were derived in Ref. [3] and in an independent work in

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Ref. [4]. A recent study [8] demonstrated that it is possible to determine accurately the ratio of spin- and orbital moments of bcc Fe using these sum rules in combination with EMCD measurements. In EMCD, the measurement of a dichroic signal is made possible by detecting two angle-resolved electron energy-loss spectra, which are subtracted from each other. The two scattering angles, are chosen to be symmetric around a mirror axis. Furthermore, the sample is used to split the incoming beam of electrons, via Bragg diffraction, to two coherent waves with a phase shift of π/2. This is achieved by tilting the sample. Hence, geometrical conditions are important for the EMCD experiment, and this is one of the experimental challenges with this method. This chapter describes the current status of the EMCD technique, including details of the experimental challenges it carries, as well as the theoretical foundation behind the sum rules. The latter involves a detailed analysis of dynamical diffraction theory. The EMCD technique is still young, and it is foreseeable that several developments and improvements will be reported in the next decade or so, making it a mature technique with which element specific information of a magnetic material may be obtained routinely. Due to the excellent spatial resolution, one may envision the detection of local effects resolving information in a nano-meter scale. Hence it is in principle possible to use EMCD to study domain wall pinning around dislocations, enhancement of spin- and orbital moments at defect structures and at internal interfaces of a material. A fully matured EMCD technique could possibly provide detailed information of the magnetism inside a material, at length scales not possible with other methods.

2.

Magnetic Circular Dichroism

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Peter Oppeneer

2.1.

The X-ray Magnetic Circular Dichroism – A Brief Overview

The interaction of polarized light with a magnetic material was observed for the first time one hundred fifty years ago [18]. Through subsequent investigations over many decades it has been revealed that the light-magnetic material interaction can be detected in various ways. One of the possible manners is the polarization-dependent absorption of polarized light in a magnetic medium, which has become known as magnetic dichroism [19]. The most common form is the magnetic circular dichroism (MCD), which is detected using circularly polarized light. MCD in the visible energy regime is nowadays routinely used to study, e.g., metal-organic materials. The possibility that an analog of the MCD could exist in the x-ray regime has been considered first one hundred years ago [20, 21]. However, at that time it was not yet possible to observe a notable dependence of the x-ray absorption on the lights polarization. Much later, Erskine and Stern [22] performed a first theoretical study on the size of the x-ray magnetic circular dichroism (XMCD) in ferromagnetic Ni, assuming that the energy of the x-ray radiation could be tuned to the M2,3 absorption edge (i.e., considering transitions from the 3p core levels to 3d valence states). Erskine and Stern estimated a detectable XMCD effect and predicted that XMCD could be used to obtain the spin-polarization of the unoccupied 3d states, i.e., provide information on the atomic spin moment. The very first experimental observation of an interaction between

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x-ray radiation and a magnetic material was made in 1985 by Namikawa et al. [23], who observed the influence of the magnetization of Ni in hard x-ray scattering at the Ni K-edge. The first observation of x-ray magnetic dichroism was reported by Van der Laan et al. [11], who observed an absorption change of linearly polarized x-rays at the M5 edge of a Tb-Fe garnet. A first x-ray magneto-optical Kerr effect measurement was reported by Bonarski and Karp [24]. The first XMCD study was performed by Sch¨utz et al. [25], using hard xrays to probe the Fe K-edge. The observed XMCD was rather small, of the order of 10−4 , therefore it did not appear to be an appealing technique for the investigation of magnetic materials. This situation changed however just a few years later, when Chen et al. [26, 27] demonstrated that appreciable XMCD signals of the order 10%-15% could be obtained at the L-edges of ferromagnetic transition metals, i.e., at the prominent 2p → 3d core to valence state transitions. At the same time, Kao et al. [28] showed the existence of a strong magnetic signal of about 15% in resonant x-ray magnetic reflectivity at the L-edges of Fe. These observations prompted that x-ray magnetic dichroism at the L-edges of transition metals could be an attractive technique for magnetic studies, being moreover sensitive to the specific elements in the magnetic material through the well-separated energy positions of 2p → 3d adsorption edges in the 3d transition elements. The use of the XMCD as a powerful technique to study magnetic properties with elemental sensitivity has been promoted by further developments. First, through the so-called XMCD sum rules derived by Thole et al. [14] and Carra et al. [29] it became possible to deduce atomic spin and orbital magnetic moments from measured XMCD and x-ray absorption spectra (XAS). Thereby core-level x-ray spectroscopy was established as one the few techniques capable of providing magnetic information down to the atomic level. Second, the availability as well as quality of x-ray radiation has improved considerably during the last two decades. Highly brilliant synchrotron radiation facilities have become available, enabling worldwide the application of tunable x-ray radiation in magnetics research. The sensitivity of magneto-x-ray techniques has likewise increased markedly. For example, small coverings of magnetic atoms on surfaces can nowadays easily be probed with XMCD [30].

2.2.

The XMCD Sum Rules

For many years sum rules have been known to exist in classical optics [31]. In these sum rules, an integral over the spectrum provides access to a physical quantity of the investigated material [32]. The possibility to use sum rules to extract values for the orbital and spin magnetic moments was considered first by Hasegawa and Howard [33] and Erskine and Stern [22]. Thole et al. [14] and Carra et al. [29] derived the XMCD sum rules that express the local spin and orbital moments through integrals of the XMCD spectrum at a certain absorption edge. In their most general form they read µ ¯+ ¯− j+,j− − µ j+,j−

µ ¯+ j+,j−

+

  h − µ ¯+ − µ ¯ j+ j+ − 1 + µ ¯+ j+,j−

+

µ ¯− j+,j−

1 lc

µ ¯− j+,j−

i

+

+µ ¯0j+,j−

µ ¯+ ¯− j− − µ j−

µ ¯0j+,j−



=

1 l(l + 1) + 2 − lc (lc + 1) ˆ hlz i, 2 l(l + 1)nh

=

l(l + 1) − 2 − lc (lc + 1) hˆ sz i 3lc nh

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(1)

Magnetic Circular Dichroism in Electron Microscopy +

l(l + 1)[l(l + 1) + 2lc (lc + 1) + 4] − 3(lc − 1)2 (lc + 2)2 ˆ htz i, 6l(l + 1)lc nh

131 (2)

where µ ¯+ ¯− j+,j− , µ j+,j− stand for the integral of the absorption spectrum of right, respectively, left, circularly polarized light over both spin-orbit split core-level absorption edges, j+ and j−. µ ¯0j+,j− is the integrated absorption for linearly polarized x-rays with polarization normal to the atomic magnetization. The angular momentum of the core level is given by lc, that of the probed valence shell by l, and nh is the number of holes in the probed valence shell. The integrated absorption spectra provide values for hˆlz i, hˆ sz i, and htˆz i, which are proportional to the z-projected orbital magnetic moment, Ml = −µB hˆlz i/h and spin moment, sz i/h; ˆtz furthermore is the magnetic dipole operator, defined PMs = −2µB hˆ as htˆz i = h i sˆz,i − 3ˆ rz,i (ˆri · ˆsi ) r12 i, which is a measure for the anisotropy of the spin i distribution (ˆsi, ˆri is the spin, respectively, position of the i-th electron in the shell). While this is the general form of the sum rules, they are mostly applied to ferromagnetic materials containing 3d transmission metal atoms. The local magnetism of the 3d atoms is commonly probed at the L2,3 absorption edges, through resonant transitions from the 2p core-levels to 3d valence states. In this particular situation the sum rules adopt the form Z N ˆ − + − hlz i, (3) [(µ+ L3 − µL3 ) + (µL2 − µL2 )]dE = 2nh L2,3 Z  N  − + − ˆ [(µ+ − µ ) − 2(µ − µ )]dE = 2hˆ s i + 7h t i , (4) z z L3 L3 L2 L2 3nh L2,3

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in which the quantity N is defined by Z Z 3 + − 0 N= [µ + µ + µ ]dE ≈ [µ+ + µ− ]dE. 2 L2,3 L2,3

(5)

Hence, N is a measure for the total absorption at the L edges, for all three polarization states. In the spirit of the Thomas-Reiche-Kuhn sum rule [31, 34] of classical optics it relates to the number of unoccupied 3d-states. In order to apply the XMCD sum rules in practice one would need to know the number of holes nh , and, to obtain a value for the spin magnetic moment, an assumption regarding the tz operator is needed. The usual assumption is to set htz i = 0, which is a reasonable approximation for atoms in an almost cubic environment. However, this can be a poor approximation, e.g., for atoms on a surface. The number of holes in the d-shell is a priori not known, and usually a value obtained from ab initio spin density functional theory (SDFT) calculations is used. Note that a dependence on the value of nh can be avoided through considering the ratio of the orbital and spin moment sum rules [35]. At this point it also deserves to be mentioned that in the derivation of the XMCD sum rules a rather large number of approximations has been made; these will be mentioned below. The XMCD sum rules were tested on Fe and Co by Chen et al. [27]. In their study, Chen et al. showed that to obtain applicable spectral integrals, i.e. those that correspond solely to the 2p → 3d transitions, a background subtraction of the µ0,± absorption spectra is needed. Also, to evaluate the spin magnetic moment an energy in between the L2 and L3 absorption edges has to be chosen as a boundary of the two edges. This choice is not critical as long as the L2 and L3 absorption edges are sufficiently separated. The background

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Table 1. Reported values of Ml /Ms obtained from the XMCD sum rules for the ferromagnetic 3d metals, Fe, Co, and Ni.

Fe Co Ni

Chen et al. [27] 0.043 0.095 —

O’Brien, Tonner [37] 0.085 0.13–0.16 0.14–0.18

Hunter Dunn et al. [38, 39] 0.07 0.16–0.19 0.16–0.17

subtraction can affect the derived values to a larger extent. Nonetheless, Chen et al. derived values for the spin and orbital moments of Fe and Co within about 7% of values derived from gyromagnetic measurements [36]. Experimental tests of the sum rules on the 3d ferromagnetic metals were also performed by O’Brien and Tonner [37] and Hunter Dunn et al. [38] and Arvanitis et al. [39]. Table I compares reported values for the ratio Ml /Ms .

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The reported values for Ml /Ms reveal an appreciable spread. The origin of the differences, which can almost reach 50%, is likely connected to how the background was subtracted. Later studies applying the background subtraction as done by Chen et al. [27] obtained values in closer agreement with their values, as expected.

In practice, the XMCD sum rules provide spin and orbital moments with an accuracy of 10-20%. This can be regarded as a surprisingly good accuracy in view of the many approximations involved in the derivation of the sum rules. In particular, the sum rules are derived for valence states in single free atoms having spherical symmetry; hence the full crystal potential as well as all hybridization with other atomic states are completely ignored. Other involved approximations are that only electric dipole transitions are considered, that no relativistic (spin-flip) transitions are considered, and that 2p → 4s transitions are ignored, see, e.g., [40, 41]. Notably, P the 2p core states are assumed to form a complete space (for the final 3d states), i.e., jz |jjz ihjjz | = 1. The description of the 2p1/2 and 2p3/2 core levels is furthermore simplified by assuming the same radial wavefunctions for these two levels and ignoring their exchange splitting in jz -levels as well as any asphericity. As the absorption of linear polarized x-rays is approximated by µ0 = 21 (µ+ + µ− ) any possible occurrence of a x-ray magnetic linear dichroism is neglected. Finally, no final state effects such as core-hole interaction or final state effects are taken into consideration. The latter effects can certainly be important for materials with localized 3d electrons such as transition metal oxides. In spite of the many involved approximations the XMCD sum rules provide reasonable spin and orbital moment values.

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The XMCD sum rules have also been tested via ab initio calculated absorption spectra and subsequent sum rule integration and comparison to ab initio moments computed from ˆlz and sˆz expectation values [42]. First it deserves to be mentioned that ab initio computer XMCD spectra of metallic 3d compounds compare in general very well with measured XMCD spectra. Second, test calculations show that nonetheless the orbital momentum sum rule provides systematically Ml -values that are 10–20% smaller than directly computed values. The reason for this is possibly that the computed absorption spectra include 2p → 4s transitions and that no background correction has been subtracted. This, again, emphasizes the role played by normalization of the XMCD spectrum through background subtraction to achieve accurate spin and orbital moments from the sum rules. To end this section on XMCD sum rules, we briefly mention first that several other sum rules relating integrated x-ray absorption spectra to certain quantities have been derived (see e.g. [43] for a survey). Also magneto-x-ray sum rules that, within the electric dipole transitions, are exact have been derived [44]. In these, the orbital moment is expressed by the sum rule Z ∞ (µ+ − µ− )dE ∝ hR × Piz (6) 0 P P P where R = i ri and P = i pi . Together with L = i ri × pi it can be shown that the integral approximately gives hlz i, but now due to all electrons in the system. A drawback for practical applications, however, is that an integral over a large energy range is needed.

3.

Analogy between XMCD and EMCD

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J´an Rusz Formal analogies between XAS and EELS have been recognized for a long time. This has been reviewed already in 1992 by Hitchcock [45]. Recently a detailed comparison of core-level spectroscopies performed on manganese oxides was presented by Walther and Stegmann [46]. This analogy is known to extend also to linear (magnetic) dichroism, see works by Yuan and Menon [47] or van Aken and Lauterbach [48]. The analogy between electron and x-ray spectroscopies can be most easily recognized from the formal similarity of the expressions for their respective scattering cross-sections (in the dipole approximation): X σ(E) ∝ |hi|ε · r|f i|2δ(E − Ef + Ei) (7) if

2

∂ σ ∝ ∂E∂Ω

X if

|hi|q · r|f i|2δ(E − Ef + Ei )

(8)

where i, f are initial and final states, q is the momentum transfer vector of the inelastic collision between the incoming electron and studied atom, ε is the polarization vector of the beam of x-rays. Ei, Ef are energies of the initial and final states, respectively, selected by the delta function to be consistent with the energy loss E. According to these expressions, the x-ray absorption spectroscopy experiment with the linearly polarized beam with polarization vector ε should be closely related to the electron

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energy loss spectroscopy with momentum transfer q [1]. This formal analogy has the following deeper physical justification. The polarized photon creates an oscillating electric field parallel to the polarization vector ε. On the other hand, an incoming electron as a charged particle, interacts electromagnetically with the electron of the target atom, and after this interaction its momentum is changed by q. This process is a result of the influence of an electromagnetic force proportional to q. Thus, the forces acting on the studied atom are proportional to polarization or momentum transfer vectors in the case of XAS or EELS, respectively. However, until recently, this analogy has not been extended to the case of circular dichroism. As described in Sec. 2., the XMCD spectrum is a difference between the scattering cross-sections of right- and left-handed circularly polarized light (RCP and LCP, respectively). The circularly polarized light can be prepared as a coherent superposition of two linearly polarized beams with phases shifted by π/2. In the TEM, one can try to set the experimental conditions such, that one has a coherent superposition of two electron beams with two different ki1 and ki2 and set the detector in the direction measuring outgoing electrons with kf such that kf − ki1 = q1 is perpendicular to kf − ki2 = q2 . If one could arrange the incoming beams to be phase shifted by π/2, one would obtain conditions analogous to XMCD. The description of the interference of two beams then leads to a notion of the mixed dynamic form factor (MDFF), a key quantity in the interferometric electron microscopy, which has the expression X S(q, q0, E) = hf |q · r|iihi|q0 · r|f iδ(E − Ef + Ei) (9)

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i,f

in the dipole approximation. For more details about the MDFF see Sec. 4.1.2. In a simple two beam experiment, the dichroic effect is proportional to the imaginary part of the MDFF. Because of the symmetries which MDFF possesses, the requirement of a non-zero imaginary part of the MDFF implies breaking of the centrosymmetry of the crystal or breaking of the time-reversal symmetry, i.e., magnetism and related spin-orbital coupling. The first case would correspond to the natural x-ray circular dichroism, while the latter case is a formal analog of the XMCD. Preparing a coherent superposition of two electron beams while keeping a constant phase shift turned out to be a challenge. So far the only viable solution is with the help of nature itself – to use the crystal itself as a beam-splitter [49]. It means that one can use the crystalline lattice to split the incoming electron beam into several coherent plane-wave components, which then give rise to the above-mentioned interference terms (MDFFs). Obviously, this requires the use of crystalline samples, which is a disadvantage compared to XMCD. It also brings an additional complexity from the theoretical and interpretational point of view – the EMCD spectrum is sensitively dependent on dynamical diffraction effects. Despite all difficulties, the method works and the rest of the chapter is devoted to the development and state-of-the-art (and beyond) of this approach to EMCD. We conclude the discussion of analogies between XMCD and EMCD by referring to the first and so far only experiment, where EMCD and XMCD spectra were directly compared and measured on the same sample. It was published in [1] and is described more in detail in Sec. 4.2.

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4. 4.1.

135

State of the Art in EMCD Theory

J´an Rusz

Theory plays an important role in the development of the EMCD experimental techniques. The reason is the complexity of the dynamical diffraction effects of electrons on the crystalline lattice. The size of the EMCD effect is found to be a sensitive function of the acceleration voltage, sample thickness, and sample and detector orientation. All these influences are difficult – if not impossible – to qualitatively predict without resorting to computer simulations. Therefore the development of EMCD goes hand-in-hand with the development of theory and simulation methods. In the following paragraphs we will describe the essential parts of the theoretical description of the EMCD phenomenon.

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4.1.1.

Dynamical Diffraction

The diffraction of electrons passing through a crystalline sample was one of the first experimental proofs of the de Broglie’s hypothesis, which states that electrons should behave also as waves with a certain wavelength (de Broglie wavelength). The first electron diffraction experiments were performed independently by G. P. Thomson and by C. J. Davidson and L. H. Germer, for which the first two got a Nobel prize in 1937. The dynamical diffraction theory is essentially a solution of the Schr¨odinger equation for passage of a probe electron through a sample. We assume that there is always just one probe electron at a time in the sample and that its energy is high, so that it occupies some of the continuum states. As such, its energy is specified by the acceleration voltage of the electron gun in the TEM. There are two major methods for solving the dynamical diffraction equations: The Bloch waves method and the multislice method. The multislice method [50] is intuitively easier to understand. It is essentially a numerical solution of a time-dependent Schr¨odinger equation, which describes a wave packet entering a sample, evolving slice-by-slice as it progresses through the crystal lattice, until it finally leaves the sample. Multislice implementations typically neglect the backscattering, because otherwise there is no tractable set of closed equations describing the movement of the wave packet as it progresses through the sample. Nevertheless, recently a generalization of the multislice method, which includes a single backscattering event, has been formulated [51]. Because of the difficulties with backscattering, the multislice method is best suited for highly accelerated beams (hundreds of keV), where the probability of backscattering is very low. The multislice method is particularly suitable for systems with defects, e.g., impurities, vacancies, dislocations, because it scales well with the size of the simulation cell. When dealing with EELS, the multislice method typically becomes computationally demanding, because every atom inside the simulation cell needs to be considered as a potential inelastic scatterer. In such case multiple runs are needed. A useful approximation has been introduced in [52]: the coordinate of atom positions along the beam direction is discretized, so that as many atoms as possible are moved into the same slice. This can significantly reduce

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the simulation time. We will not pursue this method further, interested readers are referred to comprehensive articles on the subject, such as [53, 54]. The Bloch waves method describes the state of a probe electron in the crystal as a linear combination of Bloch waves, i.e., one-electron wave functions, which are eigenstates of the crystal Hamiltonian. The Schr¨odinger equation provides the set of Bloch waves allowed by crystal symmetry. Boundary conditions and the wave-function continuity requirement at entrance and exit surfaces determine the excitation coefficients for individual Bloch waves – eigenstates of the Schr¨odinger equation. The Bloch waves themselves are often expressed in a plane-wave basis. As such, a relatively large basis set can be needed for well converged calculations. An advantage of the Bloch waves method is its independence on the sample thickness and, in principle, easy incorporation of the backscattering. On the other hand, systems with large simulation unit cells can become quite demanding in the Bloch waves method. For simulation of EELS, Bloch waves method also needs to deal with summation over all potential scatterrers. This can be solved analytically under certain geometrical conditions, however for more general situations the problem is more tricky. A solution to the problem will be described later, in Sec. 5.1. In both methods, the approach to EELS consists of three steps: 1) description of the elastic propagation of the probe electron from sample surface towards an atom, where an inelastic event occurs; 2) description of the inelastic event – calculation of matrix elements (see below), so called mixed dynamical form factor (MDFF, [55]); 3) elastic propagation of the scattered probe electron out of the sample and towards the detector. Since the Bloch waves method is the method used in a vast majority of EMCD simulations, we will briefly describe it here. For details we refer the reader to published literature, e.g., [56]. The Bloch waves, crystal Hamiltonian eigenstates, can be written as

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φ(j) (r) =

X

(j)

Cg ei(k+γ

(j) n+g)·r

(10)

g

where j is the index of the Bloch wave. In this equation we have used the boundary condition for the electron wave vector k: the only component of the wave vector that can change when entering the crystal is the component along the surface normal n, i.e., k → k + γ (j)n. The energy of the probe electrons is known, it is given by the acceleration voltage U . Entering this Ansatz into the Schr¨odinger equation we obtain an equation that is quadratic in γ (j). By neglecting the quadratic terms we obtain an eigenvalue problem, which can be (j) transformed into a Hermitean one [2], in which γ (j) are eigenvalues and Cg are corresponding eigenvectors. From the requirement of continuity of the probe electron wave function at the crystal surface we obtain X (j)? (j) (j) ψin (r) = C0 Cg eiγ (nin·r−tin )ei(kin +g)·r , (11) jg

so that it collapses to a plane wave at the sample surface plane given by the equation nin ·r = tin . The probability that an inelastic event occurs at an atom with position a is then proportional to the squared amplitude of the probe electron wave function. As a result, the fast

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Magnetic Circular Dichroism in Electron Microscopy

137

electron changes energy and direction. The rate with which such event is detected by the detector oriented under a certain direction kout is then proportional to the squared amplitude of the outgoing electron wave function, which can be described as a reciprocal wave, i.e., a beam moving from the detector towards the sample back in time [57]. Thus, for the outgoing wave we obtain a similar expression as for the incoming beam: X (l)? (l) (l) ψout(r) = D0 Dh eiγ (nout ·r−tout )ei(kout +h)·r, (12) lh

(l)

where we renamed the Bloch coefficients into Dh along with a change of summation indices. Assembling together the equation for the double differential scattering cross-section (DDSCS) we obtain d2 σ Sa(q, q0, E) 4γ 2 kout X X jlj 0 l0 = 2 Xghg0 h0 (a) (13) dΩdE a0 kin jlj0 l0 a q 2 q 02 ghg0 h0

where 0 0

(j)?

jlj l Xghg 0 0 (a) = C0 h

(j)

(l)

(l)?

(j 0 )

(j 0 )?

Cg D0 Dh C0 Cg0

(l0 )?

D0

(l0)

Dh0 ei(γ

(l) −γ (l0 ) )t

0

ei(q−q )·a

(14)

and momentum transfer vectors are given by

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q = kout + γ (l)nout − kin − γ (j)nin + h − g 0 0 q0 = kout + γ (l ) nout − kin − γ (j ) nin + h0 − g0

(15)

In these equations we assumed for the entrance surface that tin = 0 and thus we could write for the exit surface tout = t. The term Sa (q, q0, E) is the inelastic transition matrix element (MDFF), which is the subject of the next section. The summation needs to be carried out over all illuminated atoms indexed by the position vector a. The traditional solution assumes that the crystal has its c axis perpendicular to the sample surfaces and that both a, b crystal axes are perpendicular to it. Under the additional assumptions that the sample thickness t  c and that the j, l-dependence of MDFFs can be neglected, we can perform the sum analytically [58]. In general, one needs to evaluate a thickness function 1 i(γ (l) −γ (l0 ) )t X i(q−q0 )·R Tjlj 0 l0 (t) = e e (16) NR R

which is the topic of Sec. 5.1. With help of this definition, we can express DDSCS in the following way X d2 σ 4γ 2 kout X 0 Sa(q, q0, E) jlj 0 l0 = 2 , Tjlj 0 l0 (t)Yghg0 h0 ei(q−q )·u dΩdE q 2 q 02 a0 kin jlj0 l0 u

(17)

ghg0 h0

where the sum over basis vectors u denotes summation over atoms in a single unit cell and jlj 0 l0

(j)?

Yghg0 h0 = C0

(j)

(l)

(l)?

(j 0 )

(j 0 )?

Cg D0 Dh C0 Cg0

(l0 )?

D0

(l0)

Dh0

is a simple product of Bloch coefficients. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

(18)

138 4.1.2.

Jan Rusz, Stefano Rubino, Klaus Leifer et al. Mixed Dynamical Form Factor

The mixed dynamical form factor, denoted S(q, q0, E), is a general matrix element describing an inelastic scattering event on an atom. It was introduced by Kohl and Rose [55] as an interference term occurring in inelastic scattering of a coherent electron wave-packet consisting of several plane wave components. Formulation of such scattering theory leads to the following expression X 0 S(q, q0, E) = hf |eiq·r |iihi|e−iq ·r |f iδ(E − Ef + Ei ), (19) i,f

where i, f label the available initial and final states of the scattering system with energies Ei and Ef , respectively, and q, q0 are the momentum transfer vectors. Such MDFF describes an interference term occuring when coherent plane waves k and k0 scatter into direction kout fulfilling q = kout − k and q0 = kout − k0 . There are several ways of expressing the MDFF with varying levels of sophistication. In case of small q vectors (q · r  1) a simple dipole approximation can be justified S(q, q0, E) ≈ q · N(E) · q0 ,

(20)

where N(E) is a tensor reflecting the local electronic structure of the studied atom. In case of cubic symmetry it collapses to a scalar S(q, q0, E) ≈ q · q0 N (E).

(21)

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For magnetic systems the MDFF in general becomes complex. It is the imaginary part of MDFF, which gives rise to the EMCD effect. In the case of the simple dipole approximation the MDFF can be rewritten as S(q, q0, E) ≈ q · N(E) · q0 + i(q × q0 ) · M(E),

(22)

where the vector M points along magnetization direction and N(E) is a real symmetric tensor. Such expression was used in several recent works, e.g., in a study of distortions of the measured datacube [59], formulation of inelastic diffraction theory using density matrices [52], theoretical estimation of the shift of atom peaks in high-resolution TEM images [60] or a recent implementation of Bloch waves theory [61]. The parameters M and N are typically estimated so that they fulfill certain experimentally known conditions, e.g., relative strength of the dichroic signal. A more sophisticated method of evaluating the MDFF is based on atomic model Hamiltonians, e.g., the atomic multiplet theory [62, 63]. Parameters such as Slater-Condon integrals, spin-orbit coupling, crystal field symmetry and strength can be calculated ab initio or fitted to experiments to reproduce the experimentally observed spectral shapes. Such theory provides the set of initial and final states with their energy levels, and these can be used to evaluate the MDFFs. The first such attempt has been published in Ref. [64], using the dipole approximation. The multiplet theory has been used for evaluation of the double-differential scattering cross-section of magnetite, studying the thickness and energy dependence of the dichroic signal.

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Another method is based on using the density functional theory (DFT; [65, 66]). DFT is currently the most wide-spread approach of parameter-free calculations of the electronic structures of solids, molecules or atoms. The only input to the theory is the position and type of atoms in the structure. Evaluation of the MDFFs using DFT was reported in several works, e.g., [67, 68, 69], nevertheless their method of treatment of the initial core states neglected their spin-orbital splitting and thus it did not allow to predict the EMCD effect. In the recent implementation [2] the core levels were treated in the |jjz i basis. This allowed analyses of the EMCD effect – its thickness and orientation dependence. Here we briefly summarize the main concepts of the DFT evaluation of the MDFFs. The initial states are described, as mentioned above, by relativistic angular momentum indices |ii → |jjz i. Initial states are non-zero only within a limited region around the atom due to tight localization of the core-level electrons. We will call this region an atomic sphere. The final states in crystals are described as one-electron Kohn-Sham quasiparticle states, which can be labelled by Bloch vector and band index, i.e., |f i → |kni. These states are non-zero in the whole crystal, however we are only interested in the atomic sphere, where the overlap of final state wave function with initial state wave function is non-negligible. We expand both initial and final states into a combination of the spherical harmonics: |ii ≡ |jjz i =

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|f i ≡ |kni =

X lms

X

|lmsihlms|jjzi =

LM S

X lms

|LM SihLM S|kni =

jjz Clms |lmsi

X

LM S

kn DLM S |LM Si

(23) (24)

jjz kn where Clms are the Clebsh-Gordan coefficients and DLM S is a projection of the |kni KohnM Sham state onto spherical harmonics YL and spin S. Similarly, we expand the exponential in the matrix elements into a combination of spherical harmonics using the Rayleigh expansion:

eiq·r = 4π

X

iλ Yλµ (ˆ q )Yλµ (ˆ r )? jλ (qr)

(25)

λµ

where the jλ is a spherical Bessel function. Using these expressions we obtain for the MDFF the following relatively lengthy expression S(q, q0, E) =

X X X XX

mm0 LM S L0 M 0 S 0 λµ λ0 µ0 0

4πiλ−λ

0

p

[l, l, λ, λ0, L, L0]

× Yµλ (ˆ q )∗ Yµλ0 (ˆ q 0 )hjλ(q)iELSj hjλ0 (q 0 )iEL0S 0 j      l λ L l λ 0 L0 l λ L l λ 0 L0 × 0 0 0 0 0 0 −m µ M −m0 µ0 M 0     1 X l 12 j l j m+m0 2 (−1) (2j + 1) × m S −jz m0 S 0 −jz jz X kn kn ? × DLM S (DL0 M 0 S 0 ) δ(E − Ekn + Ej ) kn

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Jan Rusz, Stefano Rubino, Klaus Leifer et al. p p where [l1 , . . . , ln] ≡ (2l1 + 1) . . .(2ln + 1) and hjλ (q)iELSj is a short-hand notation for an integral of the product of an initial state radial wave function of shell j, a spherical Bessel function of order λ and argument qr and a final state radial wave function at energy E, spin S and shell L. An useful approximation is the λ = 1 approximation [2], which limits the summation over λ, λ0 at maximum value of 1. It captures the dipole transitions and has more accurate asymptotics for large momentum transfer vectors (q · r & 1). 4.1.3.

Sum Rules for EELS

The great success of the XMCD experiment would not have happened, if there would be no way to extract some essential quantitative information from XMCD spectra. This was made possible by the so-called sum rules, which connect energy integrals of the XMCD spectra to ground state magnetic properties of studied elements. The original orbital moment sum rule [14] and spin moment sum rule [29] (see Sec. 2.2.) were later rederived using angular momentum operator algebra by Ankudinov and Rehr [43], generalizing the approach of Altarelli [70]. Ankudinov and Rehr [43] presented a complete set of six dipole sum rules for the XAS spectra, which can be expressed in terms of the following six operators ˆ 1 = 2L(2L − 1)Nh ˆ1/(3Ne ) O ˆ2;i = (2L − 1)L ˆi O ˆ3;ij = (L ˆ iL ˆj + L ˆj L ˆ i )/2 − δij L(L + 1)ˆ1/3 O

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ˆ4;i = 2L(L − 1)[Sˆi − (L ˆ iL ˆ ·S ˆ+L ˆ ·S ˆL ˆ i )/L] O ˆ 5 = 2(L − 1)L ˆ · S/L ˆ O ˆ6;ij = L ˆ i (L ˆ · S) ˆ L ˆj + L ˆ j (L ˆ · S) ˆ L ˆ i − L(L ˆ iSˆj + L ˆ j Sˆi ) O

(26) (27) (28) (29) (30) (31)

where i, j are coordinate components, L is an orbital quantum number of final states in dipole transitions from initial states with an orbital quantum number l, we assume l → l + 1 ≡ L. The Nh and Ne denote number of holes and number of electrons, respectively, in the shell with orbital quantum number L (later in the text we will say simply “L shell”). Number of electrons and holes in L shell are connected by the relation Nh = 2(2L+1)−Ne . ˆ and L ˆ are spin and orbital momentum vector operators acting on the L shell; ˆ1 is an The S unit operator, i.e., Tr[ˆ1ˆ ρL] = Ne with ρˆL a density matrix for the L shell. Here we used a notation more common for EMCD, which differs from notation used in theory of XMCD, e.g., in Sec. 2. As shown in [43], it is possible to express an integrated XAS spectrum as a linear comˆ1 , . . ., O ˆ 6 operators multiplied by polarization bination of ground state mean values of O vectors. Or vice versa, suitable linear combinations of polarized XAS spectra allow to separate a mean value of any of these six operators. For instance, the orbital momentum sum rule for XMCD at L2,3 edges can be stated in the following form Z ˆ 2 i. k ≡ (2L − 1)hL ˆ k i, ∆µ(E)dE ∝ hO (32) k L3 +L2 where ∆µ(E) = µ+ (E) − µ− (E) is the XMCD spectrum, i.e., the difference of XAS spectra for right (µ+ ) or left (µ− ) circularly polarized light, k is the wavevector of the x-ray

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ˆk = L ˆ · k/k is projection of the orbital momentum operator to the direction of beam and L the beam. For the spin momentum sum rule we obtain 1 L

Z

∆µ(E)dE −

L3

1 L−1

Z

∆µ(E)dE ∝

L2

ˆ 4i hO k · . L(L − 1) k

(33)

ˆ 4 and the magnetic dipole moment operator T ˆ A useful relation between the operator O allows to reformulate it into a more familiar form   2 2L + 3 ˆ ˆ ˆ O4;i = (2L − 1)L(L − 1) Si + Ti . (34) 3 L

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Hence the spin sum rule can be stated as   Z Z 1 2L + 3 1 2 hTˆki ∆µ(E)dE − ∆µ(E)dE ∝ (2L − 1) hSˆk i + L L3 L − 1 L2 3 L

(35)

with the same proportionality constant as in the orbital momentum sum rule above. The situation is more complicated in the case of the EELS due to dynamical diffraction effects discussed above in Sec. 4.1.1.. The EELS spectra can not be described by a single inelastic transition matrix element with well specified momentum transfer vectors (as an analogy to polarization vectors of x-rays, see Sec. 3.). The EELS spectrum is a combination of a multitude of inelastic transition with various momentum transfer diads q, q0 weighted by coefficients given by dynamical diffraction conditions. This has to be taken into account in the derivation of the EELS sum rules. The spin and orbital EMCD sum rules have been independently reported in two articles by Calmels et al. [4] and Rusz et al. [3]. The latter work presents a complete set of EELS sum rules in a rotationally-invariant form, which we will briefly show here. The derivation of EELS sum rules is based on re-expressing the MDFF using mean values of combinations of angular momentum operators. It is a relatively lengthy, but rather straightforward procedure. We will not go into details of those steps here, we just state the resulting expressions, which relate energy-integrated MDFF to expectation values of ˆ1 , . . . , O ˆ 6 defined in Eqns. (26-31): operators O Z ∞ L − δj− ˆ L(L − 1) ˆ Re[Sj (q, q0, E)]dE ∝ hXi ± hY i (36) 2L − 1 2L − 1 EF Z ∞ i (q × q0 ) h ˆ 2i ± hO ˆ 4i Im[Sj (q, q0, E)]dE ∝ · (L − δj− )hO (37) 2(2L − 1) EF where ˆ1 + q · O ˆ 3 · q0 ˆ = (q · q0 )Ne O X ˆ5 + q · O ˆ 6 · q0 Yˆ = −(q · q0 )L2 O

(38) (39)

These expressions can be considered also as an inversion of the rotationally-invariant form of the sum rules for a single MDFF, see Sec. 5.2. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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To state the final expressions for the EELS sum rules we need to find an equivalent of a difference spectrum as in XMCD. Generally, we need two different detector positions, which are connected by a symmetry operation of the whole experimental geometry including incoming beam and crystal structure orientation. Particularly, we need a symmetry operation, that inverts the direction of magnetic moments, such as a mirror plane parallel to magnetic moment directions. In such conditions it can be shown that the two measurements can be simulated with the same Bloch fields, just the order of vectors q, q0 in MDFFs becomes interchanged, which, in turn, inverts the sign of the imaginary part of MDFF. Assuming that we can identify such two detector orientations, we denote the sum and difference of such spectra by S(E) and D(E), and their energy integrals over a particular edge j we denote simply Sj and Dj . Then the complete set of sum rules can be formulated in this form: Dj+ + Dj− =

ˆ 2i 4γ 2 kout X ML (q, q 0) hO jlj 0l0 (a) X (q × q0 ) · 0 0 2 2 02 ghg h a0 kin a;jlj0 l0 q q 2

(40)

ˆ 4i ML (q, q 0) hO kout X jlj 0l0 X (a) (q × q0 ) · 0 h0 2 ghg 2 02 q q 2L(L − 1) a0 kin a;jlj0 l0

(41)

i ML (q, q 0) h ˆ 1 i + hO ˆ 3 i · q0 q · N h O e q 2 q 02

(42)

ghg0 h0

Dj+ Dj− − L L−1

4γ 2

=

ghg0 h0

2

Sj+ + Sj− =

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Sj− Sj+ − L−1 L

=

4γ kout a20 kin

X

jlj 0l0

Xghg0 h0 (a)

a;jlj 0 l0 ghg0 h0

i 4γ 2 kout X ML (q, q 0) h 2 ˆ jlj 0l0 ˆ 6 i · q0 (43) X (a) q · L h O i + h O 0 5 0 q 2 q 02 a20 kin a;jlj0 l0 ghg h ghg0 h0

These four EELS sum rules are the counterparts of the x-ray absorption orbital moment sum rule, spin moment sum rule, N sum rule (combined with anisotropic orbital sum rule) and spin-orbit sum rule (combined with anisotropic spin magnetic sum rule), respectively, c.f. with [43]. In the literature there are a few works where an evaluation of a ratio of orbital and spin moment was attempted from experimental spectra. If we neglect the magnetic dipole term and assume that the spin and orbital moments are parallel, then such ratio is free of the dynamical diffraction effects, as can be inspected from Eqns. (40), (41) and (34). We obtain ˆ 2i Dj+ + Dj− 1 hO 3 mL = (44) ≈ L ˆ 4i L − 1 hO L mS Dj+ − L−1 Dj− where mL and mS are the orbital and spin moments, respectively. The first sum rule evaluation for iron was published in Ref. [4] reporting a value of 0.09 ± 0.03 without data processing, thus this value should be considered only as a semi-quantitative estimate. Similarly, in a later work [71] a value 0.14 ± 0.03 for hcp cobalt was reported. In Ref. [8] a detailed statistical analysis of reciprocal space distribution of the EMCD signal was described, which led to a value of 0.08 ± 0.01 for bcc iron. A recent work [72] published a similar value of 0.065 ± 0.005 using a different approach to data processing. Comparing these results to the XMCD data by Chen et al. [27], we observe a slight overestimation in

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the EMCD numbers. A possible explanation based on plural scattering will be discussed in Sec. 5.4.

4.2.

Experiment

Stefano Rubino

In the following, we provide a short description of several possible experimental setups for the detection of EMCD in the TEM. A standard TEM equipped with an EELS spectrometer is all that it is required to obtain dichroic spectra. An image filter is required for a collection of EFTEM datacubes. The physical manifestation of EMCD is a change of relative intensity in EELS edges as a function of the incident ki or scattering direction kf . For this reason, most TEM techniques can be adapted for EMCD, provided that certain criteria are met. They can be grouped in diffraction mode techniques, when a diffraction pattern is projected onto the EELS detector, and image mode techniques, when a real space image is projected. In the first case the detector can be used to select kf (either during the acquisition or in post-processing); in the latter case other means are to be used to select the appropriate helicity of the excitation, for example by using the objective aperture (OA) to select kf . The interested reader can find more detailed information in the following references: general [73, 74], LACDIF [6], CBED [75], EFTEM [76], chiral STEM [7], quantitative EMCD [8].

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4.2.1.

Basics

There are different methods by which one can obtain two coherent electron beams with a specific phase shift in the TEM, however, as mentioned above, the only one so far successfully employed for EMCD is the so called intrinsic way: the specimen itself, when crystalline in nature, acts as beam splitter, phase tuner and target [73, 49, 77]. When the electron beam enters a crystal, it becomes a coherent superposition of Bloch waves having the same periodicity as of the crystal (in the approximation that the crystal is infinite in the x and y direction). Each of these Bloch waves can be taken as an electron beam ki (with i = 1, 2, ...) capable of transferring momentum to the atom by being scattered in the direction kf . This direction can be chosen, for example by placing the EELS detector on a specific point in the diffraction plane. In practice, this is accomplished by projecting the diffraction pattern (i.e. the back focal plane of the objective lens) onto the spectrometer entrance aperture (SEA) and using the diffraction deflection coils to adjust the position of the SEA with respect to the transmitted beam (Fig. 1). If the SEA is placed on the so-called Thales circle, i.e. the smallest circle in the diffraction plane passing through the two beam directions, the momentum transfers from the two beams will be perpendicular to each other. Two points on such circle have the additional property that they are equidistant from the two beams and they in fact correspond to RCP and LCP excitation (assuming G is dephased by π/2 with respect to the transmitted beam); they have been named respectively A (or σ + ) and B (or σ − ) in Fig. 1. Any other position of the SEA in the diffraction plane would correspond to elliptical polarization; with the particular case of the SEA lying on the qx axis

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Figure 1. In the diffraction plane, two electron plane waves propagating in two slightly different directions k1 and k2 appear as two bright spots here indicated as (000) and G, respectively. The size of the spot is directly related to the convergence angle. The direction from (000) to G defines the qx axis and the systematic row. The (000)–G segment is the diameter of the Thales circle. Placing an aperture in the diffraction plane defines kf and the collection angle. If the aperture is placed on the circle at an equal distance from (000) and G, the points A (σ + ) and B (σ − ) are obtained. If G is dephased by π/2 with respect to (000), these two points correspond to RCP and LCP excitation, respectively.

Figure 2. Each point of the data cube contains information about the number of electrons that have been detected for that particular energy-loss (z-axis) and spatial coordinate (xand y-axis) for the image mode. If the data cube is collected in diffraction mode, angular and energy information is recorded, with scattering directions kx and ky substituting the xand y-axis.

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Figure 3. Left: Fe L2,3 XMCD of epitaxial iron on GaAs(001) remanently magnetized along the in-plane (100) direction. The full and dashed curves are obtained by reversing the handedness of circular polarized x-rays at each energy. The magnitude of the dichroism is represented by the difference (dotted) spectrum. Middle: EMCD measurements at the Fe L2,3 edge for 10 nm Fe on GaAs (001) in the two configurations σ(+) and σ(−). Right: simulations of the EMCD spectra. The dichroic signal is 0.07 for the measured spectra and 0.32 for the simulations. The r.m.s. of the noise is 0.03. From Ref. [1].

corresponding to linear polarization. Since any polarization state can be thought as superposition of RCP and LCP, it follows that the maximum of MCD can be expected for pure RCP or LCP states, i.e. for the two points A and B on the Thales circle. However, this is only valid in the approximation of two plane waves dephased by π/2. When we generalize to the many beams case and different dephase values, the maximum (and minimum) of the EMCD signal is shown to appear in other regions of the diffraction plane. Fig. 1 also shows that a very easy way for switching from RCP to LCP excitation is to simply shift the SEA from A to B. This is an important fact as the EMCD signal is defined as the difference between spectra with opposite helicity and therefore requires the acquisition of two spectra. The important point to remember is that to excite chiral transitions in the TEM with the intrinsic method (sample as beam splitter and phase tuner) one has to either record the entire diffraction plane at different energy losses or place a kf -defining aperture (the SEA or the objective aperture, for instance) in the diffraction plane and then record spectra or an EFTEM series. Ideally, one would want to record the entire data cube (Fig. 2) either in real space for two opposite polarizations or in reciprocal space. 4.2.2.

Spectroscopic Approach

The simplest way to record the EMCD signal is to project the diffraction pattern on the SEA and record angle-resolved EELS spectra with different excitation helicity. For example, if the SEA is placed in the position A of Fig. 1, one can change the helicity by either modifying the boundary conditions for the Bloch waves (thus changing the relative phase between the beams) or by moving the SEA to select a different kf . In the first case, the boundary conditions are determined by the specimen thickness and orientation with respect to the incident electron beam. It is possible to change the orientation by simply tilting the specimen or the beam. Beam tilt is preferred for small angles (a few mrad) since the speci-

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men tilt is mechanical and is not as precise. However beam tilt moves the beam away from the optical axis where aberrations are minimal and therefore should not be used for more than a few mrad tilt. If the sample is not uniform in thickness, the boundary conditions can be varied by simply moving to a region with the same orientation but different thickness. The quality of the sample is also important, with the ideal case being a single crystal of high purity. However, real samples have impurities, defects, texture angles and contaminations randomly distributed throughout the sample. Therefore, measurements coming from different parts of the same sample might be affected differently by these imperfections and might give rise to spectral differences that could interfere with the correct extraction of the EMCD signal. For these reasons the detector shift method is preferred. When the SEA is moved in the diffraction plane, the illumination conditions remain the same, within the limits dictated by specimen drift and column stability, that could cause the illuminated region to change during the serial acquisition of the EMCD spectra. This method was used to obtain the first proof of EMCD [1] by comparing the EMCD and XMCD signal from the same specimen. A thin Fe single crystal film was epitaxially grown in ultra high vacuum on top of a GaAs [001] self-supporting substrate and protected by 2.5 nm of Cu capping layer. The specimen, suitable for both XAS and TEM experiments, was transferred without breaking the vacuum to the beamline for XMCD measurements. Circularly polarized x-rays from the APPLE-II-type undulator radiation source at the ELETTRA storage ring were focused on a 50 µm spot on the sample surface, at 45 degrees incidence. The dichroic signal was obtained by scanning in energy over the Fe L2,3 edge and by reversing the photon helicity, as well as, for a given x-ray helicity, by rotating the sample of 180 degrees around an axis perpendicular to its surface. The remanent in-plane magnetization of the sample was mapped by XMCD all over the relevant parts of the sample in order to assess the uniformity of its magnetization. Representative data are shown in the left panel of Fig. 3. A further capping layer of 2 nm of Cu was deposited to prevent Fe layer oxidation during the transfer of the samples to the TEM in Vienna. For the EELS spectra, a flat region of 100 nm radius and uniform thickness was selected in a single grain of Fe. The magnetization of the iron film in the TEM experiment is forced to be saturated in the out-of-plane direction by a field (created by the objective lens) that is large with respect to the in-plane coercivity. This is crystallographically identical to the in-plane magnetization used in the XMCD experiment, providing two physically equivalent conditions. The measured spectra are shown in the middle panel of Fig. 3. The dichroic signal is given by the difference between the two spectra taken at the position σ(+) and σ(−). A comparison between the XMCD and the EMCD spectra shows that the observed dichroic signal is smaller than predicted. This can be at least in part explained by the following considerations: The iron layer is grown epitaxially on the GaAs substrate, but they have different unit cells. The diffraction patterns of iron and GaAs overlap almost completely except for the four (200) reflections of GaAs, which are where the four (100) Fe reflections would be if they were not forbidden. For this measurement, the kf -selecting aperture is placed on the (200) spot of the GaAs substrate, therefore a significant part of the collected signal at the Fe L2,3 edge does not come from the interference between the Fe (000) and (110) spot but from a double scattering event: one elastic, caused by the GaAs substrate (with wave vector transfer q 6= 0 and E = 0); and one inelastic, caused by the Fe substrate (with q = 0 and E 6= 0). This contribution is obviously non-dichroic because for

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all four GaAs (200) spots the energy dependence will be the same as the one associated with the Fe spectrum of the direct beam. The intensity of this contribution from each spot will be different if the four spots have different excitation errors. This will be corrected once the spectra are normalized in the post-edge region. However the presence of this non-dichroic term will reduce the value of the relative dichroic signal. Variations in the thermal diffuse scattering between the acquisition at position σ(+) and position σ(−) can also reduce the measured dichroic signal. Moreover, the integration of the signal over the SEA and the non-zero convergence angle reduces the percentage dichroic effect. Finally, the simulated dichroic signal in this configuration shows a strong dependence on the thickness (10 ± 2 nm) of the Fe layer [2]. A deviation from the nominal value of a few nanometers would reduce the dichroic signal to half its value. Clearly both EMCD in the TEM and XMCD on the Fe/GaAs sample show comparable spectroscopic features, referred to either remanent or forced magnetization. Furthermore the comparison with the numerical predictions gives the first experimental confirmation of the EMCD effect in Fe.

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4.2.3.

Alternative Methods

For all diffraction mode techniques the spatial resolution is determined by the size of the illuminated region. With a moderate convergence angle, this is normally in the micron range, but can be reduced to 100 nm by using a selected area aperture (SAA). If the sample thickness and/or orientation changes significantly within the illuminated area, the resulting EMCD signal will be a superposition of EMCD signals. Therefore, improving the spatial resolution is also a way to lessen the quality demanded on the sample. The simplest way to reduce the illuminated area is to converge the beam more and more, until its smallest possible size is obtained as defined by the diffraction limit (the Airy disk, with radius r = 1.22λ/2α [78], where λ is the wavelength of the electron beam and α the convergence semiangle). In practice this limit is of the order of 1 - 2 nm. When the source is partially incoherent and/or the lens has spherical aberration this value is accordingly larger, possibly by one order of magnitude. This is the so-called CBED configuration [78, 75]. The chiral STEM configuration [7] is nothing more than a CBED setup where EELS spectra are acquired while the beam is scanned across the sample. An additional advantage of this setup is that all electrons in the beam can contribute to the EMCD signal as none is blocked by the SAA anymore. The major drawback of the CBED setup is that, as the convergence semiangle α is increased, so do the spots in the diffraction pattern, changing from point-like to disks as the incident beam direction (and therefore all diffracted beams as well) is no longer single-valued but within a range defined by α. When the beam is completely converged, the value of α is defined by the condenser system and it is normally in the 1-10 mrad range when small condenser apertures are used. If α is too big, the diffraction disks may overlap, reducing the EMCD signal. It is possible to use a LACDIF [79, 6] setup to reduce this problem. A different way of improving the spatial resolution is given by the image mode techniques. In the spectroscopic approach, the image of the sample is projected onto the SEA, which limits and defines the region from which EMCD spectra are recorded. Increasing the TEM magnification reduces the size of the SEA relative to the projected image, thereby increasing the EMCD lateral resolution (up to the limit of the TEM resolution). Once again,

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the change of helicity can be obtained by placing the OA in the positions A and B of the diffraction plane while acquiring the spectra, as shown in Fig. 5 for the EFTEM approach discussed in the next section.

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4.2.4.

Quantitative EMCD

Figure 4. ESD: a series of energy filtered images (left) of the diffraction pattern of bcc Fe in two-beam case is acquired with an energy window of 2 eV and energy step of 1 eV. By placing two virtual apertures (squares of 0.5G × 0.5G) on the Thales circle positions, EMCD spectra can be extracted from the data cube (top right). Dichroic maps can be obtained (experiment, bottom left and simulation, bottom right) by using the horizontal mirror axis to subtract, pixel by pixel, the signal in the upper half plane from the signal in the lower half plane and integrating the energy slices corresponding to the L3 or L2 edge. Alternatively, the spectrum in each pixel can be fitted to obtain the area under each relevant edge. Figure adapted from [8].

The EMCD signature is a difference in the spectral features of an ionization edge due to differences in the helicity of the excitation. As such, one might think that EMCD measurements are simply a subgroup of angle-resolved EELS measurements and can be performed only with an EELS spectrometer. However, spectra need not be recorded directly, but can be extracted from an EELS data cube. In the EFTEM approach, also called Energy Spectroscopic Diffraction or Imaging (ESD or ESI), an image filter is used to record serially the image projected on the detector (either a diffraction pattern or a real space image), while the energy window is varied, obtaining a series of images as function of the energy loss. In this case each pixel of the CCD camera acts as a detector and the signal for several different chiral excitations is recorded simulta-

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Figure 5. Scheme of ESI measurements: the OA is placed at the A position on the Thales circle, the TEM is switched to image mode and an EFS is acquired scanning the L2,3 edge of the element of interest. The OA is then shifted to the B position and another EFS is taken over the same energy range. For every point in real space (i.e., for the same (x, y) pixel in each energy slice), two spectra are obtained (blue for position A, red for position B). Under certain assumptions (see text) the difference between the integrated spectral intensity at L3 should be opposite to that at L2 . An example is shown in Fig. 6.

neously. For ESD, the advantage of recording the entire diffraction pattern is that one can easily see where the maximum dichroic signal is located and comparison with the calculated dichroic map is rather straightforward [8, 76]. Spectra can be extracted post-acquisition by use of virtual apertures. The disadvantage is that one can either use parallel illumination, but then spatial resolution will be poor (the size of the illuminated area is defined by the selected area apertures and it is in the ∼100 nm range); or one can use a convergent beam (LACDIF or CBED method) to improve both signal intensity and spatial resolution, but then the spots in the diffraction patterns will become disks (proportionally to the convergence angle) and the dichroic signal will be smeared out. The datacube in reciprocal space could also be acquired with a simple spectrometer by serially recording spectra while shifting the diffraction pattern with respect to the SEA by use of the deflection coils (similar to energy spectroscopic imaging but in TEM diffraction mode). This acquisition method hasn’t been tried yet as it sacrifices qx , qy resolution for a better energy resolution. However for the application of the sum rules [3] only integrals of the spectral lines are used therefore there is no need for a high energy resolution. The dichroic signal can be extracted [5, 8] in two ways from the obtained EELS data cube (Fig. 4 shows an example for bcc-Fe). One can take the energy filtered image of the diffraction pattern recorded for the energy loss corresponding to the L3 (or L2 ) peak. To improve the SNR all images corresponding to the L3 edge can be summed up. The line connecting the (000) and the diffracted spot defines the x-axis. It is used as a mirror plane to obtain the EMCD signal by subtracting pixels with positive and negative qy values. The positioning of the mirror axis is critical as small displacements from the proper position could induce artefacts especially around the diffraction spots. Alternatively, one can imagine placing a virtual aperture in the same position in every image of the recorded diffraction pattern and measure the intensity falling within this

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Figure 6. Real space dichroic maps: a) Energy filtered diffraction pattern of bcc Fe (grown on MgO with a wetting Fe/V layer) at 710 eV using a 5 eV slit, in 3BC geometry with G = ±(200). The dashed circles indicates the positions of the objective aperture that were used for acquiring the two data cubes. b) Dark field (G) image before the two EFTEM data cubes were acquired, revealing possible regions with correct orientation for the real space maps (bright areas). In c) and d) the EMCD real space maps for the L3 and L2 edges are shown, respectively. The arrows indicates the same positions in c) and d), from where spectra were extracted in e). The corresponding regions of c) and d) are indicated in b) with a white box. Square boxes with different sizes were used, averaging over 2 nm, 6 nm, 14 nm, 30 nm and 46 nm as indicated. An EMCD signal is observed at both L2,3 edges even for the smallest (2 nm) spatial resolution. The spectra were offset in intensity for clarity. Figure adapted from [76].

aperture as function of the energy loss at which the image was recorded. The plot thus obtained is equivalent1 to the energy loss spectrum that would have been recorded with that particular scattering angle (i.e., with the SEA in the place of the virtual aperture). Extracting the corresponding spectrum from the opposite position on the mirror axis produces an EMCD measurement. The possibility to use virtual apertures of different sizes to extract EELS spectra from the same data cube provides another possibility to study the effect of collection angle on the EMCD signal [80]. For ESI it is an image of the sample that is projected onto the SEA and then an Energy Filtered Series (EFS) is started. It should be noted that in this case the OA is needed to select kf (Fig. 5) and two series have to be acquired, one for each position of the OA. Real space dichroic maps are then obtained by subtracting each image of one series from the corresponding (i.e., with the same energy loss) image of the other series. 1

it should be noted that the energy step is smaller than the energy window, therefore the spectra extracted from the datacube would correspond to EELS spectra obtained with a 2 eV/channel dispersion and with partially overlapping channels. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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By using the sum rules [3] it can be shown that when the orbital contribution to the total magnetization is negligible with respect to the spin contribution (which is a good approximation for late transition metals), then the difference of the spectral intensity integrated over the L3 edge is the opposite of the difference of spectral intensity integrated over the ˆ z i = 0), that is: L2 edge (assuming hL Z

L3 (A) −

Z

L3 (B) = −

Z

L2 (A) −

Z



L2 (B) .

(45)

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If the illuminated area is uniform in thickness and is not bent, then the two difference images should have the same value for every pixel. If the illuminated area has, for example, a variation in thickness, thickness fringes will appear in the dark field image and in the difference images (one difference image being like a negative for the other difference image). The difference image will be zero for the areas in the specimen where there is no magnetization parallel to the electron beam, for example areas where the magnetization remains in plane or where there are epitaxially grown layers of non-magnetic materials. Similarly to ESD, spectra can also be extracted by placing a virtual aperture in the same position of each image of the two series. An example of chiral ESI is shown in Fig. 6. For both ESD and ESI, when only the dichroic maps are of interest, the data cube can be reduced to just four or five points in the energy-loss dimension: two points for the pre-edge region, one for the L3 , one for the L2 and eventually one for the post-edge region. The advantage is that the energy window for each point can be increased to several eV, improving the SNR, and the acquisition time can be reduced, together with the detrimental effect of beam and specimen drift. The two pre-edge points are used to evaluate and remove the background from the edges, in a fashion similar to the elemental map three-window method [81]. The post-edge point can be acquired for the post-edge normalization, if needed.

4.3.

Data Treatment

Klaus Leifer Since the EMCD signal is rather weak, an important part of the data treatment aims at the optimization of the signal/noise (S/N) ratio, which becomes a decisive factor when the EMCD signal is to be extracted quantitatively. The first step in the increase of S/N consists in the optimization of the signal. Whereas the increase of acquisition times might result in an increasing influence of instrumental instabilities on the acquisition process, the increase of the emission current leads directly to a strongly enhanced signal. This was demonstrated, e.g., in [76]. As we will see, the optimization of the data treatment of EMCD spectra involves equally the optimal choice of experimental settings in order to minimize the influence of unwanted effects on the EMCD signal. In the following text we describe the treatment of experimental data that were acquired using the two most often used EMCD measurements methods, the detector shift technique and the electron spectroscopic diffraction (ESD) data cube acquisition. For more details about these approaches see, sections 4.2.4. and 4.2.2., respectively.

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The raw spectra obtained from the detector shift technique are first background subtracted. As shown in Fig. 7, in the post-edge region at energy losses higher than the L2 edge, the edge signal often is different between spectrum σ(+) and σ(−). This height difference also can appear in ESD technique. Such difference can be caused by instabilities of the emission current and non-perfect positioning of the acquisition aperture at positions A and B. Though to date little is known from the theoretical description of this post-edge intensity and thus, real differences in this post-edge intensity cannot be excluded. When the difference in the post-edge signal in spectra σ(+) and σ(−) appears too large, the spectra should probably be rejected and the spectra should be acquired again since acquisition artefacts might dominate. In case of small differences of these post-edge intensities (in the percent range), the spectra are normalized, this means the post-edge region in spectra σ(+) and σ(−) are multiplied with a factor such that they are at the same level.

Figure 7. a) Two background subtracted spectra acquired with the aperture positioned at A and B in Fig. 1 respectively. b) Same spectra as in a), but normalized. The difference spectrum shows the EMCD signal at the L2,3 edges. The spectra here were extracted from ESD data cubes. The spectral treatment (background subtraction and normalization) is the same in both methods discussed in Secs. 4.3.1. and 4.3.2. Once the spectra are normalized, the L2,3 edge positions in spectra σ(+) and σ(−) may be slightly different. In EMCD on transition metals, significant peak shifts beyond 100 meV as a function of the position of the acquisition aperture are not expected. Energy shifts may appear during the acquisition due to energy drifts of the gun or, in the case of ESD, due to the non-isochromaticity of the detector plane. In the spectrum acquisition mode, often the energy dispersion, i.e., the energy width/pixel is sufficiently low so that the two spectra can be easily shifted numerically such that the maxima of L2,3 peaks in both spectra coincide. Subsequently, the two spectra will be subtracted from each other yielding the EMCD difference spectrum. The EMCD signal consists in the intensity of the L3 and L2 difference peaks. Reported strengths of EMCD signals, i.e., the ratio between L2,3 difference signal and L2,3 edge intensity are in the range of 5-15% [8, 5]. When the EMCD signal is to be extracted quantitatively from the difference spectra, at energy resolutions of 1 eV or worse, there might be a considerable overlap between L3 and L2 edge intensities. This can make the choice of integration interval in the difference spectrum difficult. In such

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cases, the recommended approach is to decompose the spectrum into individual edges by fitting it on some suitable model spectrum [8, 76].

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4.3.2.

ESD Data Cubes

The goal of the acquisition of ESD data cubes is, as in the detector shift method, to obtain spectra and finally the EMCD signal. But here, the data cube allows for the positioning of a numerical aperture as well as for the calculation of EMCD maps, i.e., the position of the strongest EMCD signal can be determined experimentally. This is particularly important since this procedure maximizes the EMCD signal and optimizes the S/N ratio. In general, due to complicated dynamical diffraction effects, the EMCD signal is not centered on the Thales circle spanned by the 0-beam and the excited reflection. In order to optimize the strength of the EMCD signal, it is important to observe the extension of this signal directly in the reciprocal space plane. Thus, when data are acquired, much of the data treatment can be guided by the visual inspection of the obtained EMCD maps. Though, when new materials are to be characterized for the first time, prior simulations are still recommended at this stage of development of this technique. Such simulations can be done using publicly available simulation packages [2, 61]. The data treatment of the ESD data cube typically starts with rebinning. Due to the weakness of the EMCD signal, it is important to reduce the influence of noise at each stage of the data treatment. In practice, rebinning to a 256 × 256 or 512 × 512 ESD pattern dimension is a reasonable compromise that significantly enhances the S/N ratio in each pixel and still keeps a very good angular resolution. When the region of the EMCD signal is known precisely, for example by prior experiments, a numerical window can be set directly in the ESD cube, the spectra in this window can then be summed and the following data treatment of such spectra follows then the procedures described in Sec. 4.3.1.). More often, the crystallography, composition or texture of the sample might have an unknown influence on the EMCD signal. In these cases, we recommend a pixel-by-pixel treatment of each spectrum in the (qx ,qy ) plane. To our experience, such pixel by pixel treatment compared to the method of setting the numerical aperture right in the beginning of the data treatment procedure, leads both to similar S/N ratios, but pixel-by-pixel treatment offers a better flexibility for statistical analysis of error bars. As the next step, the background will be subtracted. For L-edges of transition metals, the power-law background model yields very good results. Following this, all spectra in the (qx ,qy ) plane will be normalized so that their post-edge intensity coincides (Fig. 7). In the ideal case, one would like to have spectra with highest energy resolution and no energy shift between the spectra. In practice, current energy filters limit the resolution of spectra obtained from ESD data cubes to about 1eV [82]. When energy shifts occur due to instrumental instabilities or the non-isochromaticity of the energy filter, the corresponding spectra could be corrected by acquiring non-isochromaticity maps [59]. One difficulty, as mentioned already in Sec. 4.3.1., consists in the fact that the subtraction of the spectra at position A and B often still requires the definition of an energy interval, from which the EMCD signal would be extracted. Such interval definition might be difficult due to possible overlaps of the peaks resulting from the L3 and L2 edges. In this case, fitting the spectra with model functions makes it possible to obtain the entire edge intensity—instead

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Figure 8. Reciprocal space maps of the EMCD signal of an iron sample oriented in 3beam geometry ([8]). Theoretically simulated relative EMCD maps at the L3 edge are shown in a). The inset shows the simulated diffraction pattern. In b) and c) 3BC maps of experimentally obtained relative EMCD signal at L3 and L2 edges are shown. The black lines indicate the applied mirror axes and blue spots the positions of the transmitted and Bragg scattered G = (200) and −G = (¯200) beams. The inset in b) shows the diffraction patterns averaged over an energy interval from 695 eV to 740 eV. Adapted from [8]. of defining the quantification interval, the entire L3 and L2 edge is obtained from the fitted function. A detailed description of the fitting procedure can be found in [8]. The obtained edge intensity is then reported in (qx ,qy ) maps. In order to simplify the extraction of the EMCD signal the EMCD maps are rotated such that the line passing through reflection and 0-beam is horizontal. In principle, the rotation step could be carried out earlier in the data treatment. But since the rotation step includes an averaging of intensities over neighbored intensities, it might be advantageous to carry out this step at a later stage in the data treatment. In order to obtain the EMCD signal, the mirror axis has to be carefully chosen. The mirror axis will pass through the center of the 0-beam and the selected reflection. The data are now prepared to calculate the EMCD difference maps, which are constructed as a difference of the diffraction pattern and its mirror image. Such difference maps in the 2beam case geometry can be found in [8, 5]. However, the 3-beam case seems to be a more suitable acquisition geometry, since in this case, there are detector positions available for the extraction of the EMCD signal that correspond to perfectly symmetric detector positions [76]. The resulting EMCD maps in the 3-beam case geometry are shown in Fig. 8 b) and c). As can be seen from a comparison with Fig. 8 a), theoretical and experimental maps are in very good agreement in spatial distribution of the EMCD signal in reciprocal space as well as its intensity. From such EMCD maps, the mL /mS ratio can be determined quantitatively according to the formula (Sec. 4.1.3.): mL 2 DL3 + DL2 . (46) = mS 3 DL3 − 2DL2 When using the 3-beam case, the EMCD signal intensity D that is input in the above formula, results from the difference intensity using a vertical mirror axis, i.e., the left half of the Fig. 8 b) and c) will be subtracted from their right half. In practice, the sample can only be oriented with a precision of some fraction of a mrad; thus the sample orientation might slightly deviate from the perfect 3-beam condition. Such orientation deviation has already been taken into account in the simulation in Fig. 8 a). For such small orientation

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0.9G

10nm

0.1G 1.1G

0.9G

20nm

1.1G −0.1G

1.1G

−0.1G

0.9G

0.1G

0.1G

deviations, there is one simple solution for the calculation of an optimized difference signal. It was shown that the computation of the double difference, i.e., first calculating the difference map with a horizontal mirror axis and subsequently applying the vertical mirror axis yields excellent results in the determination of the mL /mS ratio [76]. From difference intensities D in the double difference maps, mL /mS ratio maps can be calculated (see [8]). By positioning the numerical aperture in these maps, the mL /mS ratio can be determined by averaging over all pixels in such map. Whereas the position of the numerical aperture was chosen to be the point of the maximum EMCD signal in simulated maps, the size of the aperture can be chosen numerically. In order to find the optimal size, the mL /mS ratio and its error bar are reported as a function of aperture diameter as shown in Fig. 9. In this case, an mL /mS ratio of 0.08 was found, in fair agreement with data from XMCD that yields slightly lower values [27]. A theoretical description of the best choice of the numerical aperture is given in [80]. It should be noted that the intensities of the L-edges are modified due to plural scattering. Though this change of intensity is small, it will influence the mL /mS ratio. It has been shown in [83] that the application of deconvolution techniques to EMCD spectra yields an mL /mS ratio for Fe that is in excellent agreement with XMCD data, see Sec. 5.4.

−0.1G

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Figure 9. The mL /mS ratio obtained for different window sizes in 2-beam geometry using horizontal mirror axis and in 3-beam geometry using both horizontal and vertical mirror axes (double difference). Inset shows the histogram with fit of the mL /mS ratio for the window size of 0.5G × 0.5G in 2-beam orientation. The error bars give the standard error of the mean value of the mL /mS in each integration window. Adapted from [8].

30nm

1.5

−5.0

Figure 10. Simulation of the displacement position of the Fe (200) reflection at the L2 edge caused by the presence of the dichroic signal as a function of sample thickness. The simulations were carried out as described in [84] orienting the sample on a 2-beam geometry. To demonstrate the displacement effect, simulation is shown in the vicinity of the G = (200) reflection.

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When the EMCD signal is calculated from ESD data cubes, one subtle artefact may appear: due to the fact that EMCD signal at positions A and B is of opposite sign, the position of the Bragg-reflection can be slightly shifted by the presence of the EMCD signal. Gatel et al. [59] suggest that this shift can be substantial and thus it can deform the EMCD signal due to wrong placement of the mirror axis. In the case of the Fe crystal mentioned above, this change has been simulated as a function of crystal thickness, see Fig. 10. Here, the obtained displacement of the Fe (200) reflection was under 2% of G(200). Therefore, though this EMCD inherent drift problem must be kept in mind, in many cases its influence on the quantitative treatment of EMCD spectra can be negligible. In summary, the main tools for data treatment of spectra and ESD data cubes are available now. What is needed in the future, are more studies of different magnetic systems to verify the sum rules and especially to optimize the spatial resolution of the EMCD technique. Besides a further optimization of the data treatment, this needs first of all the refinement of acquisition strategies.

5.

Novel Directions

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In this section we will describe some new ideas—at the time of writing this chapter—in the field of EMCD. Namely, we will describe alternative and more general ways of calculating the thickness function and evaluation of energy integrated MDFFs by formal inversion of EELS sum rules. Using the latter, we will explore the diffraction-plane distribution of the signal originating from various characteristics of studied elements, such as spin moment, spin-orbital interaction, anisotropic terms, etc. Finally, we will try to shed some light on the apparent overestimation of the orbital to spin moment ratios obtained by EMCD, when compared to established XMCD measurements.

5.1.

Thickness Function

Anders Johansson

In this section we describe the various approaches to evaluation of the thickness function introduced in Eqn. (16). The summation over unit cells needs to be done within an irradiated section of the sample, which we denote Ω(t). The complete definition of the thickness function is thus Tjlj 0 l0 (t) =

1 iγ−(ll0 ) t X −i[γ−(jj0 ) nin −γ−(ll0 ) nout]·R e e NR

(47)

R∈Ω(t)

where we used definition of momentum transfer vectors, Eqn. (15), and the relation eiR·g = (ll0) 1 valid for any reciprocal lattice vector g. Here we introduced the notation γ± = γ (l) ± 0 γ (l ) . Analytical formula. For specific samples the summation in Eqn. (47) can, with some approximations, be carried out analytically and brought to a closed form as shown in [58]. Let a, b, c be suitably assigned crystal unit cell lattice vectors. Without loss of generality,

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we adopt a convention c k z. If the following conditions are fulfilled, we can perform the sum in Eqn. (47) analytically: • entrance and exit sample surfaces are mutually parallel • both surfaces are orthogonal to c, i.e., their norms are along z-axis • the a, b lattice vectors are orthogonal to c, i.e., they both lie in the xy-plane These conditions can be fulfilled by cubic, tetragonal, orthorhombic or hexagonal lattices oriented according to the above mentioned conditions and with (001)-surfaces. Under these assumptions we have n ˆin = ˆ z and n ˆout = −ˆ z. The summation over R can be split into three sums over lattice vectors where the sum within the xy-plane will simply yield the total number of illuminated atoms within the plane, denoted Nxy . The total number of planes (lattice points) in z-direction is denoted Nz . Introducing the notation (jj 0) (ll0) (jj 0) (ll0) ∆γ = γ− − γ− and ∆η = η+ − η+ , enables us to write Tjlj 0 l0 (t) as2 N

Tjlj 0 l0 (t) =

z Nxy (iγ (ll0 ) −η(ll0 ) )t X + e(i∆γ −∆η )nc . e − NR

(48)

n=0

The sum of the geometric sequence can be further simplified. If we assume the thickness of the sample to be much larger than the lattice constant, t  c, or equivalently Nz  1, and c(i∆γ − ∆η ) to be a small number compared to 1, using Nz Nxy = NR we get (in accordance with [58]) (jj 0 )

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Tjlj 0 l0 (t) = ei[γ− ×

(ll0 ) t (jj 0 ) (ll0 ) ] 2 −[η+ +η+ ] 2t

+γ−

cosh ∆η 2t sin ∆γ 2t + i sinh ∆η 2t cos ∆γ 2t , (∆γ + i∆η ) 2t

(49)

where the factors NR and 1/NR have cancelled. In the case of no absorption this simplifies to t (jj 0 ) (ll0 ) t sin ∆γ 2 Tjlj 0 l0 (t) = ei[γ− +γ− ] 2 . (50) ∆γ 2t Supercell approach. The supercell approach is essentially an application of the analytical formula, but for larger (non-primitive) unit cells. This way we can describe, for example, a simple-cubic structure with√surface normals along √ zone axis (111) as a system with a hexagonal unit cell with ahex = 2abcc and chex = 3abcc containing 3 times the volume of the cubic conventional unit cell, see Fig. 11. The only formal change is in the structure factor and surface normals, which enter the secular equation for Bloch coefficients. All the restrictions from the previous section stay valid, thus there is still a quite limited set of crystal structures and orientations that can be treated by this approach. Recently this method has been used in a simulation of orientation-dependent electron channeling for NiFe2 O4 crystal [85]. 2 (j)

η ’s can be understood as an imaginary part of γ (j) . They appear when we take into account an absorption, see, e.g., [2, 49, 56, 58]. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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Figure 11. Left: A simple cubic crystal can be seen along the (111)-direction as a hexagonal one with 3-times larger volume per unit cell. To guide the eye, different colors denote atoms with different z-coordinates: z = 0, 13 , 23 for red, blue and green, respectively. Right: An illustration of a set of illuminated unit cells represented by solid spheres for a 15 nm thin sample with a cubic lattice with non-(001) surfaces, assuming a tilted beam of diameter 3.5 nm.

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Explicit summation. For general geometries the sum in Eqn. (47) can be calculated explicitly once the illuminated unit cells, R ∈ Ω(t), have been identified. We have implemented this by means of a flood-fill algorithm determining the R inside a cut-off cone, a shape approximating the beam inside the sample, see Fig. 11. Obviously, this method is completely general, i.e., the restrictions for analytical thickness function are removed. However, the number of illuminated unit cells in the sample can be large for wider beams and thicker samples (up to millions) and that can make such calculations very lengthy. Therefore this method is particularly suited for thin samples and narrow focused beams. Shape-function approach. Here we describe a semi-analytical approach of calculating the thickness function based on Fourier transforms. It removes all constraints of the analytical thickness function, similarly to the explicit summation. Its main advantage is that it is practically independent of the size of the illuminated sample region. It is usable for arbitrary crystal structures and for any orientation of crystal lattice axes and surface normals, which can also be non-parallel. This approach uses a shape function to define the illuminated volume. With some manipulations we arrive at an expression containing the shape amplitude, i.e., the Fourier transform of the shape function. The shape amplitude can then be efficiently calculated if the shape is approximated with a polyhedron [86]. This method is limited to the case of no absorption. The summation in Eqn. (47), with γ (j) and γ (l) real, should be carried out over all lattice Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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vectors inside a body Ω(t): (ll0 )

eiγ− t X −ip·R Tjlj 0 l0 (t) = e . NR

(51)

R∈Ω(t)

(ll0)

(jj 0 )

where p ≡ γ− n ˆ out + γ− n ˆin . P The discrete sum can be rewritten as a continuous integral using a Dirac-comb R δ(r − R): Z X X e−ip·R = e−ip·r δ(r − R) dr R∈Ω(t)

R∈Ω(t)

=

Z

e−ip·r

X R

where θt (r) is the shape function of Ω(t), defined by: ( 1 if r ∈ Ω(t), θt (r) = 0 if r ∈ / Ω(t).

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(52)

δ(r − R)θt (r) dr,

(53)

Equation (52) can be interpreted as a Fourier transform using the kernel e−ip·r . The Fourier transform of a product of two functions is, according to the convolution theorem of Fourier analysis, equal to the convolution of the Fourier transform of each function. Hence we can rewrite the last expression of Eqn. (52) as " # X X eip·R = F δ(r − R) (p) ⊗ F [θ(r)] (p) R∈Ω(t)

R

1 X = δ(p − G) ⊗ Θ(p), Vu

(54)

G

recognizing that the Fourier transform of a real-space Dirac comb is a Dirac comb in reciprocal space divided by the unit cell volume Vu [86] and denoting the Fourier transform of the shape function, called the shape amplitude, by Θ(p). Since NR , the number of unit cells inside Ω(t), roughly equals VΩ /Vu , we can write the thickness function as: (ll0 )

eiγ− Tjlj 0 l0 (t) = VΩ

t

X G

Θ(p − G),

(55)

where the sum over G in practical cases only has to be computed for a few G within some radius since the shape amplitude decays rapidly with larger reciprocal vectors. According to Komrska [86], the shape amplitude, Θ(p), of any polyhedron can be expressed analytically as a finite sum over its vertices, edges and faces: ( VΩ if p = 0, Θ(p) = PF (56) f =1 Θf (p) otherwise,

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where Θf (p) is given by Θf (p) = and Θf e (p) is given by Θf e (p) =

 ± i Pf e∓ipdf p

ˆ f, if p = ±pN ˆ e=1 Θf e (p) if p 6= ±pNf ,

(57)

(Ve ) ip·n ˆ f e e−ip·ξ Le if p · ˆ te = 0, p·ˆ nf e −ip·ξ(Ve ) ˆ −ip· t L e e ˆ e (1 − e ) if p · te 6= 0. p·ˆ t

(58)

 pi2 (

ˆ

p·Nf ˆ [p2 −(p·N

f

)2 ]

PE f

e

In the equations above, the indices e, f label edges and faces of the polyhedron, F is the number of faces and Ef is the number of edges of face f . Pf is the area of face f , df is its ˆ f is its distance from some fixed reference point (e.g., origin of coordinate system) and N outward unit normal. The vector n ˆ f e is an outward unit normal of the edge e lying within the plane containing face f . Le is the length of the edge and ˆ te is a unit vector pointing along the edge. Its direction is given by a convention that it is oriented counter-clockwise if ˆ f . The vector ξ(Ve ) defines the vertex at viewed against the direction of the face normal N the beginning of the edge. These methods have been implemented in a new version of the code described in [2]. More details can be found in [87] and a publication is in preparation [88].

5.2.

Dipole Approximation and Energy-Integrated MDFF

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J´an Rusz In Sec. 4.1.2. we have discussed several methods of calculating the MDFF at various levels of sophistication. Here we will describe a simple method of evaluating energyintegrated MDFFs (IMDFF) on a base of few physical parameters, which can be calculated, e.g., using first principles DFT codes. More specifically, by IMDFF we will have in mind an energy integral of MDFF over a single particular edge. The method is based on inversion of EELS sum rules, which were described in Sec. 4.1.3. Essentially, it is a direct application of Eqns. (36) and (37), assuming that we ˆ1 , . . . , O ˆ 6 given by Eqns. (26–31). know the ground state expectation values of operators O Having these relations at hand, we can evaluate IMDFFs very efficiently. 3 In simulations presented here we have set the anisotropic operators mean values to zero, ˆ 3;ij i = 0 and hO ˆ 6;ij i = 0 and for the other parameters we have adopted the following hO values: L = 2 Nh = 2.7 ˆ = (0, 0, 0.05) hLi ˆ = (0, 0, 1.10) hSi

ˆ = (0, 0, 0.01) hTi ˆ · Si ˆ = −0.05 hL 3

Namely, on a single Pentium IV Xeon CPU at 2.5 GHz we can evaluate one million of IMDFFs in less than 8 seconds. Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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which approximately follow the properties of bulk bcc iron magnetized along (001) axis. We note that our approach allows to construct material-specific IMDFFs on a basis of a few physical parameters, which can be easily obtained from electronic structure calculations. Using these formulas we can now identify the physical meaning of parameters of the dipole approximation of Eqn. 22, namely Z L − δj− ˆ 1 i + hO ˆ 3 i] ± L(L − 1) [L2 hO ˆ 5 i + hO ˆ 6 i] (59) N(E)dE ∝ [Ne hO 2L − 1 2L − 1 j± Z ˆ 2i ˆ 4i L − δj− hO hO M(E)dE ∝ ± (60) 2L − 1 2 2L(L − 1) j± ˆ i we see that the diagonal elements of Comparing with the definitions of operators O ˆ1 ) and N are mainly influenced by the number of particles (trace of density matrix, O ˆ strength of spin-orbital interaction, O5 . The off-diagonal elements are then determined by anisotropy of spin-dependent electron distribution in the surrounding of the studied atom. Note that anisotropies can also contribute to diagonal elements of N. The vector M is then determined by spin and orbital magnetization and by the magnetic ˆ 2 and O ˆ 4 ). dipole term (O An interesting application of this method is to calculate diffraction patterns resulting from hypothetical MDFFs, in which one sets a mean value of selected component of opˆ1 , . . ., O ˆ 6 to, say, one, while setting all the others to zero. This can give us an erators O information how the signal originating, for example, from orbital magnetic moment, is distributed within the diffraction plane. We have performed such calculations and they are summarized in Fig. 12. Obviously, the distribution of the signal from spin-moment component sx is the same as distribution of the signal from magnetic dipole term or orbital magnetic moment, since they are multiplied by the same set of Bloch coefficients and by vector product of momentum transfer vectors (though with different constant prefactor). Therefore, there is only a limited set of different signal distributions from components of these six operators. They have in total 26 components (from 2 tensors, 2 vectors and 2 scalars), but form only 10 different distributions of the signal within the diffraction plane: 3 from x, y, z components of vector operators, 1 from scalar operators, 3 from diagonal elements of tensor operators and 3 from their off-diagonal elements. ˆ1 ), We can conclude that the diffraction pattern is mainly formed by the N -term (O ˆ whereas the spin-orbital interaction (O5 ) in the dipole interaction proportionally enhances or reduces the signal from the N -term, but does not influence its distribution in the diffraction plane. The anisotropic operators have a more complicated influence. The first two diagonal elements xx and yy can distort the square symmetry into a rectangular one, while the zz component seems to only add some intensity to the N -term. The off-diagonal terms are even more interesting: the xy term distorts the diffraction pattern adding a contribution with the symmetry of a rhombus, the xz term shifts Bragg spots to the x-direction and yz term shifts Bragg spots in negative direction along the y-axis. The magnetic contributions form a rather complicated pattern, with strong thickness dependence. Particularly, the z-component also displays a dense structure of lines, which we interpret in terms of magnetic Kikuchi lines. The presence of a contribution from x and

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ˆ 1, . . . , O ˆ 6. Figure 12. Distribution of the signal originating from components of operators O ˆ ˆ ˆ ˆ ˆ ˆ ˆ ˆ ˆ ˆ Columns correspond to O1 , O6;xx, O6;yy , O6;zz , O6;xy , O6;xz , O6;yx, O2;x, O2;y , O2;z , i.e., scalar operator, diagonal elements of tensor operator, off-diagonal elements of tensor operator and vector operator, respectively. Each row corresponds to different thickness, starting at 5 nm with step 5 nm. The 0-beam is in the middle and G = (200) is along the x-axis. Both axes labels are in multiples of the G(200).

y terms was to some extent unexpected, since it corresponds to in-plane magnetization. For instance, x-rays in XMCD experiment with the same direction as electrons in this (001) zone axis setup would not be sensitive to magnetic moments within the xy plane. However, due to higher order Laue zones contributions and energy loss of probe electrons, we can detect also the in-plane magnetization. We will discuss that more in detail in the next section.

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5.3.

163

In-Plane Magnetization

As pointed out in the previous section, somewhat surprisingly, we can measure with EMCD also components of magnetization perpendicular to the beam. This can be of practical importance in systems with strong magneto-crystalline anisotropy. Often in thin magnetic layers, the magnetic moments stay in-plane even in relatively strong perpendicular external magnetic fields, due to the shape anisotropy term. It is interesting to note, that in an exact (001) zone axis orientation of a cubic crystal, we can separate contributions from all three components of the magnetization vector from a single diffraction pattern. Observe that the signal from the x component is symmetric with respect to the ky axis, while both y and z-components lead to an antisymmetric distribution of the signal with respect to that axis. Therefore if we sum the left diffraction half-plane with a mirror image of the right diffraction half-plane, we remove contributions from y and z-components, while the x-contribution gets doubled. A subsequent difference of the upper and lower diffraction quarter-planes removes the contributions from N -term and spin-orbit ˆ 3 and O ˆ 6 , with an term. It also removes the eventual contributions from tensor operators O exception of their yz term, the contribution of which has the same symmetry properties as the contribution from x-component of magnetic signal. In analogic way we can extract the signal from the y-component of the magnetization. The contribution from the z-component of magnetization is antisymmetric to both horizontal and vertical mirror axes, therefore it can be extracted by the double difference procedure introduced in [8]. Its antisymmetry with respect to kx = ky line can moreover be used to remove the eventual xy components from anisotropy tensors. Thus a single measurement of a diffraction pattern in zone axis orientation allows in principle to probe the magnetization vector in all three dimensions and that is a unique feature of EMCD. It is necessary to say, though, that such analysis is only possible for structures with high enough symmetry, otherwise there might not be a sufficient number of symmetry operations, which would allow such separation. In the low-symmetry case one would need to resort to fitting the measured diffraction pattern in order to decompose it into ˆ 1, . . . , O ˆ 6. a combination of theoretical distributions from individual components of O

5.4.

Sum Rules and Influence of the Plural Scattering

At the end of the Sec. 4.1.3. we have compared the available EMCD experimental data of ratios of orbital and spin magnetic moments to their XMCD counterparts. We have observed that EMCD seems to overestimate the ratio. Here we will describe a plausible explanation for such overestimation – namely, a plural scattering of probe electrons. It is well-known that the core-level EELS spectral shapes are influenced by plural scattering [89]. This means, that a probe electron, which has excited a sample electron from its core level, could undergo another one (or more) energy-loss processes by, for example, exciting a band electron into an unoccupied level, or by exciting a plasmon or by some other channels. By registering such electron in the detector we can only observe its energy loss and momentum, but we can’t say how many energy loss processes it has went through. This complication is traditionally solved by measuring a low-loss spectrum together with the core-level EELS spectrum and using this information to remove the plural scattering –

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Figure 13. Top: Scheme of the convolution of low-loss spectra consisting of zero-loss peak (ZLP) and plasmon peak (PP) with core-level edges L3 (upper part) and L2 (lower part); EP P , EL3 , EL2 denote energies of plasmon peak, L3 and L2 edges. Bottom: Influence of the deconvolution on the ratio of the orbital and spin magnetic moments extracted using EMCD sum rules. The plural scattering is parametrized by the ratio of plasmon peak and zero-loss peak area, k = AP P /AZLP . Figure adapted from [83]. see, e.g., [90] for a recent review of various methods of removing plural scattering effects from core-level EELS spectra. Since this correction needs to be applied to both spectra, which are subtracted, when constructing the EMCD spectrum, it was incorrectly assumed that plural scattering can be neglected in EMCD measurements. However, we will demonstrate that it is not the case [83]. Here we will briefly describe our findings. A typical low-loss spectrum has a so-called plasmon peak at energies 10-20 eV beyond the zero-loss peak, see schematic Fig. 13 (top part). By convolution of the low-loss spectrum with the L3 peak we broaden the L3 peak and form a shoulder at higher energy side. Similarly for the L2 peak. Note that the plural scattering involving excitation of a 2p3/2 core electron produces a shoulder, which actually overlaps with the L2 peak. This is the key observation for further

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analysis. Let’s imagine now the EMCD spectrum: it is composed of the difference of spectra at the L3 edge and at the L2 edge. The L3 edge difference is, to a good approximation, not influenced by plural scattering. To be more precise, it is broadened due to non-zero width of the zero-loss peak, but its area is practically unchanged. In contrast, the L2 edge difference contains also a fraction of L3 edge difference due to overlap of above-mentioned shoulder at higher energy loss side of L3 edge. Thus the L2 edge dichroic signal is suppressed by plural scattering. If we denote the ratio of area of the plasmon peak, AP P , and the zero-loss peak, AZLP , as k = AP P /AZLP , then we can approximately say that the L2 area is enhanced due to plural scattering by kAL3 , where AL3 is the area of the L3 peak. By inserting this into sum rules expressions, we obtain a relation between the “clean” mL /mS ratio (denoted u) and the observed one, when plural scattering effects are neglected (denoted u ˜) u ˜ = u =

(2L − 1)u + L(L − 1)k/3 + kLu 2L − 1 − kL − 3kuL/(L − 1) (2L − 1)˜ u − L(L − 1)k/3 − kL˜ u 2L − 1 + kL + 3k˜ uL/(L − 1)

(61) (62)

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which can be linearized for small k and u, u ˜. Particularly for the L2,3 edges (L = 2) we obtain   4k 2k u ˜ ≈ u 1+ + (63) 3 9   4k 2k u ≈ u ˜ 1− − (64) 3 9 The general relation, Eqn. (61), is plotted in the bottom part of the Fig. 13 for various values of k. When these relations are applied to quantitative measurements by Lidbaum et al. [8], performed on a bcc iron specimen of thickness 20 nm (value k ≈ 0.1), we obtain a corrected value mL /mS = 0.043 ± 0.01, which agrees excellently with Chen et al. [27]. More recent measurement also on bcc iron, but at different thickness of 10 nm, led to value 0.065 [72]. Since it is measured at lower thickness, the value of k is smaller. An estimate of k ≈ 0.05–0.07 leads to the same value as before, 0.045 ± 0.01. This is a very supportive argument for our theory of the quantitative influence of plural scattering on recent EMCD measurement. Therefore we suggest for future quantitative EMCD experiments, to always perform a measurement of low-loss spectra and to perform a deconvolution to remove the plural scattering, or at least, evaluate the value of k and perform an a posteriori correction of the obtained orbital to spin moment ratio [83].

6.

Conclusions and Outlook

In the short history of the EMCD method we have seen an impressive progress. In the time-span of only seven years since its proposal [91] we have witnessed its experimental and theoretical confirmation [1], formulation of first principles theory [2] and relevant sum rules [3, 4], dramatic improvements of spatial resolution [6, 5, 7, 76], first attempts of

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quantitative measurements [4, 71] up to development of data treatment methods allowing reliable quantitative EMCD measurements [8, 76, 72, 83]. Still, despite its obvious advantages over XMCD, EMCD remains being a technique used only by handful of labs worldwide. One might ask for possible reasons. We believe that there are two sources of difficulties. At its current state of the art, EMCD depends on 1) high-quality crystalline samples and on 2) stable and well controlled state of the microscope during the whole time of the measurement. There are obvious difficulties in sample preparations - strains, formation of small grains with relative mis-orientations, etc. What would be needed is some sort of generalization of the EMCD experiment, which would not place such high demands on the sample quality. From the instrumental point of view, there were attempts to split the electron beam to two coherent phase shifted beams before entering the sample. So far this approach was not yet successful due to various technical difficulties. Another option is a development of some more general data treatment procedures, which would not rely on dynamical diffraction so strongly as the current methods do. We imagine that an application of powerful statistical methods such as principal component analysis [92] or multivariate curve resolution [85] could bring fresh air to the data analysis and strengthen the position of EMCD as a routine magnetic characterization method. Regarding the stability of microscope conditions, there are several sources of error in the transmission electron microscope, such as sample drift, non-isochromaticity, difficulty to keep the sample orientation constant throughout the measurement time. These effects lead to a necessity to reduce the duration of signal acquisition. Thus an EMCD measurement is a fight for signal-to-noise ratio. There are numerical methods that can a posteriori correct for drifts and/or non-isochromaticity, nevertheless at the moment there is no available method to correct the data if the sample orientation changes during acquisition. Therefore, here we have to rely on progress in the development of instruments. Perhaps in a few years it will be a routine task to perform a TEM measurement of datacubes lasting for hours without worrying about drifts or tilts of the sample. To conclude, we hope that we succeeded to convey our main message to the reader: At the moment EMCD is still an experimental method with its infant’s ailments. Nonetheless, there are many reasons to believe that a fully developed EMCD technique can become one of the most flexible magnetic characterization tools.

References [1] P. Schattschneider, S. Rubino, C. H´ebert, J. Rusz, J. Kuneˇs, P. Nov´ak, E. Carlino, M. Fabrizioli, G. Panaccione, and G. Rossi. Detection of magnetic circular dichroism using a transmission electron microscope. Nature, 441(7092):486–488, 2006. [2] J. Rusz, S. Rubino, and P. Schattschneider. First-principles theory of chiral dichroism in electron microscopy applied to 3d ferromagnets. Phys. Rev. B, 75(21):214425, Jun 2007. [3] J. Rusz, O. Eriksson, P. Nov´ak, and P. M. Oppeneer. Sum rules for electron energy loss near edge spectra. Phys. Rev. B, 76(6):060408, Aug 2007.

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[4] L. Calmels, F. Houdellier, B. Warot-Fonrose, C. Gatel, M. J. H¨ytch, V. Serin, E. Snoeck, and P. Schattschneider. Experimental application of sum rules for electron energy loss magnetic chiral dichroism. Phys. Rev. B, 76(6):060409, Aug 2007. [5] B. Warot-Fonrose, F. Houdellier, M.J. Hytch, L. Calmels, V. Serin, and E. Snoeck. Mapping inelastic intensities in diffraction patterns of magnetic samples using the energy spectrum imaging technique. Ultramicroscopy, 108(5):393–398, 2008. [6] P. Schattschneider, C. H´ebert, S. Rubino, M. St¨oger-Pollach, J. Rusz, and P. Nov´ak. Magnetic circular dichroism in EELS: Towards 10 nm resolution. Ultramicroscopy, 108(5):433–438, 2007. [7] P. Schattschneider, M. St¨oger-Pollach, S. Rubino, M. Sperl, C. Hurm, J. Zweck, and J. Rusz. Detection of magnetic circular dichroism on the 2 nm scale. Phys. Rev. B, 78:104413, 2008. [8] H. Lidbaum, J. Rusz, A. Liebig, B. Hj¨orvarsson, P. M. Oppeneer, E. Coronel, O. Eriksson, and K. Leifer. Quantitative magnetic information from reciprocal space maps in transmission electron microscopy. Phys. Rev. Lett., 102(3):037201, Jan 2009. [9] Roland Wiesendanger. Scanning probe microscopy and spectroscopy: methods and applications. Cambridge University Press, 1994.

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[10] F. Meier, L. Zhou, J. Wiebe, and R. Wiesendanger. Revealing magnetic interactions from single-atom magnetization curves. Science, 320(5872):82–86, 2008. [11] G. van der Laan, B. T. Thole, G. A. Sawatzky, J. B. Goedkoop, J. C. Fuggle, J.-M. Esteva, R. Karnatak, J. P. Remeika, and H. A. Dabkowska. Experimental proof of magnetic x-ray dichroism. Phys. Rev. B, 34(9):6529–6531, Nov 1986. [12] G. Sch¨utz, R. Wienke, W. Wilhelm, W. Wagner, P. Kienle, R. Zeller, and R. Frahm. Strong spin-dependent absorption at the L2,3 -edges of 5d-impurities in iron. Z. Phys. B-Condens. Mat., 75(4):495–500, 1989. [13] J. St¨ohr. Exploring the microscopic origin of magnetic anisotropies with x-ray magnetic circular dichroism (xmcd) spectroscopy. Journal of Magnetism and Magnetic Materials, 200(1-3):470–497, 1999. [14] B. T. Thole, P. Carra, F. Sette, and G. van der Laan. X-ray circular dichroism as a probe of orbital magnetization. Phys. Rev. Lett., 68(12):1943–1946, Mar 1992. [15] G. van der Laan. Angular momentum sum rules for x-ray absorption. Phys. Rev. B, 57(1):112–115, Jan 1998. [16] A. Scholl, J. St¨ohr, J. L¨uning, J. W. Seo, J. Fompeyrine, H. Siegwart, J.-P. Locquet, F. Nolting, S. Anders, E. E. Fullerton, M. R. Scheinfein, and H. A. Padmore. Observation of antiferromagnetic domains in epitaxial thin films. Science, 287(5455):1014– 1016, 2000.

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In: Circular Dichroism: Theory and Spectroscopy Editor: David S. Rodgers

ISBN: 978-1-61122-522-8 2012 Nova Science Publishers, Inc.

Chapter 4

APPLICATION OF CIRCULAR DICHROISM TO LIPOPROTEINS: STRUCTURE, STABILITY AND REMODELING OF GOOD AND BAD CHOLESTEROL Xuan Gao, Shobini Jayaraman, Jeremiah Wally, Madhumita Guha, Mengxiao Lu, David Atkinson, and Olga Gursky* Department of Physiology and Biophysics, Boston University School of Medicine, Boston MA, US

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Lipoproteins are water-soluble non-covalent assemblies comprised of several proteins (termed apolipoproteins) and several hundred lipid molecules. These assemblies mediate transport and metabolism of lipids and are central to the development of major human diseases, most notably atherosclerosis. Plasma lipoproteins are divided into classes according to particle size, density, composition and function. High-density lipoproteins (HDL, or Good Cholesterol, d=8-13 nm) mediate cholesterol removal from the peripheral tissues, and low-density lipoproteins (LDL, or Bad Cholesterol, d=22 nm) mediate cholesterol delivery. The balance between LDL and HDL determines the risk of developing atherosclerosis. Compositional and structural heterogeneity as well as the large size of lipoproteins have hindered their high-resolution structural studies. Lowresolution methods such as circular dichroism (CD) have been extensively used for studies of lipoprotein structure and stability. Far- and near-UV CD in conjunction with site-directed mutagenesis has been used to assess apolipoprotein conformation in solution and on lipoproteins. In addition, thermal denaturation data recorded by far- and near-UV CD, together with turbidity and light scattering measurements in CD experiments, have been instrumental in uncovering kinetic mechanism of lipoprotein stabilization in vitro and in linking it to metabolic lipoprotein remodeling in vivo. This chapter describes the application of CD spectroscopy to the analysis of apolipoprotein conformation and to *

Corresponding author: Olga Gursky, Department of Physiology and Biophysics, Boston University School of Medicine, W329, 700 Albany Street, Boston MA, 02118; Tel. (617) 638-7894; FAX (617) 638-4207; E-mail: [email protected];Funding: This work was supported by the National Institutes of Health grants HL026355 and GM067260.

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Xuan Gao, Shobini Jayaraman, Jeremiah Wally et al. studies of structural stability and remodeling of the major lipoprotein classes, including nascent reconstituted HDL (rHDL) as well as mature high-, low-, and very low-density lipoproteins from human plasma. The results demonstrate the power of CD spectroscopy coupled with other biophysical techniques, such as light scattering, electron microscopy, and differential scanning calorimetry, for the analysis of complex structural transitions in heterogeneous macromolecular assemblies.

Keywords: high-density lipoprotein, low-density lipoprotein, very low-density lipoprotein, light scattering, turbidity, kinetic stability, lipid-lowering drugs, atherosclerosis

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ABBREVIATIONS HDL rHDL LDL VLDL apo PC Ch CE TG LCAT CD LS DSC EM T-jump TFE BOG CMC Gdn HCl

high-density lipoprotein; reconstituted high-density lipoprotein; low-density lipoprotein; very low-density lipoprotein; apolipoprotein; phosphatidylcholine; cholesterol; cholesterol ester; triacylglyceride; lecithin:cholesterol acyltransferase; circular dichroism; light scattering; differential scanning calorimetry; electron microscopy, temperature jump, trifluoroethanol; -octyl-glucopyranoside; critical micelle concentration; guanidine hydrochloride.

INTRODUCTION TO LIPOPROTEINS Plasma Lipoproteins and their Constituents The plasma lipoproteins are water-soluble non-covalent assemblies (d=10-100 nm) comprised of specific proteins termed apolipoproteins (apo) and lipids. The polar lipoprotein surface is formed of amphipathic proteins and lipids, mainly phosphatidylcholines (PC) and cholesterol (Ch), while the apolar lipids, mainly cholesterol esters (CE) and triacylglycerides (TG), are sequestered in the core (Figure 1, 2). These assemblies solubilize lipids and mediate their transport and metabolism. Dysregulation of the lipoprotein metabolism is central to the development of human diseases such as coronary artery disease and stroke, which are the major killers in the developed world [Havel & Kane, 2001; Zannis et al., 2004].

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Figure 1. Cartoon representation of nascent ―discoidal‖ and plasma ―spherical‖ HDL. Nascent HDL, that are comprised of exchangeable apolipoproteins and polar lipids (mainly phospholipids and cholesterol), are remodeled by lecithin:cholesterol acyltransferase (LCAT). Apolar molecules of cholesterol ester produced by LCAT move from the particle surface to its interior, leading to HDL maturation into small spherical particles containing a core of cholesterol esters (CE) and a small amount of triacylglycerides (TG).

Figure 2. Representative lipid constituents of plasma and model lipoproteins used in this chapter.

Plasma lipoproteins form several classes that have distinct particle size, density, composition and function. Since proteins, which are heavier than lipids, are located at the particles surface, smaller lipoproteins have higher density. High-density lipoproteins (HDL, Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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or Good Cholesterol, d=8-13 nm) mediate cholesterol removal from the peripheral tissues via the reverse cholesterol transport pathway, and low-density lipoproteins (LDL, or Bad Cholesterol, d=22 nm) mediate cholesterol delivery. Abundant evidence suggests that the balance between LDL and HDL determines the risk of developing atherosclerosis ([Fielding & Fielding, 1995; Tall, 1998; Barter & Rye, 2007] and references therein). In addition, very low-density lipoproteins (VLDL, d=30-100 nm) are metabolic precursors of LDL and an independent risk factor for atherosclerosis [Skalen et al., 2002; Oloffson & Boren, 2005; Kanel & Vasan, 2009]. The main focus of this chapter is on HDL and its apoproteins.

Figure 3. Schematic representation of the sequence arrangement of the repeated putative -helical motifs of apoA-I, apoA-II, apoC-I, peptide models, and consensus sequence peptides showing the regions encoded by exon 3 and 4 in the gene. The lower part of the figure illustrates helix wheel representations of the sequence of apoA-I residues 101-120, apoA-II residues 51-70, and the consensus sequence of the AB tandem repeat. Acidic residues (red), basic residues (blue), apolar residues (yellow) and polar uncharged residues (white). The putative helix distributions are from [Segrest et al., 1992]. The motif repeats are from [Nolte & Atkinson, 1992].

Plasma HDL form a heterogeneous population of particles that originate from the liver [Hamilton et al., 1976] and intestine [Green et al., 1978]. The anti-atherogenic action of HDL

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and its major protein, apoA-I, mainly results from their role in reverse cholesterol transport pathway. In this pathway, apoA-I in lipid-poor form interacts with the ABC-A1 transporter that mediates the efflux of phospholipids and cholesterol from peripheral cells, leading to formation of nascent ―discoidal‖1 HDL [Dufort & Chimini, 2007; Rye & Barter, 2004; Duong et al., 2006]. ApoA-I on these HDL serves as a cofactor of lecithin cholesterol acyltransferase (LCAT) [Fielding et al., 1972; Fielding & Fielding, 2007]. LCAT converts amphipathic molecules of cholesterol into apolar molecules of CE that move from the particle surface to its interior, thereby converting the nascent ―discoidal‖ to mature ―spherical‖1 HDL (Figure 1). ApoA-I on spherical particles provides the ligand for the scavenger receptor, SR-BI, that mediates selective uptake of CE from HDL by the liver [Acton et al., 1998; Krieger, 1999; Harder & McPherson, 2007]. In addition to apoA-I, other apolipoproteins (apoA-II, E, Cs) are found in small amounts on HDL and can modulate HDL metabolism. All these proteins are exchangeable (water-soluble) and can transfer among plasma lipoproteins. Furthermore, all these proteins are predominantly -helical and hence, are well- suited for CD spectroscopic analysis. In this chapter, we report CD studies on model ―discoidal‖ and plasma ―spherical‖ HDL containing human apoA-I, A-II or C-I. LDL are the major plasma carriers of cholesterol in the form of CE. Plasma concentrations of LDL cholesterol and, particularly, of the major LDL protein, apoB, are the strongest predictors of the risk of atherosclerosis [Havel & Kane, 2001]. In contrast to smaller exchangeable proteins that are highly -helical, apoB (4536 a. a., which is one of the largest known proteins) is comprised of both amphipathic -helices and -sheets and is permanently associated with the host particle, i. e., is non-exchangeable [Olofsson & Boren, 2009; Cladaras et al., 1986]. Each particle contains one copy of apoB that forms a ligand for LDL receptor. LDL receptor is expressed in various cells, including peripheral cells that require cholesterol, as well as liver cells. LDL are taken up by these cells via the receptor-mediated whole-particle endocytosis [Brown & Goldstein, 1986; Goldstein et al., 1985]. VLDL, which are major plasma carriers of TG, are secreted by the liver and are direct metabolic precursors of LDL (for recent reviews see [Oloffson & Boren, 2009; Havel, 2010]). High plasma levels of TG and VLDL are a hallmark of metabolic syndrome that is associated with increased risk of diabetes and atherosclerosis. Each VLDL particle contains one copy of apoB and multiple copies of the exchangeable proteins, apoE and apoCs. ApoB and apoE direct VLDL to its receptor, while apoCs modulate VLDL remodeling, such as the lipaseinduced transformation of VLDL into LDL. In this chapter, we report CD studies of human plasma LDL and VLDL differing in the particle size and composition. The apolipoproteins fulfill two major roles on lipoproteins. In their structural role, these proteins are responsible for the assembly and structural integrity of the lipoprotein particle. In their functional role, they act as co-factors for enzymes (such as LCAT and lipases) and as ligands for cellular receptors that are central to lipid transport and metabolism. The exchangeable apolipoproteins (apoA-I, A-II, E and C-I/II/III) share a common genetic origin. These proteins have evolved from an ancestral gene closely related to the apoC-I gene [Luo et al., 1986]. Hence, apoC-I, the smallest human apolipoprotein (57 a. a.), provides a genetic, structural and functional prototype for this protein family. The sequences of the exchangeable apolipoproteins contain tandem 11/22-residue repeats, punctuated by Pro, which are postulated to form lipid surface-binding amphipathic helices. Similar 11-mer repeats are found in synucleins that also bind to lipid surface [Bussell & Eliezer, 2003]. In

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apolipoproteins, the 22-residue repeats are classified into 11-residue sub-repeats A and B [Segrest et al., 1992]. The canonical ―class-A‖ amphipathic helix has a large apolar face that subtends 120-180o, with basic residues positioned at the apolar-polar interface and acid residues in the middle of the polar face (Figure 3). The apolar faces can form protein-protein interactions in solution as well as protein-lipid interactions on the lipid surface.

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Apolipoprotein A-I ApoA-I (243 a. a.) is synthesized in the liver and intestine. The first 43 residues are encoded by exon 3, and the rest of the molecule, including 10 copies of the tandem 11- or 22residue repeats, is encoded by exon 4 (Figure 3). ApoA-I can exist in the lipid-free (or lipidpoor) state in solution or in association with HDL. Hence, this protein has an adaptable conformation comprised from the amphipathic -helices that form flexible tertiary structure. Far- and near-UV CD spectroscopy coupled with other biophysical techniques helped elucidate the molten globule-like properties of apoA-I and other exchangeable proteins in solution and relate these properties to the lipid surface-binding function of these proteins [Gursky & Atkinson, 1996 (I); Gursky & Atkinson, 1996 (II); Soulages & Bendavid, 1998; Weers et al., 2001; Morrow et al., 2002]. Sequence analysis [Nolte and Atkinson, 1992], crystal structure of (1-43)apoA-I deletion mutant [Borhani et al., 1997], NMR assignments [Cushley & Okon, 2002], and H-D exchange [Chetti et al., 2009] have inferred different helical positions with different flexible regions for apoA-I in the lipid-free state. These differences probably reflect structural adaptability of apoA-I whose alternative conformations are depicted by different structural probes. Segment deletion and point mutations have been designed to elucidate the conformation and function for each putative helical segment [Gorshkova et al., 2000, 2002, 2006; Fang et al., 2003; Rogers et al., 1997, 1998 (I, II)]. The N-terminal region (residues 159), whose structure is not well-defined, stabilizes the lipid-free apoA-I conformation [Rogers et al., 1997; Fang et al., 2003 Zhu & Atkinson, 2004;]. The central region (residues 60-184), which contains well-defined putative amphipathic -helices, is important for LCAT activation and lipid binding [Sorci-Thomas et al., 1997 (I, II), 1998]. The C-terminal region (residues 185-243) is highly hydrophobic and is proposed to contain the primary lipid-binding site in apoA-I [Saito et al., 2003; Zhu & Atkinson, 2007] and several other exchangeable proteins [Saito et al., 1998]. In this chapter, we report CD studies of the peptide fragments from the central region of apoA-I.

Peptide Models of the Exchangeable Apolipoproteins Synthetic peptide fragments and designed model peptides have been used to determine structural and functional properties required for lipid binding or LCAT activation. These studies demonstrated the importance of helix length, Pro punctuation and charge distribution in protein binding to lipid surface [Anantharamaiah et al., 1985; Posin et al., 1984; Posin et al., 1986 (II); Chung et al., 1985].

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NMR structures of several peptide models of apoA-I [Mishra et al., 1998; Wang et al., 1997], apoE [Wang et al., 1996, Clayton et al., 1999], and apoCs [Rozek et al., 1999; Buchko et al., 1997] have been determined in complexes with SDS or DPC micelles. The predominant peptide conformation observed in these complexes is helix-kink-helix with frayed termini. Alternative conformations, such as helix hairpin, have also been detected [Rozek et al., 1999]. However, it is unclear whether the small micelles used in these studies, particularly the charged SDS complexes, provide accurate models for lipoproteins. Our own studies have concentrated on 44-residue peptides representing different segments of apoA-I, together with ―idealized‖ consensus sequence peptides (Figure 3). We have defined the structural, stability and lipid binding properties of the N- and C-terminal peptides and showed that the results are consistent with our mutational studies of apoA-I [Zhu & Atkinson, 2004, 2007]. Based on the sequence homology among apoA-I, E and A-IV, we derived a 22-residue consensus sequence, AB (Figure 3) [Nolte & Atkinson, 1992]. The two 11-mers, A (PLAEELRARLR) and B (AQLEELRERLG), have six common residues and similar charge distributions. Both repeats have high helical propensities by sequence analysis, but the B-A junction has the highest turn probability due to Pro at the beginning of repeat A. Three 44mer peptides, ABAB, BABA and ABBA, reflecting different 11-mer arrangements in apoA-I sequence (Figure 3), have been studied. ABAB showed the highest α-helical content in solution (~80% as compared with 30-50% in other peptides) and was probably composed of two antiparallel α-helices connected by a Pro-containing turn. Molecular dynamics simulations [Luo, 2008] and 2D NMR [Zang et al., 1995] suggested that ABAB adopts a loose helix-turn-helix conformation. Our X-ray crystallographic studies of ABAB have substantiated that the helix-turn-helix motif is the basis of the crystal structure of this peptide [Chao, 2002] and, probably, other exchangeable apolipoproteins in solution.

CD STUDIES OF LIPOPROTEINS: ADVANTAGES AND LIMITATIONS Light Scattering of Lipoproteins in CD Experiments Application of CD to secondary structural analysis of lipoproteins is complicated by the light scattering (LS) of these large particles. Lipoprotein diameters, that range from about 10 nm in HDL to 22 nm in LDL and 30-100 nm in VLDL, are comparable to the wavelength of far-UV radiation (~200 nm), leading to significant LS effects in far-UV CD experiments [Mao & Wallace, 1984]. These effects, compounded by the spectral contributions from the lipids [Chen & Kane, 1986], distort far-UV CD spectra of lipoproteins and lead to systematic errors in protein secondary structural estimates from these spectra. These errors, which are difficult to correct for, are minimal for HDL-size particles but increase with increasing particle size and lipid content that ranges from about 50% in HDL to 80% or more in LDL and VLDL [Mao & Wallace, 1984; Chen & Kane, 1986]. Therefore, we limit far-UV CD analysis of these particles to qualitative assessment of secondary structural changes induced by variations in internal conditions, such as protein and lipid composition, or external conditions, such as buffer composition and temperature.

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Light scattering effects in CD experiments are not only a limitation but also a valuable tool for monitoring heat-induced changes in macromolecular size. For example, simultaneous measurements of CD and LS are useful to assess heat-induced protein aggregation, which underlies irreversible thermal unfolding or misfolding of a wide range of proteins [Benjwal et al., 2006]. Another example is concomitant measurement of CD and turbidity to monitor thermal denaturation of lipoproteins. Such measurements helped reveal that lipoprotein denaturation involves not only unfolding of the protein secondary structure (observed by farUV CD) but also partial dissociation of the protein from the lipoprotein surface and the ensuing lipoprotein fusion (detected by turbidity, electron microscopy (EM), and nondenaturing gel electrophoresis) [Gursky et al., 2002]. Furthermore, fusion of the corecontaining lipoproteins is followed by their rupture and release of the apolar core lipids that coalesce into large droplets; formation of such droplets was detected by EM and was monitored in real time by near-UV CD and turbidity/LS [Mehta et al., 2003; Jayaraman et al., 2005 (I); Guha et al., 2007]. Simultaneous measurements of CD and LS/turbidity not only save time and sample but also greatly increase the accuracy in correlating microscopic changes (such as protein unfolding monitored by CD) with the macroscopic changes (such as increase in the particle size due to protein aggregation or lipoprotein fusion monitored by LS). In this chapter, we illustrate the application of LS /turbidity measurements in far- or near-UV CD experiments for the analysis of the heat-induced structural transitions in lipoproteins. Turbidity and LS can be conveniently recorded in CD experiments to monitor changes in the particle size. Light scattering is recorded by using the total fluorescence accessory in spectropolarimeters such as AVIV or Jasco. This accessory contains an additional UV detector that is oriented at 90o to the direct beam and is operated without filters to record right-angle LS [Benjwal et al., 2006]. Although such LS measurements are insufficient to determine the particle size on the absolute scale (to do so, a dedicated multiangle LS instrument is required), they are very useful to monitor in real time relative changes in the particle size. Similar information can be obtained by using dynode voltage in CD experiments. Dynode voltage is the high voltage (102-103 V) applied to the photomultiplier of the CD detector to compensate for the reduction in intensity of the direct beam. Such a reduction may occur due to increased light absorption or scattering; the latter reflects an increase in the particle size and/or refractive index. During thermal denaturation, the chemical composition of a sample remains invariant and hence, UV absorption is nearly invariant. Therefore, any significant changes in turbidity or LS must originate from the changes in the particle size (which may result from protein aggregation or lipoprotein fusion) or in the refractive index (which may accompany lipid phase transitions). Hence, dynode voltage in CD experiments is proportional to turbidity. We use both LS and turbidity to monitor thermal denaturation of lipoproteins. The results, taken together with the corresponding far- or near-UV CD data, are used to dissect the pathways of apolipoprotein interactions with the lipid surface [Benjwal et al., 2007]. Especially useful are the measurements of turbidity/LS during heating of VLDL, since strong LS by these large particles further increases upon their fusion, rupture and coalescence into lipid droplets [Guha et al., 2007]. These effects enabled us to perform the first quantitative analysis of VLDL stability by using turbidity measurements in kinetic CD experiments [Guha et al., 2007].

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Studies of Lipoprotein Stability in Kinetic CD Experiments Kinetic mode in conventional CD spectropolarimeters is useful to monitor the time course of slow transitions that occur on a scale of minutes to hours. Faster transitions are difficult to follow because of the limited time resolution of conventional CD instruments [Chen et al., 2010]. This leads to relatively long dead time in kinetic CD experiments (10 sec), which is the time it takes to accumulate one data point under equilibrium conditions. CD analysis of very slow transitions is limited by the instability of the UV/vis Xenon lamp, which causes baseline drift over time. As a result, the transition time constants that can be reliably measured by using a kinetic mode in conventional CD spectrometers range from about 102105 sec. This is many orders of magnitude longer than the sub-microsecond time scale reported for unfolding of small -helical proteins ([Kubelka et al., 2004] and references therein), such as exchangeable apolipoproteins in solution. Therefore, the unfolding kinetics of such proteins is not amenable to conventional CD analysis and calls for fast-response techniques such as time-resolved CD and fluorescence. Remarkably, compared to the fast unfolding of helical proteins in solution, the unfolding of exchangeable apolipoproteins in lipoproteins is slower by at least 10 orders of magnitude, which is well suited for the kinetic CD analysis. This slowdown occurs because, in lipoproteins such as HDL, protein unfolding leads to transient disruption of multiple protein and lipid interactions during partial dissociation of the unfolded protein from the lipid surface and the ensuing particle fusion [Gursky et al., 2002; Mehta et al., 2003; Jayaraman et al., 2005 (II)]. Importantly, similar protein dissociation and particle fusion events occur during metabolic remodeling of HDL by plasma factors [Mehta et al., 2003; Guha et al., 2008] (Figure 4). Therefore, lipoprotein denaturation provides a tractable model for quantitative analysis of kinetic barriers that modulate metabolic remodeling of plasma lipoproteins in vivo and in vitro. CD spectroscopy is uniquely suited for measuring these barriers in kinetic experiments, such as the denaturant-jumps [Mehta et al., 2003] or temperature-jumps (Tjumps) described below. In this chapter, we illustrate the applications of CD spectroscopy to structural and stability studies of apolipoproteins in solution and on lipoproteins. This includes: apolipoproteins and their peptide models and fragments in aqueous solution (Results, part 1); ―discoidal‖11 complexes reconstituted from these proteins and polar lipids (rHDL), which mimic nascent HDL (part 2); and ―spherical‖1 core-containing lipoproteins, including human plasma HDL, LDL and VLDL (part 3).

1

We use the terms ―discoidal‖ for nascent HDL comprised of proteins and polar lipids, and ―spherical‖ for mature lipoproteins that, in addition to proteins and polar lipids in their surface, contain an apolar lipid core. These operational terms are not intended to describe the actual particle shape. Lipoprotein shape probably deviates from either disk or sphere and, according to several EM reports, can be approximated by a distorted ellipsoid ([Zhang et al., 2010] and references therein).

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Figure 4. Major subclasses of high-density lipoproteins and the free energy barriers separating these subclasses: cartoon representation (top) and electron micrographs (bottom). At an early step of reverse cholesterol transport, nascent ―discoidal‖ HDL are remodeled by LCAT leading to HDL maturation into small spherical particles containing a core of cholesterol esters. These small particles undergo further remodeling by LCAT and other plasma factors, such as cholesterol ester and phospholipid transfer proteins. This causes an imbalance between the core and surface of the particle, which can be resolved via fusion of small HDL3 into larger HDL2 particles and dissociation of lipid-poor apoA-I. The putative high-energy transition state of HDL fusion is illustrated. At the last step of reverse cholesterol transport, HDL disintegrate and their apolar core lipids are taken up by the hepatic HDL receptor while the apolipoproteins are recycled or catabolized. Similarly, apolipoprotein dissociation and HDL fusion followed by rupture and release of apolar lipids occur during thermal or chemical denaturation, as illustrated in the electron micrographs of negatively stained HDL (bottom). Bottom panels show (left to right): model ―discoidal‖ rHDL reconstituted from human apoA-I, POPC , and cholesterol (I); human plasma HDL3 that are intact (II) or have been fused (III) or ruptured upon heating, which led to lipid coalescence into large droplets (III).

RESULTS AND DISCUSSION 1. Solution Conformation of Peptide Fragments of ApoA-I We used far-UV CD to characterize two overlapping 44-residue peptides corresponding to putative helices 4 and 5 (residues 99-142) and 5 and 6 (residues 121-164) from the central region of apoA-I (Figure 3). The peptide structure and stability were analyzed in aqueous solution (10 mM Na phosphate buffer, pH 7.4) and in a similar solution containing the helixinducing organic solvent, trifluoroethanol (TFE), or a lipid-mimicking detergent, -octylglucopyranoside (BOG). The goal was to assess the helical propensity of individual segments in apoA-I and their potential interactions in various environments.

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Figure 5. Far-UV CD spectra of peptide fragments [99-142]apoA-I (left) and [121-164]apoA-I (right) in aqueous solution. The spectra were recorded from peptide solutions of 0.01 to 0.50 mg/mL concentration in 10 mM Na phosphate buffer at pH 7.4, 25 °C. The spectra were averaged over 3 scans and normalized to peptide molar residue concentration; data at 0.50 mg/mL were truncated below 207 nm.

Figure 6. Far-UV CD spectra of peptide fragments [99-142]apoA-I (left) and [121-164]apoA-I (right) in the presence of helix-inducing agent, TFE. The spectra were recorded from peptide solutions containing 10 to 70% TFE in 10 mM Na phosphate buffer at pH 7.4, 25 °C, averaged over 3 scans, and normalized to peptide concentration.

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Figure 7. Far-UV CD data of peptide fragments [99-142]apoA-I (left) and [121-164]apoA-I (right) in the presence of non-ionic detergent, BOG. The spectra were recorded from solutions of 0.05 mg/mL peptide concentration containing 0.0 to 0.7% (top) and 0.8 to 3.0 (middle) BOG as described in Figure 6 legend. Percent -helical content calculated from [222] as a function of BOG concentration (bottom). The best fit line was determined using a sigmoidal fit for all data points; error bars represent deviations among different data sets.

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Figure 8. Far-UV CD heating data recorded of [99-142]apoA-1 (left) and [130-162]apoA-1 (right) in the presence of 0.0 to 2.0% BOG. The samples were heated from 0 to 100 °C at a rate of 50 oC/h, and changes in the -helical structure were monitored by CD at 222 nm. Buffer conditions are as in Fig. 7.

Far-UV CD spectra were recorded at 25 °C from buffered solutions of [99-142]apoA-I or [121-164]apoA-I at peptide concentrations ranging from 0.01 to 0.50 mg/mL (Figure 5). The spectra were typical of small peptides that have helical propensity but are largely unfolded in solution. Helical content, which was estimated from the molar residue ellipticity at 222 nm, [222], according to [Mao & Wallace, 1984], was about 25% for [99-142]apoA-I and about 13% for [121-164]apoA-I. Changes in peptide concentration from 0.01 to 0.5 mg/mL did not result in significant spectral changes, indicating that the peptide self-association at these concentrations did not induce additional helical structure. To induce helical structure, we used a helix-promoting solvent, TFE [Jirgensons & Ross, 1982]. Far-UV CD spectra of the peptides indicated a progressive increase in the helical content upon increasing TFE concentration from 10 to 70% vol/vol (Figure 6). In [99142]apoA-I, this increase was nearly linear, reaching ~75% -helix in 70% TFE. In [121164]apoA-I, the helical content increased non-linearly, reaching saturation at ~50% -helix in 70% TFE. (Figure 6). These results suggest that [99-142]apoA-I has higher helical propensity than [121-164]apoA-I. To assess peptide conformation on the lipid, we used a mild non-ionic detergent, BOG. Earlier studies showed that apolipoprotein binding to the detergent micelles induces helical structure similar to that in protein:phospholipid complexes. Far-UV CD spectra were recorded from 0.05 mg/mL peptide solutions containing 0-3 % BOG at 25 °C (Figure 7). Below its critical micelle concentration (CMC), which is 0.65% at 25 oC [Garavito, 1991], BOG had little effect on the peptide conformation (Figure 7, top). However, between 0.6 and 1.5 % BOG, a marked increase in the peptide helical content was observed (Figure 7, middle). This increase clearly paralleled micelle formation by BOG (Figure 7, bottom). Therefore, helical structure was induced by peptide interactions with micellar, but not monomeric, detergent.

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Again, the maximal helical content observed in the presence of BOG was higher in [99142]apoA-I as compared to [121-164]apoA-I, 50% versus 36% -helix. Hence, BOG induced less helical structure than TFE; also, the helix content was higher in [99-142]apoA-I than in [121-164]apoA-I under any solvent conditions explored. To test the thermal stability of this helical structure, the buffered solutions of 0.05 mg/mL peptide concentration containing 0-3% BOG were heated and cooled from 0-100 oC at a constant rate, and changes in the peptide helical content were monitored by CD at 222 nm, 222(T) (Figure 8). Heating above room temperature led to low-cooperativity unfolding of the helical structure, which is characteristic of small peptides. The unfolding was fully reversible, as evident from the overlapping heating and cooling data. Interestingly, cooling below room temperatures also induced helical unfolding at BOG concentrations between 0.8 and 1.2%. This reflects dissociation of the BOG micelles at low temperatures. In fact, the CMC of BOG is higher at low temperatures [Miguel et al., 1989], i.e., more detergent is needed to form the micelles because of weakened hydrophobic effect at low temperatures [Schellman, 1997]. Hence, in a detergent solution at near-CMC concentration, cooling shifts the equilibrium from the micelles towards the monomeric detergent. This is accompanied by the loss of the micelle-induced helical structure of the peptide at low temperatures (Figure 9).

Figure 9. Effect of temperature on the peptide conformation in the presence of BOG near its critical micelle concentration. The helical content of [99-142]apoA-1 in 1.0% BOG as a function of temperature monitored by CD at 222 nm (bottom) and the cartoon representation of the temperaturedependent changes in the peptide-BOG association. BOG is shown in blue (monomers or spherical micelles) and the peptide is in red; cylinders show -helices.

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Figure 10. Free energy diagram and EM data illustrating heat- or denaturant-induced fusion of nascent ―discoidal‖ HDL into larger particles (such as multilamellar vesicles) accompanied by dissociation of lipid-poor apolipoprotein. The high-energy transition state in ―disk‖ fusion is illustrated. Left EM panel show negatively stained intact ABAB:DMPC complexes face-up or stacked on edge (left). Such stacking, depicted in a cartoon, is an artifact of negative stain preparation [Zhang et al., 2010]. Right EM panel shows the same sample upon heating and cooling from 25-95 oC, which led to multilamellar vesicle formation.

Low-temperature unfolding with dissociation observed in peptide:micelle complexes (Figure 8, 9) is reminiscent of low-temperature unfolding with dissociation observed by CD in the self-associated forms of apoC-I [Gursky & Atkinson, 1998] and of the C-terminal fragment of apoA-I [Zhu & Atkinson, 2007]. In larger marginally stable proteins, lowtemperature unfolding without dissociation has been reported for many molten globule-like proteins, including apoA-II [Gursky & Atkinson, 1996 (II)]. In contrast, model and plasma lipoproteins show no cold denaturation. Furthermore, in contrast to reversible -helical unfolding in free apolipoproteins or peptides and in peptide:micelle complexes, helical unfolding in lipoproteins is thermodynamically irreversible [Gursky et al., 2002; Mehta et al., 2003]. Hence, even though apolipoproteins acquire similar helical structure upon binding to BOG micelles and to lipid surface, the structural stability of the resulting complexes is very different. The rest of this chapter is devoted to analyses of structural stability of model and plasma lipoproteins.

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Figure 11. Far-UV CD spectra and chemical unfolding data of apolipoprotein A-I in rHDL. Singledonor HDL and other plasma lipoproteins used in our work were isolated by density centrifugation [Schumaker& Puppione, 1986] from plasma of healthy volunteer donors according to the rules and regulations of the Institutional Review Board. ApoA-I was isolated from these HDL and refolded as described [Gursky & Atkinson, 1996 (I)]. The apoA-I:POPC:Ch complexes containing 10 mol % unesterified cholesterol (Ch) were reconstituted by cholate dialysis and characterized by non-denaturing gel electrophoresis and EM [Jayaraman et al., 2010]. (A) Far-UV CD spectra were recorded from these complexes at 25 oC (pink circles). Sample conditions are 10 µg/mL protein in standard buffer (10 mM Na phosphate, pH 7.6). CD spectrum of lipid-free human apoA-I recorded under identical conditions is shown for comparison (black line). Insert: Negative stain electron micrographs recorded as described [Jayaraman et al., 2010] show apoA-I:POPC:Ch complexes face-up or stacked on edge. (B) Chemical denaturation of apoA-I:POPC:Ch complexes monitored by far-UV CD. Stock solution of 8 M GdnHCl in standard buffer was titrated into the rHDL sample (initial sample conditions same as in panel A). An automated titrator was used with 0.05 M concentration step, 0.5 min stir time, 30 s signal averaging time, and 1.8 mL constant sample volume. Protein -helical unfolding at 25 oC was monitored by CD at 222 nm, 222.

2. Structural Stability of ―Discoidal‖ Reconstituted High-density Lipoproteins (rHDL) Similar to folding/unfolding of many small water-soluble proteins, apolipoprotein unfolding in solution in the absence of aggregation is thermodynamically reversible. This reversibility manifests itself as the absence of the hysteresis in the thermal and chemical denaturation data recorded by such methods as differential scanning calorimetry (DSC), CD spectroscopy, etc. Moreover, in thermodynamically reversible transitions the denaturation data are independent of the rate at which the experiments are conducted (such as the heating rate in thermal unfolding or the incubation time in chemical unfolding). Thermodynamic reversibility is a consequence of a relatively smooth energy landscape between the folded and

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unfolded protein states, which is characteristic of structurally simple systems. In contrast, large macromolecular assemblies are often characterized by complex energy landscapes containing kinetic traps and barriers that are proposed to provide structural stabilization and functional optimization to these assemblies [Plaza del Pino et al., 2000; Sanchez-Ruiz, 2010]. Our CD/LS studies indicate that lipoproteins present an example of macromolecular assemblies whose structural stability and functional remodeling are modulated by kinetic barriers (Figure 4). For example, CD studies of discoidal rHDL showed that the native and denatured states of rHDL are separated by high kinetic barriers that decelerate protein unfolding, rendering it thermodynamically irreversible [Gursky et al., 2002; Jayaraman et al., 2005 (II)]. Such barriers arise from the partial dissociation of the unfolded proteins from the rHDL surface, leading to rHDL fusion into vesicles (Figure 10). Particle fusion reduces surface-to-volume ratio and thereby compensates for the loss of the polar surface component The basic premise for the kinetic stability of lipoproteins is illustrated in Figures 11-13 showing CD and LS data recorded of discoidal rHDL. Figure 11A shows far-UV CD spectra of the major HDL protein, human apoA-I, that is free in solution or reconstituted in complexes with POPC and 10 mol % of unesterified cholesterol (Ch). Such rHDL, which were reconstituted and characterized as described ([Jayaraman et al., 2010] and references therein), provide useful models for nascent plasma HDL that also contain apoA-I as their major protein, unsaturated PCs such as POPC as their major lipids, and up to 10 mol % Ch ([Duong et al., 2006] and references therein). On the basis of the CD spectra in Figure 11A, -helix content is estimated to be about 60% in lipid-free apoA-I in solution, and about 80% in apoA-I:POPC:Ch complexes, with the remaining structure being largely unordered. The helical structure in rHDL unfolds upon chemical denaturation. This is illustrated in Figure 11B showing guanidine hydrochloride (Gdn HCl) denaturation data of apoAI:POPC:Ch complexes monitored by CD at 222 nm for helix-to-coil transition. For a typical globular protein that undergoes a cooperative two-state unfolding, the Gdn HCl titration curve is sigmoidal with the inflection point corresponding to zero thermodynamic stability, G1/2 =RTln Keq=0; here, Keq=[U]/[F] is equilibrium constant between the unfolded and folded states with respective concentrations [U] and [F]. The data in Figure 11B represent just an upper segment of such a sigmoidal curve and do not show an inflection point. For a thermodynamically reversible transition this implies that in the denaturant-free buffer the protein unfolding is at least half-way over, i.e. [U][F], G0, and hence the -helical content in rHDL proteins cannot exceed 50%. This is at odds with the high -helical content in apoA-I (~80%) indicated by the far-UV CD spectrum of rHDL (Figure 11A). Moreover, prolonged lipoprotein incubation with Gdn HCl leads to progressive protein unfolding, resulting in a shift of the titration curve to lower denaturant concentrations, which implies even lower thermodynamic stability, GbufferLDL>HDL, and with increasing size of the lipid droplets formed upon release of its core lipids. We conclude that the induced negative CD peak centered at 310-320 nm reflects re-packing of apolar lipids, such as cholesterol esters and triglycerides, upon their release from the lipoprotein core and coalescence into large lipid droplets [Jayaraman et al., 2005 (I); Guha et al., 2007]. In our stability studies, we took advantage of the induced near-UV CD to monitor rupture of the core-containing lipoproteins in thermal denaturation experiments. Together with nearUV CD, we recorded right-angle light scattering to monitor increase in the particle size due to lipoprotein fusion, rupture and coalescence into lipid droplets. Figure 21 shows such CD and LS melting data recorded of human plasma LDL at 280 nm, i. e., at the shoulder of the nearUV CD peak that reports on LDL rupture. Our objective was to test whether, similar to HDL subclasses, LDL subclasses show higher stability for smaller particles. In contrast to HDL and VLDL that contain multiple copies of the exchangeable apolipoproteins as their major proteins, each LDL particle contains one copy of the nonexchangeable apoB that comprises >95% of its total protein content [Segrest et al., 2001; Oloffson & Boren, 2005]. As a result, LDL comprise a relatively homogeneous particle population. Nevertheless, human plasma LDL form subclasses differing in particle size, charge, density, composition, and apoB conformation. This includes large buoyant LDL1

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(density ≤1.02 g/mL), intermediate LDL2 (1.02-1.04 g/mL) that comprise the major plasma fraction, and small dense LDL3 (1.04-1.06 g/mL) that are thought to be particularly proatherogenic [Chapman et al., 1998; Kwiterovich, 2002]. The latter may result from the increased affinity of small dense LDL for the arterial proteoglycans, as well as the increased propensity of these particles to undergo post-translational modifications such as oxidation ([Kwiterovich, 2002] and references therein). The structural details underlying functional differences among LDL subclasses are not well understood. Far- and near-UV CD spectra in Figure 22 do not detect any differences in apoB conformation in large and small LDL. However, CD spectra do not provide a sensitive diagnostic tool to detect conformational changes affecting limited regions of this enormous 550 kD protein. In contrast, antibody binding studies or fluorescence lifetime measurements, which are sensitive to global or local conformational changes, have reported different apoB conformations on different-size LDL [McNamara et al., 1996; Lund-Katz et al., 1998]. These differences are expected to affect the interactions of apoB with LDL receptor and other ligands, such as arterial wall proteoglucans, and thereby impart functional differences to LDL subclases.

Figure 20. Near-UV CD spectra of intact and ruptured human HDL and of the major HDL protein, apoA-I. The spectra were recorded at 25 oC from samples of HDL (2.5 mg/ml, protein, 0.5 M NaCl in standard buffer) that were intact (purple) or heated and cooled in a DCS experiment from 25 to 115 oC (brown). CD spectrum of lipid-free intact human apoA-I, that was recorded in standard buffer at 25 oC, is shown for comparison (black). Arrow shows the near-UV CD peak that is induced upon release of the apolar lipids from the lipoprotein core and their coalescence into large lipid droplets.

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Figure 21. Differential stability of human plasma LDL subclasses revealed by near-UV CD and turbidity. Single-donor human plasma LDL were isolated from EDTA-treated plasma by density gradient centrifugation [Schumaker & Puppione, 1986], and were separated into density fractions, from LDL>VLDL, correlates inversely with the particle size. The general trend emerging from these studies is that smaller lipoproteins tend to be more stable. This may be due to higher protein:lipid ratio in smaller particles, their higher curvature, as well as the differences in protein conformation and lipid composition in large and small particles. In addition, increased surface coverage by apoB reported for small dense LDL3 [McNamara et al., 1996] may contribute to their increased stability. Studies of the structural basis for this observation and its potential functional implications are underway.

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3.3. Lipoprotein Stability and Lipid-lowering Drugs The stability of plasma lipoproteins shows batch-to-batch variations that are donor- and diet-specific and probably result from subtle differences in the protein and lipid composition. The largest variation was observed in the stability of VLDL isolated from plasma of a donor before and after administration of a lipid-lowering drug from the statin family. Statins, which are the most widely prescribed drugs, reduce plasma cholesterol by inhibiting HMG-CoA reductase that is the rate-limiting enzyme in cholesterol biosynthesis [Endo, 1992]. Inhibition of this enzyme in the liver decreases synthesis of cholesterol and increases synthesis of LDL receptors [Ma et al., 1986], thereby increasing the clearance of LDL and reducing LDL CE. Because of the overall reduction in CE, the CE:TG ratio in the lipoprotein core is reduced. This is expected to affect the stability and hence, the metabolic properties of the lipoproteins. In fact, a reduction in stability of model HDL upon reduction in CE:TG ratio has been observed in our and in the earlier studies [Sparks et al., 1995]. To our knowledge, the effects of lipid core composition on VLDL stability have not been reported. Our preliminary data, which were recorded by turbidity in CD experimens, show a large reduction in the apparent temperature of the heat-induced VLDL fusion and rupture upon statin administration [Figure 23A]. Similarly, an apparent reduction in stability was observed in LDL; however, no significant changes in the HDL stability were detected (data not shown). We speculate that the apparent reduction in VLDL stability results, in part, from the reducion in CE:TG ratio in the VLDL core detected by thin-layer chromatography [Figure 23B]. However, other factors may also play a role; these factors and their protential effects on lipoprotein metabolism will be explored in our future studies. The results may help better

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understand the molecular mechanisms of action of the lipid-lowering therapies and their effects on lipoprotein stability and remodeling.

Figure 23. Structural stability and lipid core composition in human VLDL obtained from different donors. VLDL were isolated from EDTA-treated plasma by density gradient centrifugations in the density range 0.94-1.006 g/mL as described [Schumaker & Puppione, 1986]. Four plasma batches from three volunteer donors were used: donor A before (pink) and after administration of statins (violet), donor B, and donor C. VLDL samples (1.5 mg/mL protein in 10 mM Na phosphate buffer, pH 7.6) were heated from 20-98 oC at a rate of 11 oC/h. Thermal disruption of VLDL, which involves particle fusion, rupture and coalescence into large lipid droplets, was monitored by measuring turbidity (dynode voltage) in CD experiments [Guha et al., 2007]. VLDL isolated from plasma of donor A showed a large reduction in the apparent temperature of denaturation by about -15 oC upon administration of statins (large arrow). VLDL from donor B showed intermediate stability between those of donor A before and after administration of statins. Thin-layer chromatography showed a large reduction in CE:TG ratio in VLDL upon administration of statins to donor A. This reduction is expected to contribute to VLDL destabilization. Furthermore, VLDL from donor B and from donor A before statin treatment had similar CE:TG ratio, yet the latter showed higher apparent stability (gray and pink lines); also, VLDL from donor C and from donor A after statin treatment showed comparable thermal stability, yet CE:TG ratios in these VLDL were significantly different. This suggests that factors other than CE:TG ratio contribute to the variations in VLDL stability.

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CONCLUSION CD spectroscopy in conjunction with other biophysical, biochemical, and protein engineering techniques provides a versatile tool for structural and stability studies of model and plasma lipoproteins and their constituents. Far- and near-UV CD yields insights into conformational adaptability of apolipoproteins and their model peptides to various environments. Such adaptability is key to transfer of these proteins from the aqueous environment in plasma to the lipid surface during metabolism. CD spectroscopy coupled with DSC, fluorescence and other biophysical techniques helped elucidate the molten globule-like properties of the exchangeable apolipoproteins in solution and relate these properties to the lipid surface-binding function of these proteins [Gursky & Atkinson, 1996 (I); Gursky & Atkinson, 1996 (II); Soulages & Bendavid, 1998; Weers et al., 2001; Morrow et al., 2002]. Furthermore, CD coupled with proline scanning mutagenesis facilitated secondary structural assignment to individual protein groups in the smallest apolipoprotein, apoC-I (6 kD), that is a structural and functional prototype for larger apolipoproteins [Gursky, 2001]. In larger proteins such as apoA-I (28 kD) or apoE (32 kD), CD spectroscopy coupled with site-directed mutagenesis helped determine the role of individual protein domains, their segments, as well as specific amino acids in the overall protein conformation, stability and structural adaptability to various environments [Gorshkova et al., 2000, 2002, 2006; Fang et al., 2003; Rogers et al., 1997, 1998 (I, II); Zhu & Atkinson, 2004, 2007; Sorci-Thomas et al., 1997 (I, II), 1998; Saito et al., 1998, 2003]. Furthermore, CD was instrumental in verifying amyloid formation upon HDL oxidation by showing -helix to -sheet conversion in apoA-I [Wong et al., 2010], or in disproving such a conversion in apoB upon LDL oxidation [Jayaraman et al., 2007]. The role of CD for structural analysis of lipoproteins is underscored by the fact that highresolution studies of these particles have been hampered by their large size and by their conformational and compositional heterogeneity, as well as their ability to exchange some of their protein and lipid components. Lipoprotein stability studies by CD and LS, such as our work, may help obtain small homogeneous particles of increased stability suitable for future high-resolution x-ray crystallographic analysis. Stability studies may also shed new light on the mechanisms of action of lipid-lowering drugs, as well as help create lipoproteins with improved functional properties [Pownall, 2005] for future use as diagnostic or therapeutic tools, or as vehicles for drug delivery [Ryan, 2008; Glikson et al., 2009]. However, application of CD to structural studies of lipoproteins has its limitations, particularly for LDL and VLDL particles containing large amounts of apolar lipid in their core and apoB, which is one of the largest known proteins, in their surface. Light scattering by these large particles together with CD contribution from the lipids distorts far-UV CD spectra of these particles and precludes accurate quantitative analysis of the protein secondary structure. Therefore, CD analysis of large lipoproteins is limited to comparative studies of the protein conformation. Even so, spectral changes in far- or near-UV do not always result from changes in the secondary or tertiary apolipoprotein structure; instead, they may reflect the CD contribution from the lipids which greatly increases upon lipoprotein rupture and coalescence into lipid droplets. For example, VLDL heating beyond 80 oC leads to a large induced CD peak centered at 320 nm, with a shoulder extending into far-UV, which reports on re-packing of VLDL lipids rather than conformational changes in the proteins [Guha et al., 2007].

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Another potential caveat is that the absence of spectral changes in far- or near-UV CD of LDL or VLDL does not always mean that the conformation of apoB remains invariant (Figure 22). Hence, other structural probes, such as fluorescence lifetime measurements and antibody binding, should be used in conjunction with CD to assess local and global conformational changes in this enormous 550 kD protein. In addition to structural studies, CD proved indispensable for the stability studies of model and plasma lipoproteins. Far-UV CD spectroscopy together with turbidity and LS measurements in CD experiments was instrumental in uncovering kinetic mechanism of lipoprotein stabilization and linking it to lipoprotein remodeling in vitro and in vivo. In model or plasma HDL that are comprised of highly -helical exchangeable apolipoproteins such as apoA-I, far-UV CD is the method of choice for monitoring the time course of protein unfolding. The results are useful for quantitative kinetic analysis of lipoprotein stability. Furthermore, near-UV CD of the core-containing lipoproteins, particularly LDL and VLDL, is useful for monitoring in real time re-packing of apolar core lipids during lipoprotein rupture. In addition, LS and turbidity measurements in CD experiments are useful to monitor in real time lipoprotein fusion and rupture. In summary, conventional CD spectroscopy combined with LS/turbidity measurements and other structural and biochemical probes provides a versatile tool for obtaining specific structural information on the protein and lipid moieties, and is uniquely suited for studies of kinetic lipoprotein stability that typically ranges from about G*15-20 kcal/mol [Gursky et al., 2002]. Lipoproteins are just one example of macromolecular assemblies whose structural stability and functional remodeling are subjects to kinetic control. In recent years, kinetic stability has emerged as a general mechanism for structural stabilization and functional optimization of an increasing number of biological macromolecules and their assemblies (reviewed by [Sanchez-Ruiz, 2010]). This opens a possibility of even broader application of conventional CD spectroscopy for the structural stability studies of such assemblies.

ACKNOWLEDGMENT We thank Cheryl England and Michael Gigliotti for help with isolation of plasma lipoproteins and purification of apolipoproteins, Yuhang Lui for help with isolation of LDL subclasses, and Donald L. Gantz for expert help with electron microscopy. OG is grateful to Dr. Anke Steinmetz for very helpful comments on the manuscript prior to publication. This work was supported by the National Institute of Health grants HL026355 and GM067260.

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Olofsson, S. O., & Boren, J. (2005) Apolipoprotein B: a clinically important apolipoprotein which assembles atherogenic lipoproteins and promotes the development of atherosclerosis. J. Intern. Med. 258(5), 395-410. Parks, J. S., Huggins, K. W., Gebre, A. K., & Burleson, E. R. (2000) Phosphatidylcholine fluidity and structure affect lecithin:cholesterol acyltransferase activity. J. Lipid Res. 41(4), 546-553. Ponsin, G., Strong, K., Gotto, A. M. Jr., Sparrow, J. T., & Pownall, H. J. (1984) In vitro binding of synthetic acylated lipid-associating peptides to high-density lipoprotein: Effect of hydrophobicity. Biochemistry, 23, 5337-5342. Ponsin, G., Hester, L., Gotto, A. M. Jr., Pownall, H. J., & Sparrow, J. T. (1986) Lipid-peptide association and activation of lecithin: Cholesterol acyltransferase. J. Biol. Chem. 261, 9202-9205. Pownall, H. J. (2005). Remodeling of human plasma lipoproteins by detergent perturbation. Biochemistry, 44(28), 9714-9722. Plaza del Pino, I. M., Ibarra-Molero, B., & Sanchez-Ruiz, J. M. (2000) Lower kinetic limit to protein thermal stability: a proposal regarding protein stability in vivo and its relation with misfolding diseases. Proteins, 40(1), 58-70. Reijngoud, D. J., & Phillips, M. C. (1982) Mechanism of dissociation of human apolipoprotein A-I from complexes with dimyristoylphosphatidylcholine as studied by guanidine hydrochloride denaturation. Biochemistry, 21(12), 2969-2976. Reijngoud D. J., & Phillips M. C. (1984) Mechanism of dissociation of human apolipoproteins A-I, A-II, and C from complexes with dimyristoylphosphatidylcholine as studied by thermal denaturation. Biochemistry, 23, 726-734. Rogers, D. P., Roberts, L. M., Lebowitz, J., Datta, G., Anantharamaiah, G. M., Engler, J. A., & Brouillette, C. G. (1998) The lipid-free structure of apolipoprotein A-I: Effects of amino-terminal deletions. Biochemistry, 37, 11714-11725. Rogers, D. P., Brouilette, C. G., Engler, J. A., Tendian, S. W., Roberts, L., Mirsha, V., Anantharamaiah, G. M., Lund-Kutz, S., Phillips, M. C., & Ray, M. J. (1997) Truncation of the amino terminus of human apolipoprotein A-I substantially alters only the lipid-free conformation. Biochemistry 36, 288-300. Rogers, D. P., Roberts, L. M., Lebowitz, J., Engler, J. A., & Brouilette, C. G. (1998). Structural analysis of apolipoprotein A-I: Effects of amino- and carboxy-terminal deletions on the lipid-free structure. Biochemistry 37, 945-955. Rozek, A., Sparrow, J. T., Weisgraber, K. H., & Cushley, R. J. (1999) Conformation of human apolipoproitein C-I in a lipid-mimetic environment determined by CD and NMR spectroscopy. Biochemistry 38, 14475-14484. Ryan, R. O. (2008) Nanodisks: hydrophobic drug delivery vehicles. Expert Opin Drug Deliv. 5(3), 343-351. Rye, K. A., & Barter, P. J. (2004). Formation and metabolism of prebeta-migrating, lipidpoor apolipoprotein A-I. Arterioscler. Thromb. Vasc. Biol. 24, 421-428. Saito H., Dhanasekaran P., Nguyen D., Holvoet P., Lund-Katz S., & Phillips M.C. (2003) Domain structure and lipid interaction in human apolipoproteins A-I and E, a general model. J. Biol. Chem. 278(26), 23227-23232. Sanchez-Ruiz, J. M., Lopez-Lacomba, J. L., Cortijo, M., & Mateo P. L. (1988) Differential scanning calorimetry of the irreversible thermal denaturation of thermolysin. Biochemistry, 27, 1648-1652.

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Sanchez-Ruiz, J. M. (2010) Protein kinetic stability. Biophys. Chem. 148(1-3), 1-15. Schellman, J.A. (1997) Temperature, stability, and the hydrophobic interaction. Biophys J. 73(6), 2960–2964. Schumaker, V. N., & Puppione, D. L. (1986) Sequential flotation ultracentrifugation. Methods Enzymol. 128, 151-170. Segrest, J. P., Jones, M. K., De Loof, H., Brouillette, C. G., Venkatachalapathi, Y. V., & Anantharamaiah, G. M. (1992) The amphipathic helix in the exchangeable apolipoproteins: a review of secondary structure and function. J. Lipid Res. 33, 141-166. Segrest, J. P., Jones, M. K., De Loof, H., & Dashti, N. (2001) Structure of apolipoprotein B100 in low density lipoproteins. J. Lipid Res. 42(9), 1346-1367. Skalen, K., Gustafsson, M., Rydberg, E. K., Hulten, L. M., Wiklund, O., Innerarity T. L., & Boren, J. (2002) Sub-endothelial retention of atherogenic lipoproteins in early atherosclerosis. Nature, 417, 750-754. Sklar, L. A., Craig, I. F., & Pownall, H. J. (1981) Induced circular dichroism of incorporated fluorescent cholesteryl esters and polar lipids as a probe of human serum low-density lipoprotein structure and melting, J. Biol. Chem. 256, 4286−4292. Sorci-Thomas, M., Curtiss, L., Parks, J. S., Thomas, M. J., & Kearns, M. W. (1997) Alteration in apolipoprotein A-I 22-mer repeat order results in a decrease in lecithin:cholesterol acyltransferase reactivity. J. Biol. Chem. 272(11), 7278-7284. (I) Sorci-Thomas, M. G., Curtiss, L., Parks, J. S., Thomas, M. J., & Kearns, M. W. (1997) Alteration in apolipoprotein A-I amphipathic helix domain 143-164 regulates lecithin:cholesterol acyltransferase activation. J. Biol. Chem. 273 (19), 11776-11782. (II) Sorci-Thomas, M. G., Curtiss, L., Parks, J. S., Thomas, M. J., Kearns, M. W., & Landrum, M. (1998) The hydrophobic face orientation of apolipoprotein A-I amphipathic helix domain 143-164 regulates lecithin:cholesterol acyltransferase activation. J. Biol. Chem. 273 (19), 11776-11782. Soulages, J. L., & Bendavid, O. J. (1998) The lipid binding activity of the exchangeable apolipoprotein apolipophorin-III correlates with the formation of a partially folded conformation. Biochemistry 37(28), 10203-10210. Sparks, D. L., Davidson, W. S., Lund-Katz, S., & Phillips, M.C. (1995) Effects of the neutral lipid content of high density lipoprotein on apolipoprotein A-I structure and particle stability. J. Biol. Chem. 270(45), 26910-26917. Surewicz, W. K., Epand, R. M., Pownall, H. J., & Hui, S.W. (1986) Human apolipoprotein AI forms thermally stable complexes with anionic but not with zwitterionic phospholipids. J. Biol. Chem. 261(34), 16191-16197. Tailleux, A., Duriez, P., Fruchart, J. C., & Clavey, V. (2002) Apolipoprotein A-II, HDL metabolism and atherosclerosis. Atherosclerosis 164(1), 1-13. Tall, A. R. (1998). An overview of reverse cholesterol transport. Eur. Heart J. 19(Suppl A), A31-A35. Thuahnai, S. T., Lund-Katz, S., Williams, D. L., & Phillips, M. C. (2001). Scavenger receptor class B, type I-mediated uptake of various lipids into cells. Influence of the nature of the donor particle interaction with the receptor. J. Biol. Chem. 276, 43801-43808. Wang, G., Pierens, G. K., Treleaven, W. D., Sparrow, J. T., & Cushley, R. J. (1996) Conformation of human apolipoproteins E(263-286) and E(267-289) in aqueous solutions of sodium dodecyl sulfate by CD and 1H NMR. Biochemistry, 35, 10348-10366. (II)

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Wang, G., Sparrow, J. T., & Cushley, R. J. (1997) The helix-hinge-helix structural motif in human apolipoprotein A-I determined by NMR spectroscopy. Biochemistry, 36, 1365713666. Weers, P. M., Kay, C. M., & Ryan, R. O. (2001) Conformational changes of an exchangeable apolipoprotein, apolipophorin III from Locusta migratoria, at low pH: correlation with lipid binding. Biochemistry, 40(25), 7754-7760. Wong, Y. Q., Binger, K. J., Howlett, G. J., & Griffin, M. D. (2010) Methionine oxidation induces amyloid fibril formation by full-length apolipoprotein A-I. Proc. Natl. Acad. Sci. USA 107(5), 1977-1982. Woody, R. W., & Dunker, K. A. (1996) Aromatic and cystine side chain circular dichroism in proteins. In: Circular dichroism and conformational analysis of biomolecules, Fasman G. E., Edt. Plenum Press, NewYork, pp. 109-158. Yeagle, P. L., Bensen, J., Greco, M., & Arena, C. (1982) Cholesterol behavior in human serum lipoproteins, Biochemistry, 21, 1249−1254. Zannis, V. I., Kypreos, K. E., Chroni, A., Kardassis, D., & Zanni, E. E. (2004) Lipoproteins and atherogenesis. In: Molecular Mechanisms of Atherosclerosis. Loscalzo J., Edt. Zhang, F., Poulos, G., Hamilton, J. A., & Atkinson, D. (1995) Solution structure of a 44residue consensus sequence peptide of apolipoproteins by NMR. 39-th Annual Biophys. Soc. Meeting, San Francisco, CA. Abstract: Biophys. J. 68(2/2), A420, Th-Pos308. Zhang, L., Song, J., Newhouse, Y., Zhang, S., Weisgraber, K. H., & Ren, G. (2010) An optimized negative-staining protocol of electron microscopy for apoE4 POPC lipoprotein. J. Lipid Res. 51(5), 1228-1236. Zhu, H. L. & Atkinson, D. (2004) Conformation and lipid binding of the N-terminal (1-44) domain of human apolipoprotein A-I. Biochemistry, 43(41), 13156-13164. Zhu, H. L., & Atkinson D. (2007) Conformation and lipid binding of a C-terminal (198-243) peptide of human apolipoprotein A-I. Biochemistry, 46(6), 1624-1634.

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In: Circular Dichroism: Theory and Spectroscopy Editor: David S. Rodgers

ISBN: 978-1-61122-522-8 2012 Nova Science Publishers, Inc.

Chapter 5

THE USE OF CIRCULAR DICHROISM METHODS TO MONITOR UNFOLDING TRANSITIONS IN PEPTIDES, GLOBULAR AND MEMBRANE PROTEINS Ernesto A. Roman, Javier Santos, F. Luis González Flecha Laboratorio de Biofísica Molecular, Instituto de Química y Fisicoquímica Biológicas Universidad de Buenos Aires – CONICET, Junín — Buenos Aires, Argentina

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ABSTRACT This chapter discusses the use of far and near UV circular dichroism methods to analyze changes in secondary and tertiary structure during protein unfolding, and how to obtain thermodynamic and kinetic information from CD experiments. We will give a brief introduction on the basics of this technique and discuss practical examples on the analysis of the unfolding of peptides, globular and membrane proteins. Here we will deal with important practical issues such as protein concentration, path length, choice of buffer, wavelength selection, and specific issues for unfolding experiments as the determination of the pre and post transition baselines. The importance of steady–state and time–resolved CD measurements on protein folding studies will be pointed out. Near– and far–UV CD experiments under equilibrium condition will aid us in the characterization of folded, partially folded, and unfolded states, and in the quantitative description of the unfolding transition, whereas folding–unfolding kinetics (non– equilibrium experiments) will give us a clue about the dynamics of the process involved. The selected examples will focus on the unfolding of the soluble proteins β-lactamase, lysozyme and thioredoxin, and on the thermophilic membrane protein CopA from Archaeoglobus fulgidus. Also, the induction of a helical structure by co–solvents (e.g., TFE, SDS) and their stability will be discussed. We will give a walkthrough to perform experiments and quantitatively analyze them in terms of the two–state and multi–state protein folding transitions, pointing to the determination and proper interpretation of thermodynamic and kinetic parameters. In addition, the advantages of using this method and its limitations will be discussed.

Keywords: Protein circular dichroism; Protein stability; Protein unfolding; Thermodynamics; Two–state model; Unfolding intermediates Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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INTRODUCTION The Origin of the CD Signal in Proteins Circular dichroism arises from the differential interaction of circularly polarized electromagnetic radiation with chiral molecules [1]. Protein chirality originates from geometrical as well as topological features [2]; all amino–acid residues, except glycine, have at least one chiral center at Cα, and additional chiral features are formed when the polypetidic chain folds. When a protein sample is irradiated with circularly polarized electromagnetic radiation of a given wavelength, one of the two polarization components (left and right circularly polarized) is absorbed more than the other.

A  A L  A R  ( L   R )  l  C    l  C

(1)

This wavelength-dependent difference of the extinction coefficients (ε) yields the circular dichroism spectrum of the sample. Although ΔA is usually the measured quantity, most CD data for proteins are reported in terms of ellipticity (θ). This is a quantity that accounts for the fact that, after the interaction with a chiral molecule, the electric field vector (E) of the polarized electromagnetic radiation traces out an elliptical path. The ellipticity is defined as:

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tg θ 

ER  EL ER  EL

(2)

Generally θ is very small so tg θ can be approximated as θ. Moreover, the intensity of the electromagnetic radiation is proportional to the squared modulus of the electric–field vector and it follows the Beer law; thus,

θ

e e



AR ln10 2

A  R ln10 2

e e



AL ln10 2

A  L ln10 2

 A

ln10 4 (3)

The right side of equation (3) results from expanding the exponentials in a first–order Taylor series and is further simplified by discarding terms of A in the denominator. The ellipticity of a sample depends on its concentration and on the cell path length. These dependences can be removed by defining the molar ellipticity as

θ  

θ ln10    l C 4

(4) Note that units of [θ] and Δε in equation (4) are the same (e.g., M-1cm-1). If we want to express [θ] in other units (e.g., deg cm2 dmol-1), an additional numerical factor may have to be included.

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Figure 1. Far–UV circular dichroism spectra of an all alpha protein (myoglobin, continuous line), an all beta protein (concavalin A, dashed line), and a polyproline-II-type protein (type VI colagen, dotted line). Reprinted from [13]. Copyright 2001, with permission from Elsevier.

The UV–vis CD spectra are related to electronic transitions. The main chromophores in proteins are the amide group of the polypeptide backbone (far–UV region), the aromatic residues (near–UV region), and chromophoric ligands or prostetic groups (usually in the visible region of the electromagnetic spectra). The amide group is the most important chromophore in proteins, and light absorption is related to the electronic transitions from the amide non–bonding π orbital to the antibonding orbital π*, and from the oxygen lone pair orbital n to the π* [3]. Secondary structures impose positional constraints on these transitions and give rise to characteristic far–UV spectra for each structural element. The far–UV CD spectra of α-helical proteins are characterized by three bands (Figure 1). A negative band located at 222 nm corresponds to the n→π* transition. Another negative band at 208 nm and an intense positive band at 190 nm, arise from the exciton splitting of the π→π* transition. A shoulder at 175 nm has been proposed to be due to the charge transfer transitions [4]. The CD spectrum of a 310 helix is very similar to that of an α-helix [5]. In addition, the far–UV CD spectra of helical membrane proteins are shifted a few nanometers in wavelength compared to those of soluble proteins of similar structure, probably as a result of the difference in the dielectric constants between the lipid bilayer and water [6, 7]. The CD spectrum of β-sheets shows a small negative band near 215 nm assigned to the n→π* transition, a positive band near 195 nm and a negative band at around 180 nm, both corresponding to the π→π* exciton components [8]. Spectral characteristics of β-sheets signals are more variable than those corresponding to helices, given the higher structural diversity observed in β-sheets compared to α-helices [9]. On the other hand, β-sheet signals are significantly weak making the spectrum more susceptible to distortions between 225 nm and 235 nm as a consequence of the CD signals of aromatic amino acid residue side chains. Thus, the CD analysis of β-sheet rich proteins is often much less accurate than that

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corresponding to helical proteins [9]. Given the variability in the position of the CD bands among soluble proteins, it is not easy to determine whether spectral shifts found in β membrane proteins are significant [7]. Polyproline-II-type structures (PPII) show a positive band at 220 nm corresponding to the π→π* parallel transition, and a negative band at 200 nm from the π→π* perpendicular transition [10]. In this case, the n→π* transition does not contribute to the CD signal. Below 190 nm, its spectrum tends to be negative, often with a shoulder or minimum around 170 nm. Unordered structures have variable spectra similar to that of PPII structures, but slightly blue shifted, with smaller amplitudes, usually lacking the higher wavelength positive peak, and often having small positive amplitudes at wavelengths below 180 nm [11]. Because of the thermodynamic restrictions imposed by the lipid bilayer, unordered structures are rare in transmembrane segments of membrane proteins [12].

Figure 2. Near–UV circular dichroism spectra of some proteins. (A) the membrane protein Archaeoglobus fulgidus CopA in the native (black line) and unfolded state (grey line) [15], (B) the intestinal fatty acid binding protein and (C) hen lyzozyme.

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Figure 3. Induced circular dichroism spectra of (A) 1-anilino-naphthalene-8-sulfonate bound to bovine serum albumin [16], and (B) retinal in bacteriorhodopsin. Adapted with permission from [17]. Copyright 2009 American Chemical Society.

The chiral environment of aromatic side chains created by the three–dimensional organization of the protein, gives rise to near–UV CD spectra which show a wide diversity among proteins (Figure 2). The aromatic amino acid residues (tryptophan, tyrosine and phenylalanine) absorb light in this range of wavelengths. Disulfide bonds also absorb at 250280 nm and, thus, they can also contribute significantly to the CD signal of proteins in this spectroscopic region [14]. Contrary to what was described for the far–UV CD spectra, no characteristic signatures can be assigned to particular protein folds. In fact, the near–UV CD spectrum of a given protein is considered a fingerprint for each protein. Similarly, cofactors or ligands bound to specific chiral binding sites in a protein produce CD signals in the visible range where these ligands absorb (Figure 3).

Factors Affecting the CD Signal As was previously mentioned, the dependence of the measured protein ellipticity with the number of CD active molecules reached by electromagnetic radiation is removed by defining the molar ellipticity. However, [θ] is not a constant for a given system, but it depends on the thermodynamic variables determining the state of the system, i.e., temperature, pressure and composition.

θ  f T , p, xi 

(5)

If each state of a given system is characterized by a unique value of [θ], which is usually the case of protein solutions that undergo reversible transformations, the change in [θ] produced when the thermodynamic variables change can be expressed as an exact differential:

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  θ     θ     θ   d θ     dT    dp     dxi i  xi T , p  T  p , xi  p T , xi

(6)

The partial derivatives in (6) include information about the perturbation introduced by the external source, e.g., an unfolding transition, or the dynamics of the protein conformation being examined, e.g., in the pre– and post–transition regions.

The Principle of Spectral Superposition It is known that in conditions where the Beer law holds, absorbance is an additive quantity [18]. This means that the absorbance of a given system composed by several absorbing components is equal to the summation of the absorbance that corresponds to each component. In a CD experiment, this rule is valid for each one of the two polarization components (left and right circularly polarized) and, from equation (1), it is clear that this will also be valid for the measured CD signals (ΔA, or θ). If the corresponding intensive quantities are used (Δε, or [θ]), the value of the signal for the whole system results in a linear combination of the signal values corresponding to each component, being fi the mole fraction of each component in the system.

θmix  θi  fi

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i

(7)

This result implies that the CD spectrum of a given CD active element in a mixture is identical to that of the same component if it were the unique CD active component in the sample. Thus the CD spectrum of the sample will be the superposition of the spectra corresponding to all the components, and conversely, the CD spectrum of a complex system can be deconvoluted into individual components. The singular value decomposition approach [19] allows to determine how many independent components can accurately be distinguished from a CD spectrum. The power of this procedure is highly dependent on the wavelength range of the spectrum [20]. For example, for spectra registered in the range between 200 nm and 260 nm, two independent components can be clearly distinguished; this number increases to three or four if the data extends to 190 nm; to five by taking spectra to 178 nm; to six extending the range to 168 nm and to seven or eight when registering the spectra from 160 nm [13]. The secondary structure content of a given protein can be estimated from its far–UV CD spectrum using reference sets of spectra corresponding to proteins of known three– dimensional structures and one of the available algorithms for data analysis [21-32].

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PRACTICAL ISSUES Circular Dichroism Instrumentation

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Spectropolarimeters A typical instrument based on the most used method to measure the CD signal of a protein sample (the called modulation method) is represented in Figure 4. This method is based on irradiating the sample with right and left polarized light alternatively, and measuring the difference in absorbance at each wavelength. The light source usually consists of a Xenon lamp which is used in the UV–visible range of CD spectrum. Hydrogen source and synchrotron radiation can be alternatively used for electronic CD experiments in the vacuum UV region. A monochromator is used to efficiently select the excitation wavelength before reaching the polarizer. The linear polarized beam is oriented at 45° with respect to the principal direction of the retarder, which would receive two linearly polarized beams of equal magnitude in both x and y planes. The retarder has different refraction indexes producing two polarized beams that are modulated out of phase by 90° or 90°, generating the right or left circularly polarized light, respectively. The modulated light now irradiates the sample, and the intensity of the transmitted light is detected. The detection device should be appropriated for the wavelength range of the radiation. It usually consists of a photomultiplier sufficiently sensitive to detect a difference of absorbance of 10-4 over the thermal/electrical noise of the detector system [33]. Synchrotron Radiation Stations Synchrotron rings generate electromagnetic radiation with optical and spectral properties that makes this radiation of great interest for scientific research. Among its main features are high brightness and high intensity (many orders of magnitude more than with conventional instruments [34]), a high level of polarization, high collimation, and low emittance. These properties make synchrotron radiation very useful for obtaining good CD spectra in the vacuum ultraviolet (VUV) wavelength region [35, 36]. The lines operate under high vacuum, and protein samples are located in calcium fluoride or lithium fluoride cells located in sample chambers which are purged with nitrogen to remove oxygen from the light path. In these conditions, the CD spectrum of protein solutions can be extended down to 168 nm, a limit given by the absorbance of water [9]. Protein CD spectra obtained in synchroton radiation circular dichroism (SRCD) instruments are much more precise than those obtained on conventional instruments because of the higher signal–to–noise ratio. This allows to use smaller amounts of proteins, and also, to detect smaller differences among spectra [37]. The time required to acquire a suitable signal can also be greatly reduced, thus increasing the rate of data collection, which is important when a large number of protein samples have to be examined, and more importantly, for increasing the time resolution in kinetic experiments [38]. On the other hand, SRCD is very useful to obtain high quality CD spectra of high absorbing protein samples and membrane proteins, because it minimizes scattering and absorption–flattening artifacts [9, 13, 39].

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Figure 4. Diagram of a circular dichroism apparatus.

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Buffers, Path Length, Additives, and Protein Concentration Solvents for performing CD studies should be properly selected. Certain buffers may cause problems because of their high extinction coefficients at low wavelengths in the far– UV region. In some cases, protein solubility may be limited at low buffer concentrations. In this case, ionic strength may be maintained by using salts like sodium fluoride (NaF) and not NaCl because Cl- absorb substantially in the far–UV region. Note that NaF is very toxic and care should be taken with its manipulation. Suitable buffer ions for far–UV studies (in the range from 260 nm to 185 nm) include phosphate, Tris (in the range of pH 6 to 8.5). In the pH range from 1 to 3, phosphoric acid may be used (pKa=2). In the pH 4-6 range most of the buffers are based on the ionization of carboxylic acid groups (e.g., acetic acid and citric acid) which absorb strongly below 200 nm. In addition, organic buffers such as HEPES, MOPS, and MES absorb strongly below 200 nm and should be used at low concentrations for UV CD studies in the far region of the spectrum. Alternatively, very short path lengths (0.1-0.05cm) may be used to minimize buffer absorption, but in that case, protein concentration should be increased. This approach may be useful in the far–UV region, but would be impracticable in the near–UV where the extinction coefficients of proteins are lower. Fortunately, in this region, absorption of buffers does not make difficult the acquisition of spectra. Usually, in the near–UV region, it will choose a cell of 1cm-path. In some extreme cases, where protein cannot be concentrated, cylindrical cells of 2-10 cm may be used. Additives such as the detergent SDS or organic solvents, including methanol, ethanol, acetonitrile, and 2,2,2-trifluoroethanol (TFE) may be used because they are nearly transparent between 195-250 nm; some of them may be useful for promoting structure stabilization/disruption [40, 41]. Other very important additives in protein characterization are osmolytes; the use of these species to drive folding reaction is discussed below. In this

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chapter, we focus on protein unfolding: typically chaotropic agents such as urea and GdmCl are used to unfold proteins. At high concentrations, these denaturants absorb strongly and do not allow the collection of CD data below 200 nm (even when using cell path lengths of 0.1 cm). For this reason, unfolding is usually followed by far–UV CD at 220-222nm. At these wavelengths, concentrations as high as 8.0 M urea or 8.0 M GdmCl may also be sampled. When preparation of the protein includes a refolding step, denaturant should be removed by dialysis or size exclusion chromatography. Protein concentration should be carefully determined, and the optimal value will depend on the chosen path length and on the particular extinction coefficient (ελ) of the protein. For example, an absorbance between 0.5 and 0.9 will be a good starting point for designing the experiment. Usually, the same solutions may be used for far–UV CD measurements with cell path lengths of 0.1cm, and near–UV CD with cell path lengths of 1cm. A good determination of ελ and a proper calibration of the path length of the cell are critical for subsequent treatment of the CD data [40, 42]. Total absorbance of the sample may be monitored by the trace of the voltage applied to the photomultiplier. To properly measure sample ellipticity, high tension voltage should usually be less than 600 V.

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EQUILIBRIUM UNFOLDING AND CIRCULAR DICHROISM Temperature and chemical unfolding transitions can be monitored by CD as a change in ellipticity. In the far–UV region, loss of beta and α-helical content can be observed at 215 and 222 nm respectively. This is caused by loss of periodic structure in the environment of peptide bonds. In addition, changes in tertiary structure can be monitored in the near–UV region, 260-300 nm, as a change in ellipticity due to perturbations of the asymmetric environment of aromatic side chains. Moreover, CD spectra should be acquired instead of single wavelength data. The information derived from the shape of the spectrum is more complete and thus, for instance, residual structure achieved following equilibrium unfolding may be better characterized.

Chemical Unfolding The unfolding strength of urea and GdmCl are presumably related to an effect in the formation of H-bonds and favorable interactions with the backbone [43]. These chaotropes also increase the water solubility of apolar atoms of backbone and side–chains, thus determining a favorable free energy of transfer apolar residues from the protein core to the aqueous environment. Unfolding curves show different regions: pre–transitions, transitions, and post–transitions (Figure 5). In the simplest case, only one transition between the native (N) and unfolded (U) state occurs (two–state model).

N U

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(8)

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Figure 5. Chemical unfolding of human frataxin followed by far-UV CD at 220 nm. The cell path length was 0.1 cm. Protein concentration was 5 μM. Buffer was 10 mM sodium phosphate, pH 7.0. Data acquisition was performed at 20 nm/min. Protein samples were incubated for 16 hours at room temperature in each GdmCl concentration to ensure equilibrium unfolding conditions.

The transition region corresponds to the region where the major change in the CD signal occurs. This change in the signal is a consequence of a folding (or unfolding) transition where both folded (fN) and unfolded fractions (fU) significantly change.

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1  f N  fU

(9)

The steepness of the change is related to the cooperativity of the conformational change that takes place. Pre– and post–transitions have no information about the unfolding process. However, the acquisition of data corresponding to these regions is crucial to calculate the thermodynamic parameters associated with the unfolding transition. For measurements in the far–UV region, samples with the same protein concentration should be prepared for each denaturant concentration (the volume and concentration of samples depend on the selected sample cell). The incubation time before measurement is a very important variable because the time required for achieving equilibrium depends on the folding kinetic (see below in the Unfolding Kinetics section) which relies on the nature of each particular protein. Usually, more than three hours of incubation will be necessary and special care should be taken with the temperature, because at low temperatures (e.g., 4°C) unfolding may be very slow. This behavior is well illustrated by unfolding of lysozyme that requires longer incubation times (7 hours at room temperature). It is important to take into account that chaotropes usually complicate the measurement of CD in the far–UV region, particularly at wavelengths in the range of 180-220 nm. Buffers with urea or GdmCl absorb in this range. On the other hand, for measurements in the near– UV region, higher protein concentration and larger sample volumes are required.

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Chemical unfolding is characterized by a Cm value that is the concentration of denaturant that produces a change of 50% of CD signal. In the simplest case of a two states model, this value corresponds to the middle point of the transition, when 50% of the molecules are in N and the other 50% are in U. At this point, the likelihood of finding a protein molecule in U is equal to the likelihood of finding it in N (i.e. [U] = [N]). Furthermore, the difference in free energy between N and U at the Cm is ∆G°NU = 0 and K = 1.

K

U   N 

fU fN

(10)

G NU   RT ln K

(11)

In addition, ∆G°NU varies linearly with denaturant concentration [44, 45].

G NU  G H 2O NU  mNU D

(12)

Replacing (11) in (12) and solving for K:

e



G  H 2O

NU

 mNU  D 

RT

K

(13)

Because at Cm , fN = fU

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G NU  G H 2O NU  mNU D  0

(14)

Thus Cm can be calculated as

G H 2O NU mNU

 Cm

(15)

Equilibrium unfolding is described by two parameters: ∆G°H2O NU, the difference in free energy between N and U in the reference state and in the absence of denaturant, and mNU, the slope of the dependence of the free energy change with denaturant concentration. Of course, we are interested in describing the CD signal (our observable) in terms of the species present in the system. Considering the principle of spectral superposition (equation 7), the total signal can be expressed as:

Stotal  f N S N  fU SU

(16)

where SN and SU are the signals (ellipticity in CD experiments) of native and unfolded states.

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Figure 6. Unfolding and refolding of CopA monitored by far–UV circular dichroism. CopA 2.5 μM was incubated for 2 h at 25ºC with the following concentrations of GdmCl: 0, 1.0, 1.9, 3.6, 4.6, 5.0, 5.9, and 7.5 M, and the far–UV ellipticities were registered. Black arrow indicates increasing concentrations of denaturant. Inset: The relative ellipticity at 222 nm was calculated dividing each value for that corresponding to the native protein and was then plotted as a function of GdmCl concentration for the unfolding (■) and refolding (□) experiments.

Usually SN and SU vary linearly with denaturant concentration in the pre–transition and post–transition regions.

S N  S N H 2O  mN  D

(17)

SU  SU H 2O  mU  D

(18)

Combining (10), (16), (17) and (18), the total CD signal (Stotal) is related to the unfolding equilibrium constant K.

Stotal 

S N H 2O  mN  D  ( SU H 2O  mU  D) K

1  K 

(19)

To estimate ∆G°H2O NU and mNU, equation 19 has to be fitted to experimental data using nonlinear least squares methods [46] varying mN, mU, SN H2O, SU H2O, and ∆G°H2O NU [47]. Reversible solvent denaturation was successfully used to study the structural organization of soluble proteins upon folding transitions. Although membrane proteins constitute a large

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fraction of the proteome and a number of pathologies appear to be related to alterations in their folding and stability, there is limited knowledge on associated molecular events and forces involved in these processes. Helical membrane proteins seem to be more prone to be denatured by detergents such as sodium dodecyl sulfate (SDS) [48], being quite resistant to urea– or GdmCl–denaturation. Alternatively, structural effects upon incubation with these solvents lead to irreversible denaturation, as is the case for opsin denatured by urea [49]. The case for β-barrel membrane proteins is different. These proteins are resistant to SDS and they are prone to denaturation by urea and GdmCl [48]. A very interesting case is CopA, a PIB type ATPase from Archaeoglobus fulgidus which was reported as the first helical membrane protein reversible denatured by GdmCl [15]. This enzyme consists of 804 amino acid residues with eight transmembrane segments and four soluble domains. As seen in Figure 6, as detergent–lipid–protein mixed micelles are incubated with increasing concentrations of denaturant, the far–UV ellipticity diminish at all wavelengths, indicating the disappearance of secondary structure. When denaturant is diluted with a refolding buffer which keeps constant the concentration of mixed micelles, ellipticity signals are recovered indicating the reversibility of the process (Inset of Figure 6). Thermodynamic parameters of CopA unfolding, calculated as described below, were ∆G°H2O NU = 12.9 kJ mol-1, mNU = 4.1 kJ mol-1 M-1, and Cm =3 M

Figure 7. Molar ellipticity for protein Nank 4-7* denatured state at 61°C in 10 mM sodium phosphate, pH 7.0, and 200 mM NaCl as a function of cosolvent concentration. Molar ellipticity at 228 nm is given as a function of urea (), sarcosine (○), and TMAO (∆) concentrations. Protein Nank 4-7* in the absence of the osmolytes or chaotropic agent is represented as a closed square. As a strong absorbance of osmolyte solutions is observed in the range of  220 nm, authors recorded CD at 228 nm, where the signal is dominated by the contribution of α-helical and β-structures. Adapted with permission from [54] Copyright 2010 American Chemical Society.

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Unfolding in the Presence of Osmolytes As urea and GdmCl stabilizes the unfolded state of proteins, several substances —known as osmolytes— are able to modulate the unfolding equilibrium. This is reflected by a dependence of ∆G°H2O, NU with osmolyte concentration. The effect of an osmolyte in protein stability can be measured from the derivative of ∆G°H2O, NU with respect to osmolyte concentration (mosm value). In general, comparison of mosm-values enables us to determine the power of the osmolyte in driving the protein either to fold or unfold. It was proposed that osmolytes act destabilizing the unfolded state because of the unfavorable interaction of osmolyte molecules with protein backbone [50-52]. There are several osmolytes frequently used in protein unfolding studies (e.g., Na2SO4, trimethylamine N-oxide, betaine, sucrose, trehalose, sarcosine, sorbitol, proline, glycerol). As shown in Figure 7, the selection of experimental conditions (buffer, pH and temperature) in which unfolding fraction is fU ~ 0.5 enables the study of both folding induction, by increasing osmolyte concentrations, and of unfolding, by increasing denaturant concentrations [53, 54]. In addition, the use of osmolytes has also been useful in the folding studies of natural unfolded proteins [55].

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Temperature Unfolding Temperature unfolding experiments followed by CD are very informative. However, they have to be performed with special care. In a typical experiment, temperature will be varied from 0 to 95ºC at a rate of 1-2ºC min-1 (heating at constant rate), and the melting curve will be sampled at 0.2-min intervals. It is important to evaluate whether the conformational transition is reversible or not. It can be done by estimating whether the CD signal recovering after reversing the temperature ramp is near 100%. In this case, unfolding can be treated as a reversible process. Because partially folded states populated in the transition are prone to aggregate, an increase in protein concentration can lead to irreversible unfolding. Thus, only if transition is still reversible at higher protein concentrations, as those needed for near–UV CD experiments, changes in tertiary structure can be monitored. If the process being monitored is aggregation and not unfolding, or a mix of both, mistaken conclusions will be delineated. When unfolding is reversible, the free energy of the unfolding process can be calculated assuming a two–state model:

 H (Tm )  f   T    CP ln   GNU   RT ln  U   H Tm  CP T  Tm   T   fN   Tm  (20)  Tm  S = f N ( S 0 , N + l N T ) + f N ( S 0 ,U + lU T )

(21)

where fU and fN are the unfolded and folded fractions, Tm is the temperature at which fU = fN, and S is the observed CD signal. S0,N and S0,U are the intrinsic spectroscopic signals for the

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native and unfolded state, respectively, and lN and lU are the slopes for the assumed linear dependence of S0,N and S0,U with the temperature, respectively. Interestingly, free energy profiles of unfolding have a bell shape when represented as a function of temperature (Figure 8). ∆G° NU will be 0 at two different temperatures, one is at Tm (melting temperature) where the unfolding process is driven by the entropy term, and the other is TC (cold unfolding temperature) where unfolding is driven by a difference in enthalpy, presumably produced by the interaction between water molecules located on protein surface [56-58]. In Figure 8, CD signal in the near–UV (280 nm) and the calculated free energy of unfolding are shown for the case of E. coli thioredoxin. Cold unfolding could occur at very low temperatures ([U]eq,) the time course of [N] and [U] follows a single exponential curve (a decreasing exponential for U and an increasing exponential for N), it can also be observed that the exponential coefficient is the same in both equations and corresponds to the observed kinetic constant.

kobs  k f  ku

(26)

When denaturing a protein with a chaotropic agent, such as urea or GdmCl, these folding and unfolding rate constants are dependent on the denaturant concentration. Empirical exponential relations have been proposed for accounting this dependence [81]:

k f  k of  e

 mkf  D

(27)

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ku  k uo  emku  D

(28)

combining (26), (27), and (28):

kobs  k of  e

 mkf  D

 k uo  e

mku  D

(29)

Thus, the evaluation of the observed rate constants at different denaturant concentrations will allow to determine the folding and unfolding kinetic coefficients for the folding reaction in the absence of denaturants. In this section, we will focus on the common techniques used to measure these rate constants and its data processing.

Manual Mixing Slow protein folding kinetics can be studied using conventional circular dichroism instruments combined with manual mixing strategies. Kuwajima et al. [82] described the complex refolding pathway of white egg lysozyme using this approach. Briefly, the sample was preincubated with 6M GdmCl, and the experiment was triggered by addition of buffer without denaturant under continuous stirring. The ellipticity was registered as a function of

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time at 222 nm for α helix contributions, and at 250 and 287.5 nm for aromatic residues contributions. It is seen in Figure 16, that while secondary structure is fully formed instantaneously, probably during the mixing time, tertiary structure is still being built. There is strong evidence of a complex folding mechanism, which is far from a simple two–state process. This result suggests that, after dilution of denaturant, a folding intermediate with consolidated secondary structure is stabilized. However, the fine structure of the active form of the lysozyme is achieved later. This kind of folding mechanism is an example of the complex reactions needed for a protein to reach the native state.

Rapid Mixing Devices

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Fast data acquisition has been a major advance in the study of protein folding. Although manual mixing procedures allow to characterize the late events in a folding process (those occurring near the final equilibrium state), valuable information comes from the ms range. This can be studied using rapid mixing devices. The main characteristics of this equipment are very efficient mixing to yield homogeneous solutions and minimal dead times between the mixer and the detector.

Figure 16. Time course of far– and near–UV CD signals of lysozyme after 20 times dilution of denaturant. The upper panel shows the ellipticity at 222 nm after manual mixing of the denatured protein with refolding buffer. The middle panel shows the kinetics of the near–UV ellipticity appearance at 250 nm. The lower panel shows the ellipticity at 287.5 nm. Adapted with permission from [82]. Copyright 1985 American Chemical Society.

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Rapid–mixing techniques were formally developed for the study of other fast reactions such as enzyme catalysis [83-85], chemical reactions such as phosphorilation in P–ATPases [86], or ligand binding [87]. More recently, rapid mixing techniques have been introduced in the study of folding reactions [88-90]. The general procedure used for these studies is shown in Figure 15. Protein and denaturing solution are loaded in different syringes. Solutions are simultaneously injected into the mixer manually, mechanically or by a nitrogen pulse. This equipment can be used as an add–in of a typical spectropolarimeter. In this case, the cell where the final solution resides is in the optical path of a circularly polarized light beam, and CD signal is collected during the injection (continuous flow method), or once the flow is stopped (stopped flow method). Similarly, to study the refolding reaction, unfolded protein and refolding buffer are placed each one in a different syringe, and the injection and mixing procedures are the same as for unfolding. In this way, secondary and tertiary structure formation can be monitored depending on the selected wavelength. For example, inspection of the ellipticity at 222 nm can give a clue on α helix formation. Also, near–UV circular dichroism can aid in the study of the acquisition of tertiary structure since differential absorption of aromatic residues can be monitored.

Figure 17. CD study of the refolding of human thioredoxin. Ellipticity at 220 nm was recorded as a function of time. To the left of the dashed lines, the signal corresponds to the refolded enzyme. After a new injection of unfolded protein and refolding buffer, continuous flow detection is allowed and the corresponding signal is shown between the dashed lines. After a few ms, the flow is stopped, but the signal is still recorded. The inset shows the reconstruction of the burst intermediate from the equilibrium ellipticity at different wavelengths. The solid line represents the spectrum of the native thioredoxin and the dashed line corresponds to the unfolded conformation of thioredoxin. The solid circles are the experimental reconstruction of the burst intermediate far–UV CD spectrum. Adapted with permission from [91]. Copyright 1998 American Chemical Society.

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Figure 17 shows the refolding reaction of human thioredoxin from a 4M GdmCl denatured state. This is a good example to study the detection of secondary and tertiary structures upon native state formation [91]. Here, the experiment was performed by mixing solutions of denatured enzyme in the presence of denaturant and the refolding buffer, using a rapid mixing device. The authors observed that the process is not well described by a single exponential function. The appearance of at least three folding phases suggests a highly complex process. As was shown in equations (27) and (28), in the simple two–state folding process, the rate constants behave exponentially against denaturant concentration. However, when intermediate states exist, this analysis becomes more complicated. In those cases, a careful analysis should be done and other mathematical models have to be tested in the analysis. In the case of thioredoxin, unfolding seems to be done through at least three transitions. Analysis of the temporal curves showed that a rapid non–detectable phase was followed by a fast decay in the CD signal at all the analyzed wavelengths. This rapid phase was referred to as a burst intermediate formation, which usually exists in the folding pathway of globular proteins [92]. As the burst is too fast to be monitored in typical stopped–flow experiments, a special design has to be applied. For this task, Georgescu et al [91] recorded the CD signal of the denatured thioredoxin for a few milliseconds; during the continuous injection of unfolded protein and refolding buffer, they monitored the ―burst intermediate‖ CD signal. After the flow was stopped, the kinetics of the refolding process was studied. Repeating this procedure at different wavelengths, it is possible to reconstruct the spectrum of the intermediate state (inset Figure 17). Because this spectrum could not be described as a linear combination of the native and the unfolded conformation spectra, the authors concluded that a different specie is stabilized. This intermediate state rich in secondary structure is devoid of tertiary contacts.

Figure 18. Insertion and folding of peptide p25 into a lipid bilayer. Ellipticity at 220 nm is recorded after injection of peptide p25 to the lipid–containing solution. The kinetic trace represents the experimental data, while the smooth line corresponds to an exponential function fitted to experimental data. Adapted with permission from [94]. Copyright 1996 American Chemical Society.

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As in the case of globular proteins, stopped–flow techniques can be used to monitor folding transitions of membrane proteins as well as insertion and folding of peptides in membranes. However, as previously described, these systems present many difficulties due to the complexity of working with mixtures containing lipids and detergents. Moreover, as binding to a non polar environment and folding seem to be different events, the complexity of the observed signals could be very high to analyze. According to the two stages model proposed by Engelman and Popot [93], the interaction between membrane–active peptides and biological membranes takes place in two steps. A first step in which the peptide binds non–covalently to the membrane, and a second step in which insertion into the lipid environment and folding take place. Thus, the question is whether the insertion process is coupled to structure induction. Figure 18 shows the kinetics of helix induction when inserting the peptide p25 into a lipid environment [94]. Peptide p25 is a part of the subunit IV of the cytochrome c, and is important as a signal for this protein to reach and insert in the membrane environment. So, an important issue in the study of this interaction is the understanding of the structure induction when inserting into membranes. Fluorescence studies demonstrated that labeling of p25 with an appropriate fluorophore is a good tool to study binding and insertion. Fluorescence stopped flow experiments showed two kinetic constants which are commonly associated with a two–step process. As far as these processes are identified, it is worth investigating whether insertion was coupled to helix induction. Rapid mixing techniques coupled to circular dichroism detection were used to answer this question. As seen in Figure 18, no signal change was detected during the first milliseconds. However, a simple exponential decay was observed between 4s and 80s. The kinetic constant associated with this process was in the same order as the insertion constant found by fluorescence, indicating that folding was coupled to insertion in the lipid environment. In summary, using this experimental setup one can study fast kinetic processes in the millisecond time scale. Simple reactions, such as switching from a folded to unfolded state, and vice versa, usually are explained by a single kinetic constant for each reaction that is calculated from fitting mathematical models to experimental data. However, when the process is more complex, it is difficult to obtain the kinetic constants describing a given folding mechanism. In these cases, empirical models are an important tool to gain insight in the understanding of the studied reaction [95].

Relaxation Techniques Since ns and μs events are known to be the earliest processes in a folding reaction, the development of devices for measuring such structural rearrangements are of major importance. Experiments performed under these conditions usually require a perturbation, often applied using temperature or pressure jumps, or sample excitation. A typical case of TRCD in the μs time scale is the study of folding transient states. Usually a protein folds through many intermediate states. However, not always these are sufficiently stable, or either detectable by conventional techniques. Moreover, the time required by a protein population to bypass the activation barrier usually varies from a few μs to many seconds, even minutes or hours. For example, the initial collapse in the folding of proteins often occurs within the dead time of

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rapid mixing devices. In thermal unfolding experiments, fast conformational changes are not detected. Although a peltier device permits a fast change in temperature, the time scale remains within seconds, and faster events cannot be detected. However, there are other procedures to perform this task. The temperature jump device consists of a cell plugged to a capacitor. When this unit charges, the capacitor is able to discharge a current that quickly rises the temperature. If this unit is coupled to circular dichroism equipment, early structure formation may be monitored. Recently, IR laser–induced temperature jumps yielded a nice description of nanosecond scale transition between a helix and a coil transition [96]. Another relaxation technique is related to pressure perturbations. The basics of the method are similar to the temperature jump; however, the pressure here is raised or lowered. Usually, materials such as piezoelectrics are used to induce very fast pressure changes. Another setup consists of using a pulsed laser to excite the sample. This setup, coupled to CD detection systems, allows the measurement of the optical properties of transient excited states. An interesting example is given by the transient reaction intermediates of retinal– bound rhodopsin. This membrane protein consists of a polypeptide chain bonded to the retinal molecule, forming a Schiff base. Excitation of this ensemble produces several excited states with different conformational configurations [17]. Also, these states have different absorption properties and generates induced CD signals (see Figure 3), so TRCD can be used to analyze and characterize the structure of protein in close proximity to the retinal molecule [17]. Previous studies demonstrated that after light excitation of rhodopsin, retinal goes through microsecond lifetime intermediates. Figure 19 shows the ellipticity corresponding to the induced CD signal at different times after excitation with a picoseconds–laser pulse. It can be observed that the 3D structure of the protein around the retinal molecule presents significant changes in the μs timescale after perturbation.

Figure 19. Transient reaction intermediates of retinal–bound rhodopsin after pulsed laser excitation. The black line represents the ellipticity of rhodopsin in lauryl maltoside micelles. Dark grey, light grey, and grey lines represent the ellipticity after 5, 100, and 500 μs of laser excitation. Adapted with permission from [17]. Copyright 2009 American Chemical Society.

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Chevron Plots Previous sections described methodological advances in coupling fast–induced conformation changes to circular dichroism. From these experiments, it is possible to obtain kinetic parameters that can be analyzed either by modeling the relation between those constants and the perturbation, or by applying empirical models. In this section, we will describe the analysis of these curves using the so–called ―Chevron plot‖ procedure. As was described before in this chapter, protein folding can occur through single or multiple transitions. Each of these is separated from the other by energy barriers. The difference between the energy of the native and unfolded states corresponds to the ∆G°H2O NU, and the difference in energy between one state and the top of the barrier is called the Energy of Activation (Ea), which is related to the free energy change for the formation of the activated complex (G‡). The height of this barrier can be determined measuring the kinetic constants at different temperatures and analyzing them using the Arrhenius equation. The numerical value of Ea is correlated with the probability of crossing this barrier and flip from the unfolded to the native state. In other words, the higher the barrier, the less likely it is to reach the transition state. Thus, the lower the likelihood, the slower the transition is. The simplest case in a folding transition is the shift from a native state (characterized by a molar ellipticity [θ]N at 222 nm) to a denatured state (which does not contribute to the CD signal at 222 nm), or vice versa. In this context, when time–resolved circular dichroism methods are used, the time course for folding or unfolding transitions can be followed. As was previously demonstrated (see equation 25), this process can be described in terms of single exponentials:

θ222nm  θ222nm e k Copyright © 2011. Nova Science Publishers, Incorporated. All rights reserved.

N

obs t

θ222nm  θ222nm (1  ek N

obs t

)

unfolding

(30)

refolding

(31)

If we repeat this for several denaturant concentrations, different apparent kinetic constants may be obtained. When mixing native protein with increasing denaturant concentrations, the observed kinetic constant is dominated by the unfolding constant (see equation 29). On the contrary, when mixing denatured protein with refolding buffer, the apparent kinetic constant is dominated by the refolding constant. If the observed rate constants are plotted as a function of denaturant concentrations, the so–called ―Chevron Plot‖ is obtained (Figure 20). Each observed constant is a linear combination of the unfolding and folding kinetic constants (equation 26). From these constants, one can obtain ∆G°H2O NU [60]. A good example of this analysis for a two states transition is the study of the folding kinetics of variant I53D of RNase H [97]. In Figure 20A, the observed kinetic constants of the folding process showed a typical V–shape when represented as a function of denaturant concentration, which is characteristic of a two–state process. The positive–sloped arm of the Chevron plot corresponds to the reaction going from a folded conformation to the unfolded one, and the opposite occurs for the other arm.

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Figure 20. Chevron plots for RNase H variants I53D (A), and I53V (B). In the upper right corner the energy levels for the transitions are schematized. N: native state, U: unfolded state, I: intermediate, and ts: transition state. Reprinted from [97], Copyright 2004, with permission from Elsevier.

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The folding and unfolding kinetic constants in water can be determined by fitting equation (29) to the experimental data, and the corresponding ∆G°H2O NU can be calculated by using equation (11). Moreover, the slopes of each arm of the plot provide information about the surface exposition upon denaturation with respect to the exposed surface of the transition state [98]. When studying another variant, I53V, the Chevron plot is different (Figure 20B). As denaturant concentrations become lower, the dependence of the rate constant with urea concentration is not linear. This behavior usually represents the appearance of a folding intermediate with a compact structure, similar to the native state [60]. A possible interpretation is that an intermediate I was stabilized at low denaturant concentrations, but it is absent at high denaturant concentrations. This interpretation is schematized in the inset to Figure 20B.

Mapping the Unfolding Transition State In the previous section, we described techniques to analyze the kinetics of folding and unfolding through one or many intermediates. From those experiments we calculated kinetic constants that correlate with protein transitions. From those constants we obtained a quantitative characterization of the energy barrier that separates the native and unfolded states. From the Chevron plot analysis we can calculate the unfolding and folding rate constants, which are related through the G° for the native to unfolded transition. Suppose we perform an equilibrium circular dichroism experiment and calculate ∆G°H2O upon addition of a denaturant, as explained in the Equilibrium Unfolding section. Then using TRCD we measure the kinetics constants of folding and unfolding process at many concentrations of denaturant. This kinetic analysis can be repeated at different temperatures, and the activation free energy changes can be calculated. The equilibrium analysis gives us an idea of the thermodynamic stability of the protein, whereas the kinetic analysis aids us in the NU

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understanding of the separation between a transition state and the fully folded or fully unfolded states. Now, a given residue is mutated, for example in a C-terminal region of a protein, for another residue, and the previously described experiments are repeated. If we take the unfolded state as an arbitrary reference state, we will obtain a ΔΔGN-D and a ΔΔG‡D. As was proposed by Fersht [99], these two quantities can be related by:

ΦF =

ΔΔG‡-D ΔΔGN − D

(32)

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The quantity ΦF is called the “Phi value” and ranges from 0 to 1. ΦF = 0 indicates that the mutation destabilizes the transition state in the same way as the denature state. It means that the structure in the unfolded state of that region is similar to the structure in the transition state. In the case of ΦF = 1, the transition state is perturbed in the same way as the native state. This means that the structure of the region in the native state corresponds well with the structure in the transition state [60].

Figure 21. Crystal structure of wt RNase H. The mutant variants were built using the program Swiss PDB Viewer (http://spdbv.vital-it.ch/).

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Table 1. Phi values for different RNase H mutants

Reprinted from [15], Copyright 2010, with permission from Elsevier.

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Suppose the example of the RNase H discussed in the previous section. Looking at the structure of the protein (Figure 21), it is seen that the terminal helices are interacting. Previous studies from Marqusee laboratory showed that substitution of the residue 53 of helix A destabilizes the early folding core between helix A and D [100]. Thus, a subset of stabilizing and destabilizing mutations that affect this interaction would give a clue on the presence of this core in the transition state of the folding reaction. The assayed mutations were studied by steady state and stopped flow circular dichroism. Combining kinetics with thermodynamics, the Φ values were calculated using equation (30), and the results are listed in Table 1. ΦI and Φ‡ represent the phi values for the kinetic intermediate and for the transition state of the reaction. Clearly, mutations on the core residue I53 induces different effects depending on the physicochemical properties of the amino acid residue that is introduced. Mutation of Ile to Leu destabilizes the native state as ∆G°H2O shifts from 9.7 kcal mol -1 to 8.3 kcal mol -1. However, the ΦI and Φ‡ close to zero indicates that although the native state is markedly destabilized, neither the intermediate nor the transition state are significantly affected by the mutation. In contrast, mutation of Ile to Ala reduced the stability from 9.7 kcal mol -1 to 7.5 kcal mol -1 and ΦI and Φ‡ are almost 1. This indicates that both, the intermediate and transition states are destabilized to the same extent as the native state. In the case of mutation of Ile to Phe, the ΦI is 0.8, indicating that the effect of the mutation in the intermediate is smaller when compared to the transition state. However, the Φ‡ of 1.1 indicates that the transition state is more destabilized than the native state. The case for the Ile to Asp mutation is similar to the previous one, although the intermediate is highly destabilized, thus not appearing in the kinetic traces. However, addition of the stabilizing agent Na2SO4 stabilizes the intermediate relative to the native state, and destabilizes the transition state relative to the native state. This set of results can be summed as follows:

The energy barriers for mutation I53D are represented in grey traces. Here, the intermediate is highly destabilized resulting in its disappearance. The transition state and the native state are also destabilized; however, the effect on the first is stronger than in the native Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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state. In the presence of Na2SO4 (dashed lines), the intermediate is stabilized; thus, it is detected in the Chevron plot with a ΦI of 0.88. Then, the transition state and the native state are also stabilized, however, the effect on the transition state is stronger, thus, the Φ‡ is 1.3.

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CONCLUSION Circular dichroism has been used for several decades to characterize protein unfolding transitions. The main goal of these studies has been the elucidation of molecular mechanisms needed to acquire protein structure. Both equilibrium and time–resolved unfolding studies were needed to reach an understanding of mechanistic clues in this astonishing area. The development of modern CD instruments and alternative electromagnetic light sources, such as Xenon lamps or synchrotron radiation, has been critical for advances in this field. Time resolution can be achieved when CD detection is coupled to manual mixers or rapid mixing devices, allowing to explore rapid folding events in the s to ms time scales. Also, perturbation techniques, such as temperature or pressure jump, aided in the ns to μs time scales. These experiments enabled to dissect the folding reaction into steps. Far–UV and near–UV CD spectra have been largely used to show the coexistence of native–like secondary structure with no consolidated tertiary structure in molten globule forms. In other cases, results have enabled us to propose extremely cooperative folding mechanisms in which secondary and tertiary structures consolidate simultaneously. Clearly, CD is an excellent choice to perform conformational studies of protein and peptides, including extraordinarily large and complex systems (e.g., membrane proteins in their biological environments). From a practical point of view, it should be noted that the difference in absorption of right– and left–handed circularly polarized light by a protein sample is very small. In the far–UV region, it is in the range of 10-4 absorbance units. This needs accurate measurements of less than 0.1% of the total absorption signal. For this reason, a careful sample preparation is important. Special care should be taken with solvent transparency, and cell path length. More important, the existence of protein aggregation may be controlled. In addition, it is very important to routinely calibrate the CD instrument. Furthermore, evaluation of protein stability, structure induction by cosolvents, the effect of the addition of osmolytes in buffers, and the existence of partially folded states all are easy to be carried out. By always combining CD experiments with other tools for the study of protein conformation (e.g., florescence, light scattering, and NMR), we will have a better and complete picture of the phenomena under study.

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In: Circular Dichroism: Theory and Spectroscopy Editor: David S. Rodgers

ISBN: 978-1-61122-522-8 2012 Nova Science Publishers, Inc.

Chapter 6

ULTRAFAST TIME-RESOLVED CIRCULAR DICHROISM IN A PUMP-PROBE EXPERIMENT François Hache* Laboratoire d'Optique et Biosciences, Ecole Polytechnique, CNRS/INSERM Palaiseau cedex, France

ABSTRACT

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Circular dichroism (CD) is known to be a very sensitive probe of molecular conformation, and it is in particular widely used in biochemistry. Measuring the CD as a function of time is therefore very appealing to access information on the dynamics of conformational changes in molecules or biomolecules. An idea developed in the last decade is to implement the measurement of circular dichroism in a pump-probe experiment, which should allow one to access changes of CD with an unprecedented time resolution, down to the subpicosecond range. The most straightforward way to do so is to modulate the probe polarization form left to right circular and to measure the CD as a function of the pump-probe delay. This technique is however prone to many artifacts and one must be very careful when carrying out measurements. An alternative technique relies on the measurement of the pump-induced probe ellipticity. Although less direct, this technique is much more robust and very well fitted for measurements in the ultraviolet. Both techniques are described in details in this article. We then present several results obtained with these techniques. First, demonstration of the technique is made on the dynamics of the binaphthol dihedral angle after photoexcitation in the ultraviolet. We then present a complete study of the dynamics of conformational changes following photolysis of carboxy-myoglobin. Combining time-resolved CD in the visible and in the far-ultraviolet with classical calculations of CD based on coupled oscillators, we can assign the 100 ps dynamics that we measure to a transient deformation of the proximal histidine following the heme doming. Extension of these techniques to longer timescales, and particularly to the protein folding problem will be addressed in conclusion.

*

E-mail: [email protected]

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François Hache .

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I. INTRODUCTION Circular dichroism (CD) is an optical characteristics of chiral molecules and as such, it is a very sensitive probe of the conformation of molecules. It has in particular found very important application in biochemistry where measuring the CD spectrum in the ultraviolet provides valuable information on the content in secondary structure of an unknown protein [1], [2]. However, CD is usually a very weak signal. CD, which is the difference in absorption for a left or a right circularly-polarized light, typically amounts to a few 10-4 – 10-3 of the normal absorption. Such small variations are difficult to detect and commercial CDspectrophotometer requires a long averaging time to measure CD with accuracy. This feature prevents measurement of CD with a good time resolution and most measurements deal with molecules or proteins in their steady-state. However, in many cases, much information relevant to chemical or biophysical issues lies in the dynamics and one major problem is often to be able to measure signals with a good time resolution. This is particularly true for CD. Since CD is a probe of the conformation of molecules, measuring the CD as a function of time would allow one to gain knowledge on the dynamics of molecular conformational changes which are known to play an important role in many processes. Let us cite in particular the biophysical problems in which conformational change are especially important. A non-exhaustive list contains for example enzymatic reactions where the activity of the biocatalyst is triggered by such a conformational change [3], signal transduction through membrane where activation of a membrane protein in the outer side provokes a structural change in the inner side which in turn triggers a reaction chain like G protein – coupled receptors [4], or such phenomenon as vision whose first step is the photoisomerization of the retinal [5]. Another issue where conformation is of primary importance is the protein folding problem [6]. The mechanisms by which a randomly-synthesized protein acquires a definite three-dimensional structure in a very rapid time are still subject of thorough research and the possibility to follow in time the secondary or tertiary structure of biomolecules is of primary importance. These few examples show that conformational changes must often be studied with a very good time resolution. If elementary protein folding timescales lie in the hundreds of nanoseconds, basic processes such as enzymatic reactions or first vision steps involve much shorter timescales down to picoseconds. It has therefore rapidly appeared that measuring CD with a very short time resolution was a mandatory step towards the investigation of such biophysical processes. Time-resolved absorption spectroscopy has been developed for decades and the most simple way to access such short timescales is based on pump-probe experiments. Such experiments are based on the use of pulsed lasers. Two independent pulses must be generated: an intense one, called the "pump", is intended to trigger a modification in the samples whereas a second one, weaker, called the "probe" serves as a measure of the perturbed sample. The principle of the experiment is therefore to measure the characteristics of the probe as a function of the time-delay elapsed between the excitation by the pump and the probing stage. The time resolution of such experiments is clearly limited by the pulse duration. With lasers currently delivering femtosecond pulses, very high time resolution can be achieved. In most cases, the characteristics of the probe which are monitored are basic properties like absorption or fluorescence. In more sophisticated cases, it can also be Raman emission. These probes can give very exciting information on the ultrafast dynamics of

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

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molecular systems, but unfortunately, they don't provide direct information on the molecular conformation. Use of this conventional pump-probe techniques to access such information relies on "tricks" such as FRET (Förster resonant energy transfer) [7] or conformationaldependence of Amide I' bands in proteins [8]. Conversely, CD is a unique means to access conformational information in a much more direct way. The challenge is therefore to implement CD in a pump-probe experiment. Pioneering work in that direction was performed by Kliger [9] and Simon [10] in the 80's. By inserting a polarization modulator in the probe path (a technique similar to the first one described in this article), they could measure timeresolved CD (TRCD) with a nanosecond or picosecond resolution [11]. Extension towards time-resolved optical rotation has also been proposed [12]. Note also that there has been recently very interesting extension of these techniques towards time-resolved vibrational CD. Thanks to the wealth of vibrational transitions, such measurements should be very fruitful. Interesting reader are referred to Ref. [13]. In this article, we present further developments of this technique. First of all, we have extended the pump-probe CD experiment towards femtosecond and far – ultraviolet pulses. Furthermore, two complementary techniques have been developed. The first one is a regular one based on probe polarization modulation. Implementation of this technique with a femtosecond source has revealed many artifact problems that had to be solved prior to any valuable measurement. The second one relies on measurement of change in the beam ellipticity. Although much less direct than the first one, this technique is much more robust and very well adapted to measurements in the far UV. This article is organized as follows. We first recall some basics on CD and present fundamentals of the two TRCD techniques. We then detail the practical implementation of these techniques in our experimental set-up and discuss the advantages and drawbacks of each. In section IV, we present results that we have obtained with Binaphthol. Changes in the dihedral angle following photoexcitation is clearly evidenced and measurement of the dynamics of these changes is obtained for various solvents. Section V is devoted to a whole set of experiments and theoretical simulations that we have carried out on the photodissociation of carboxy-myoglobin. In view of a classical model of CD based on the coupling of oscillators, the TRCD curves are understood and the role of the proximal histidine is outlined. Finally, we present perspective of this work towards the study of the protein folding problem.

II. BASICS OF TIME-RESOLVED CIRCULAR DICHROISM Let us start by some basic definitions. The absorption coefficient is denoted  and the transmission of a sample of thickness L is e-L. CD, as we will use it in this article, is defined by CD = (LR)L

(1)

where L (resp. R) is the absorption coefficient for a left (resp. right) circular polarization. As such, CD is dependent on the sample thickness and on its concentration. It is connected to the molecular dichroic absorption by

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François Hache (2)

where c is the sample concentration (in M). Let us also recall that a linearly-polarized beam passing through a chiral sample becomes elliptically-polarized and that this ellipticity is a direct measure of the CD. It is therefore current to express the CD as a molar ellipticity expressed in radians defined through (3) We will now examine the two manners to measure the CD in a pump-probe experiments that we have implemented in our experiments.

Probe Polarization Modulation Since CD is related to the difference between left and right polarizations, the most straightforward way to measure CD is to modulate the probe polarization and to detect the subsequent transmission modulation. This is the usual way to measure CD, as carried out in commercial CD spectrophotometers. Extraction of the CD is readily obtained through the use of a lock-in amplifier locked on the modulation frequency. The signal transmitted through the sample is monitored by a photomultiplier tube (PMT), the output of which is sent to the lock-in amplifier. Calling LR)/2 the mean absorption coefficient andLR, one obtains that the transmitted signal reads

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(4) where the '+' (resp.'–') sign corresponds to left (resp.right) circular polarization. Because CD is small, this can be written (5) The signal measured by the PMT is the nonmodulated part of S whereas the LI signal provides the modulated part. If the polarization modulation is square-shaped, the CD can be obtained from the following formula: (6) Acquiring PMT and LI signals as a function of the pump-probe delay therefore directly yields the TRCD. At negative delays, when the pump arrives after the probe, one obtains the steady-state CD whereas at positive delays, one can follow the evolution of the CD with time. The principle is very simple. However, because CD is very weak, strong averaging is often necessary to get the signal out of the noise. Furthermore, as will be discussed later, in a pumpprobe configuration, there exist strong artifacts which must be carefully addressed.

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Ultrafast Time-resolved Circular Dichroism in a Pump-Probe Experiment

P

Sample

A BS

Probe

PMT

LI

Pump Figure 1. Schematic of the experimental set-up. The sample is placed between a polarizer (P) and a crossed analyzer (A) together with a Babinet-Soleil compensator (BS). A chopper (C) is inserted in the pump path. The transmitted signal is detected with a photomultiplier (PMT) and demodulated with a lock-in amplifier (LI).

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Pump-induced Ellipticity As outlined above, CD can also be measured as the ellipticity generated on a linearlypolarized beam passing through a chiral sample. One can therefore consider another set-up to measure CD without modulating the probe polarization. The set-up is depicted in the figure 1. The sample is placed between a polarizer and a crossed analyzer. After the sample, we insert a Babinet-Soleil compensator (BS). A BS is a tunable waveplate whose retardation can be finely tuned. In order to analyze the behavior of this set-up, let us introduce Jones matrices [14]. In the laboratory frame, an incoming electric field propagating in the z direction is depicted with a vector in the (x,y) plane. If the polarizer is aligned along x, the electric field arriving on the sample is .

(7)

Each optical element can be described by a 2 × 2 matrix and the output electric field reads (8) MSample is the matrix describing the sample taking optical activity into account. Its calculation follows the one given in Ref [14]. Let us first define the relevant parameters. Let nL, nR, αL, αR be respectively the refractive indices and the absorption coefficients for the left and right circular polarization. For a sample thickness L, we define the optical rotation (OR) , and the circular dichroism (CD)

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

(9)

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(10)

Considering that both OR and CD are very small quantities, we develop to the first order and we obtain for the matrix MSample

,

(11)

where α = ((αL+αR)/2) is the mean absorption coefficient (in intensity). This matrix takes CD and circular birefringence into account. These two effects commute and can be considered together without trouble [14]. Complete calculation without development is described in Ref. [15]. For a BS whose axes are oriented at 45° compared to the laboratory frame, and calling 2φ its retardation, we obtain .

(12)

Finally, denoting ε the analyzer angle (measured with respect to the cross position), we obtain (for ε whose elements tis

correspond to the

contribution of the oscillator is: (25) With the help of these normal modes, one obtains the oscillator and rotational strengths for the normal mode |n> as (e, m: electron charge and mass, c: light velocity, NA: Avogadro number; the refractive index is supposed to be equal to 1) (26) and

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Table 1. Parameters of the heme and of the individual aromatic amino acids utilized to model the MbCO and Mb CD spectra with the coupled oscillator calculation

(a) Angle (in degrees ) of the transition moment with respect to the x-axis. (b) M.C. Hsu and R. W. Woody, J. Am. Chem. Soc. 93, 3513(1971). (c) D. M. Rogers and J. D. Hirst, J. Phys. Chem. 107, 11191 (2003).

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Ultrafast Time-resolved Circular Dichroism in a Pump-Probe Experiment 200 (a)



(c)

60 40

100

 20

0

0 200 (d)

(b)



60 40

100



20 0

0 400

425

450

475

Wavelength (nm)

400

425

450

475

Wavelength (nm)

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Figure 9. Steady-state absorption and CD spectra in MbCO (upper curves) and Mb (lower curves) and their fits.

When expressing the frequencies in eV and the rotational strengths in DBM (Debye-Bohr magneton), the absorption and the CD read (28)

(29) In order to reproduce the steady-state absorption and CD spectra for MbCO and Mb, we have utilized the parameters in Table I [28]. The spectra are displayed in Figure 9 (MbCO and Mb curves). These curves give a satisfactory agreement.

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80 70 60 MbCO Mb* Mb** Mb

50

CD

40 30 20 10 0 -10

400

450

500

Wavelength (nm)

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Figure 10. Calculated CD spectra for MbCO, Mb and two intermediate configurations (see text).

Experiment Simulation We want here to utilize our calculations to better understand the experimental signals that we have obtained (Figure 7). Even though we know the starting and ending points (MbCO and Mb), it is not sufficient to consider the corresponding steady-state CD spectra to understand our data. The first reason is that following the CO dissociation, the heme undergoes an instantaneous electronic transition from a low-spin state to a high-spin one. As already stated, this change is accompanied by a shift of the transition frequencies as well as a decrease of the oscillator strengths. Furthermore, the heme domes and the iron atom moves out of the heme plane by a fraction of an Angström. This doming is responsible for the larger coupling between electronic and vibrational transitions. This change of electronic transitions automatically induces a change of CD which has nothing to do with a conformational change. It is therefore important to calculate the CD for intermediate configurations in order to single out the effects of conformational changes. In the following, we consider several relevant intermediate configurations. The predicted CD spectra are displayed in Figure 10. As a first intermediate configuration, that we denote Mb*, we consider the case where the protein geometry is the same as MbCO but where the electronic state of the heme has been shifted to the Mb one. Even though this configuration has no real existence because the change in the electronic transitions and doming of the heme are closely connected, it serves as a starting point of the conformational changes after getting rid of the variation of the electronic state. The predicted CD change when going from MbCO to Mb* corresponds to the instantaneous drop observed at 422 nm (near the MbCO peak) and to the instantaneous increase at 440 nm (near the Mb peak). Following this very first step, we have simulated the effect of the change of geometry of the heme. We have therefore taken the geometry of MbCO for all the amino acids except for the heme. We have also considered the case where the heme and the proximal histidine have been moved to their final geometry. In both cases, the corresponding CD spectra are very

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260 nm 230 nm

0.0

100

-0.5

0

-1

 (M cm )

-1 0 0

-1

Differential circular dichroism

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close to the final Mb CD spectrum. This interesting feature shows that the large CD change that we observe in our experiment cannot be related to a progressive change from the MbCO geometry to the Mb one. We have therefore to examine other possible explanations of our observations. Given the importance of the proximal and distal histidine in the origin of the CD spectrum, we have examined the effects of a rotation of the imidazole planes on the CD spectra. Rotating the distal histidine in fact did not lead to a large change and even though such movements are probable due to collisions of the CO in the first docking site, they cannot be invoked to interpret our experiment. Rotation of the proximal histidine about the axis perpendicular to the heme proved to deeply affect the CD spectrum [29]. This result of our calculation is surprising at first sight because the proximal histidine does not provide a large contribution to the total rotational strength due to is perpendicular position with respect to the heme. The reason for the huge effect of this rotation is to be sought in the coupling between the heme and the proximal histidine which mainly determines the normal modes of the system. When His93 is rotated, the positions and the oscillator strengths of the normal modes do not change appreciably but their composition in terms of original transitions is strongly modified and so is the repartition of the rotational strength between the two modes. This change translates into a large modification of the CD spectrum [28]. We have considered a rotation of π/6 (Mb** in Figure 10). One can see that the CD decreases strongly in this case. Even though this rotation is somewhat artificial, it is clear that a deformation of His93 is expected to completely change the shape of the CD spectrum.

-200

Mb MbCO

-3 0 0

-4 0 0

-1.0

200

220

240

260

280

300

320

Wavelength (nm)

0

100

200

300

400

Pump-probe delay (psec) Figure 11. Time-resolved differential circular dichroism (in arbitrary units) at 260 and 230 nm probe wavelengths following MbCO photolysis.

Interpretation of the Experiment Thanks to the previous calculation, we are able to propose a mechanism responsible for the strong transient CD structure that we have observed following the photodissociation of MbCO. The major role of the proximal histidine is clearly evidenced in the calculation. We

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therefore propose that the transient CD signal comes from a temporary deformation of the proximal histidine subsequent to the heme doming. This histidine is attached on one end to the iron atom and on the other end to the F helix, which represents a quite heavy structure. When the iron atom goes out of the heme plane, the histidine becomes squeezed between the iron atom and the F helix and we think that this results into a deformation of the histidine which is responsible for the transient CD we observe. In order to relax its stress, the histidine pushes the F helix, triggering larger scale conformation changes in the protein. Our measurements show that the relaxation of the histidine is over within 100 ps, a very short timescale. Note that this timescale is consistent with global relaxation measurements carried out in MbCO [30].

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TRCD in the Ultraviolet As can be seen in the inset of Figure 11, there are two spectral region in the UV where MbCO and Mb display a CD structure. The first one around 260 nm is likely to involve aromatic amino acids and especially tryptophan whereas the second one below 230 nm is known to correspond to the protein backbone. We have investigated TRCD in these two regions and results are depicted in Figure 11. At 260 nm, we observe an instantaneous passage from MbCO to Mb. No dynamics is observable. This feature, in association with pump-induced absorption change measurement [16], is an indication that contrarily to what was expected, tryptophans do not play a dominant role in the CD signal in this region and here again, TRCD does not provide information on the long range motion involving the whole protein. We can assign CD for this wavelength mainly to the heme. This assertion however puts question. How come we don't see a transient structure similar to the one we observe in the Soret band when the proximal histidine gets squeezed ? The answer can be understood by considering the CD curves: CD for Mb is very small at this wavelength contrarily to MbCO. Therefore, the change of CD we measure is actually due to the vanishing of the CD when passing from MbCO to Mb. During the intermediate steps described in the previous section, the Mb* or Mb** CD spectra are expected to be even smaller than the Mb one. They are therefore not expected to display any strong feature even when the proximal histidine becomes distorted. Things are completely different at 220 nm. Let us first recall that the major origin of CD at this wavelength lies in the presence of the α-helices which compose the myoglobin backbone. The experimental signal at 220 nm is however very similar to the one observed in the visible with a rapid decrease followed by a total relaxation in 100 psec. Actually, there is a striking difference with the CD measured in the visible: the CD being negative at 220 nm (see inset), the TRCD corresponds to an increase in absolute value of the CD. This feature is quite interesting and this transient increase of the CD can be tentatively assigned to a deformation of the F helix consecutive to the heme doming and to the aforementioned proximal Histidine squeezing. The similarity of the timescales in the visible and in the UV would therefore originate in the common origin of the two signals.

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VI. PERSPECTIVES : PROTEIN DYNAMICS A domain where TRCD could advantageously complement existing technique is protein dynamics and more specially, protein folding. Indeed, CD has been used for a long time to investigate the 3D structures of proteins [2]. It is well known that the CD in the far UV is very characteristics of secondary structures, with specific features pertaining to α-helices or βstrands. It is current that for proteins for which no X-Ray structure determination exists, one uses déconvolution of the far-UV CD spectrum to gain information on the content of an unknown protein in secondary structures. Deconvolution programs are available [31, 32]. Note also that this discipline is knowing a real boost thanks to the availability of UV radiation down to 160 nm with synchrotron radiation [33]. Thanks to the possibility to follow CD with a very good time resolution, TRCD is very well fitted to observe rapid phenomena in processes such as protein folding. In particular, probing the CD in the 220 nm band allows the fraction of α-helices to be monitored in real time during formation or denaturation processes. Current techniques rather rely on the IR absorption in the Amide I' band which are known to be dependent of the secondary structure [8]. However, due to the breadth of these IR bands and their small separation, this technique is rather qualitative. Measuring the CD would clearly be a complementary technique, hopefully more quantitative. Investigating complex processes such as protein folding in a pump-probe experiment is a real challenge, especially because it is not easy to trigger such processes with a laser pulse. The most popular technique is the T-jump where one utilizes a nanosecond laser pulse to instantaneously heat up the water surrounding the studied protein [34]. Other techniques exist. The reader is referred to ref. [35] for a review on these issues common to all the experiments. We want here to comment on a few points that must be addressed to apply TRCD to such processes. First of all, it is clear that the timescales involved in protein folding are much longer than the one presented in this article. Most rapid phenomena have been shown to occur on hundreds of nanoseconds for short polypeptides [36] and the fastest protein folding timescales are in the microsecond range [37]. For such times, usual pump-probe experiments where the delay is changed with an optical line are no longer possible and one has to utilize two lasers with an electronic synchronization [38]. Furthermore, studying such "slow" processes impair the use of very high repetition rate for the lasers, which in turn strongly degrades the sensitivity of the technique based in part on a strong averaging of fluctuating measurements. On the other hand, CD around 220 nm is remarkably strong since it amounts to percent compared to the absorption. This feature is very favorable and should correct this problem. Another issue when working in a T-jump scheme is the estimation of the laser-induced temperature jump. This is usually performed directly with the IR probe. In case of CD in the far UV, this characteristics is no longer available and new calibration techniques must be proposed. In spite of all the technical challenges that exist to implement far-UV TRCD to measure protein folding dynamics, we think that this technique could bring a quantitative probe which would beneficially complement the existing techniques.

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CONCLUSION Time-resolved circular dichroism is a very attractive technique to access information on the rapid dynamics of conformational changes in molecules or biomolecules. In spite of the extreme weakness of CD signals, it is possible to measure TRCD with a good precision and we have depicted two such techniques used in a pump-probe configuration. The first one relies on the modulation of the probe polarization from left to right circular whereas the second one is based on pump-induced ellipticity measurements. Advantages and drawbacks of the two techniques are discussed. Applications of these techniques to the measurement of ultrafast conformational relaxation in binaphthol and in carboxy-myoglobin have been described. In both cases, elementary molecular motions are monitored with an unprecedented time resolution. TRCD should be applied to many other chemical issues. However, the brightest future should lie in the protein folding issue. The well-known relationship between UV CD spectra and secondary structures permits to envision fruitful applications of TRCD to this crucial problem, allowing in particular very first steps of secondary structure formation to be investigated.

ACKNOWLEDGMENTS Thibault Dartigalongue, Claire Niezborala and Mai-Thu Khuc have carried out most of the experimental work described in this article.

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Adler, A. J.; Greenfield, N. J.; Fasman, G. D. In Methods in Enzymology; Hirs, C.; Timasheff, S. N.; Ed.; Academic Press: New-York, 1973; pp 675-735. [2] Fasman, G. D. Ed. Circular dichroism and the conformational analysis of biomolecules; Plenum Press: New York, 1996. [3] Garcia-Viloca, M.; Gao, J.; Karplus, M.; Truhlar, D. G. Science 2004, 303, 186-195. [4] Park, P. S. H.; Lodowski, D. T.; Palczewski, K. Annu. Rev. Pharmacol. Toxicol. 2008, 48, 107-141. [5] Smith, S. O. Annual Review of Biophysics 2009, 39, to appear (june 2010). [6] Dill, K. A.; Ozkan, S. B.; Shell, M. S.; Weikl, T. R. Annu. Rev. Biophys. 2008, 37, 289316. [7] Liman, E. A.; Schuler, B.; Bakajin, O.; Eaton, W. A. Science 2003, 301, 1233-1235. [8] Surewicz, W. K.; Mantsch, H. H.; Chapman, D. Biochem. 1993, 32, 389-394. [9] Lewis, J. W.; Tilton, R. F.; Einterz, C. M.; Milder, S. J.; Kuntz, I. D.; Kliger, D. S. J. Phys. Chem. 1985, 89, 289-294. [10] Xie, X.; Simon, J. D. Rev. Sci. Instrum. 1989, 60, 2614-2626. [11] Kliger, D. S.; Lewis, J. W. In Circular dichroism - Principles and applications; N. Berova, K. Nakanishi and R. W. Woody; Ed.; Wiley-VCH: New-york, 2000; pp 243259.

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[12] Shapiro, D. B.; Goldbeck, R. A.; Che, D.; Esquerra, R. M.; Paquette, S. J.; Kliger, D. S. Biophys. J. 1995, 68, 326-334. [13] Helbing, J.; Bonmarin, M. Chimia Int. J. Chem. 2009, 63, 128-133. [14] Xie, X.; Simon, J. D. J. Opt. Soc. Am. B 1990, 7, 1673-1684. [15] Niezborala, C.; Hache, F. J. Opt. Soc. Am. B 2006, 23, 2418-2424. [16] Dartigalongue, T.; Niezborala, C.; Hache, F. Phys. Chem. Chem. Phys. 2007, 9, 16111615. [17] Dartigalongue, T.; Hache, F. J. Opt. Soc. Am. B 2003, 20, 1780-1787. [18] Niezborala, C.; Hache, F. J. Am. Chem. Soc. 2008, 130, 12783-12786. [19] Rettig, W.; Maus, M. In Conformational analysis of molecules in excited states; J. E. Waluk; Ed.; Wiley-VCH: New-York, 2000; pp 1-55. [20] Millar, D. P.; Eisenthal, K. B. J. Chem. Phys. 1985, 86, 5076-5091. [21] Kindt, J. T.; Schmuttenmaer, C. A. The Journal of Physical Chemistry 1996, 100, 10373-10379. [22] Karplus, M. In Hemoglobin and oxygen binding; C. Ho; Ed.; Elsevier: Amsterdam, 1982; pp 3-11. [23] Miller, R. J. D. Annu. Rev. Phys. Chem. 1991, 42, 581-614. [24] Franzen, S.; Kiger, L.; Poyart, C.; Martin, J.-L. Biophys. J. 2001, 80, 2372-2385. [25] Dartigalongue, T.; Hache, F. Chem. Phys. Lett. 2005, 415, 313-316. [26] Hsu, M. C.; Woody, R. W. J. Am. Chem. Soc. 1971, 93, 3515-3525. [27] Applequist, J.; Sundberg, K. R.; Olson, M. L.; Weiss, L. C. J. Chem. Phys. 1979, 70, 1240-1246. [28] Dartigalongue, T.; Hache, F. J. Chem. Phys. 2005, 123, 184901-1/9. [29] Dartigalongue, T.; Hache, F. Chirality 2006, 18, 273-278. [30] Miller, R. J. D. Acc. Chem. Res. 1994, 27, 145-150. [31] Sreerama, N.; Woody, R. W. Anal. Biochem. 2000, 287, 252-260. [32] Whitmore, L.; Wallace, B. A. Nucl. Acids Res. 2004, 32, 668-673. [33] Wallace, B. A.; Janes, R. W. Curr. Opin. Chem. Biol. 2001, 5, 567-571. [34] Callender, R. H.; Dyer, R. B. Curr. Opin. Struct. Biol 2002, 12, 628-633. [35] Volk, M. European Journal of Organic Chemistry 2001, 2001, 2605-2621. [36] Petty, S. A.; Volk, M. Phys. Chem. Chem. Phys. 2004, 6, 1022-1030. [37] Eaton, W. A.; Muñoz, V.; Thompson, P. A.; Henry, E. R.; Hofrichter, J. Acc. Chem. Res. 1998, 31, 745-753. [38] Bredenbeck, J.; Helbing, J.; Hamm, P. Rev. Sci. Instr. 2004, 75, 4462-4466.

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In: Circular Dichroism: Theory and Spectroscopy Editor: David S. Rodgers

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Chapter 7

ON THE UTILITY OF CIRCULAR DICHROISM SPECTROPOLARIMETRY IN ASSESSING PROTEIN INTERACTIONS WITH NANOPARTICLES Michael J.W. Johnston*, and Mary Alice Hefford Centre for Vaccine Evaluation, Biologics and Genetic Therapies Directorate, Health Canada

1. ABSTRACT

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Nanotechnology is the manipulation of material resulting in the production of particles or structures at the nanoscale with distinct characteristics that are novel or superior as compared to the bulk material [1]. The resulting nanoparticles, due to their small size, may demonstrate altered physical, chemical and/or biological properties. One of the most promising avenues for nanotechnology is in the medical field. Nanoparticles are currently being used or are proposed as effective means for medical imaging and as vehicles for vaccine and drug delivery. As a result of the increased surface/volume ratio nanoparticles display compared to the bulk form of the material and the increased reactivity for a given weight of material, interactions between nanoparticles and biological systems are of increased concern. Of particular interest is the potential for enhanced interaction with proteins; either those natively to the body or those administered with the nanoparticle as a therapeutic. Nanoparticle/protein interactions may cause protein conformational changes resulting in alterations in and/or abolition of function or, if severe enough, immunological recognition of the protein as foreign [2]. This chapter will review the utility of circular dichroism spectropolarimetry, a technique classically used to assess the secondary and tertiary structure of proteins, as a method for assessing conformational changes in proteins adsorbed to the surface of a nanoparticle, encapsulated as a drug payload within a nanoparticle or externally conjugated to the nanoparticle and functioning as a targeting ligand.

*

To whom correspondence should be addressed. PhD. Research Scientist, Centre for Vaccine Evaluation, Biologics and Genetic Therapies Directorate, Health Canada, 251 Sir Frederick Banting Driveway: Locator 2201E, Tunney‘s Pasture, Ottawa, Ontario, Canada K1A 0K9. Email [email protected]; Tel: 1-613-9411540; Fax: 1-613-941-8933

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2. INTRODUCTION 2.1. Nanoparticles and Medical Applications The rapid development of nanotechnology and ensuing controlled production of nanoparticles are driving forces for new paradigms in the biomedical field for the prevention, diagnosis and treatment of a wide range of medical conditions. These particles can be composed of a wide variety of materials including carbon nanotubes, organic polymeric constructs, metallic particles and lipids among many others. Nanoparticles are currently being used, or are proposed as, an effective means for medical imaging, and for vaccine and drug delivery.

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2.2. Nanoscale Drug Delivery Systems When both small molecule drugs and biotherapeutics are formulated in Nanoscale Drug Delivery Systems (NDDS) an increase in the effectiveness of the therapeutic agent [3;4]and a reduction of detrimental toxic side effects [5] is often observed, resulting in an improved therapeutic index. These benefits can be attributed to the ability of the NDDS to allow for regulated release of the therapeutic [4;6;7], the passive/active targeting of the NDDS and its therapeutic payload to sites of disease, reduced accumulation of the therapeutic agent in susceptible tissues, increased circulation lifetimes of the therapeutic and improved stability/solubility of some agents [8;9]. Numerous nano-scale drug delivery systems have been approved for clinical use (eg. Doxil (PEGylated liposomal doxorubicin), Myocet (liposomal doxorubicin), Abraxane (albumin/paclitaxel nanoparticles), AmBisome (liposomal amphotericin B) and Pegasys (PEGylated interferon)[10]) and the field is rapidly expanding with many more NDDS under development globally for the treatment of many diseases [1113] including malaria [14]. The most advanced NDDS are the lipid-based delivery systems (liposomes) with a number of systems approved for clinical use [11]. For example, a non-pegylated liposomal formulation of doxorubicin (Myocet, 150nm diameter lipid vesicles) which has been approved for the treatment of breast cancer, demonstrates comparable anti-tumor efficacy in relation to the free drug; but has an improved therapeutic index due to reduced cardiotoxicity and (grade-4) neutropenia [15;16]. Additionally, pegylated liposomal doxorubicin (Doxil/Caylex, 100nm diameter lipid vesicles) has been approved for the treatment of ovarian and breast cancers as well as AIDS-related Kaposi‘s sarcoma [15;16]. This pegylated formulation shows enhanced circulation life and greater area-under-the-curve (AUC), due to avoidance of the reticuloendothelial system, compared to free doxorubicin and non-pegylated liposomal doxorubicin formulations [15]. Clinical studies with pegylated liposomal doxorubicin have shown similar response rates and overall survival in ovarian and breast cancer treatments when compared to other small molecule therapies (i.e paclitaxel, vincristine etc.) [15]. However, reduced toxic side effects such as nausea/vomiting, hair loss, grade 3 and 4 leukopenia and cardiotoxicity were observed in numerous studies [15;16]. In the treatment of AIDS-related Kaposi‘s sarcoma, pegylated liposomal doxorubicin has shown significantly

Wilhite, Stephen C., and David S. Rodgers. Circular Dichroism: Theory and Spectroscopy : Theory and Spectroscopy, edited by David S. Rodgers,

On the Utility of Circular Dichroism Spectropolarimetry … improved response rates when compared to other doxorubicin/bleomycin/vincristine combination therapy) [15].

treatments

283 (bleomycin

or

2.3. Nanoscale Imaging Agents Through the use of nanotechnology, many of the currently utilized imaging technologies such as MRI (magnetic resonance imaging), PET (positron emission tomography), ultrasound and optical imaging can be enhanced. Nanoscale superparamagnetic particles (such as iron oxide nanoparticles) have been used as contrast agents for MRI with conjugation of these particles to components more readily taken up by cancerous cells allowing for the improved identification of tumor sites. This concept has been demonstrated by Kumar and coworkers who used a novel nanoscale membrane-permeable contrast agent containing superparamagnetic iron oxide to improve MRI detection of U-87 glioma tumor models in mice [17]. Superparamagnetic iron oxide nanoparticles have also been used as contrast agents for precision ultrastructural ultrasound in the characterization of malignant tissues. Sakamoto and coworkers demonstrated this technique by differentiating HER-2/neu positive SKBR-3 from non cancerous cells with the breast cancer targeting Herceptin antibody [18]. Finally; nanoparticles such as quantum dots can be used for optical imaging. These particles can be conjugated to targeting ligands, much like NDDS, to direct them to specific cells and tissues. For example, quantum dots conjugated to RGD (arginine–glycine–aspartic acid containing peptides) [19] peptides and VEGF protein (vascular endothelial growth factor) [20] have been used to image angiogenic blood vessels.

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2.4. Nanoscale Vaccine Delivery In addition to functioning as drug delivery systems and imaging agents, nanoparticles can also be used as delivery systems and/or adjuvants for vaccines, providing an alternative to conventional delivery systems and immunopotentiators [21]. These nanoscale systems can carry proteins or genetic material and have been developed for a wide variety of administration routes including trans-dermal, oral, nasal [22] and conventional intramuscular injection. Additionally, nanoparticle vaccines have the capacity for controlled release of the antigen and targeted delivery to antigen presenting cells [23]. An example of an approved nanoscale adjuvant is MF59, a 250nm sized emulsion of squalene, polysorbate 80 and sorbitan triolate in citrate buffer. Use of this nano-scale adjuvant has resulted in enhanced antibody titres in pigs vaccinated against glycoprotein D of herpes simplex virus [21]. Similar results have been observed in the clinic with antibody titres of seronegative patients when immunized against HIV, CMV and HSV [21].

2.5. Nanoparticle Interactions with Proteins When nanoparticles or NDDS are intravenously administered they are almost immediately coated with circulatory proteins. The composition of this protein corona is

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dynamic with proteins composing the soft corona (rapid dynamic exchange) and the hard corona (proteins/biological material with a higher affinity for the particles) [24]. The composition of the corona and its dynamics will be dependent on the particle size, surface chemistry, surface curvature and hydrophobicity of the nanoparticle. The composition of the protein corona will, in turn, determine the biological response and what cells in the body ―see‖ [2;24;25]. Circulatory proteins may adsorb onto NDDS and nanoparticles in a native like structural state or may adsorb with change to either the secondary and/or tertiary structure. Structural changes that are not severe enough to cause the protein to be recognized as foreign can still result in the exposure of epitopes that are usually buried within the protein core [2]. These structural changes and exposure of ―cryptic epitopes‖ may result in change/loss in protein function or changes in cellular responses. If the structural changes to the proteins of the corona are severe enough, protein(s) that compose the corona may be recognized as foreign, leading to the potential development of autoimmunity [2]. In addition to interactions between nanoparticles and circulatory proteins, nanoparticles and NDDS may interact with, and structurally modify their protein payloads and/or proteins conjugated to their surface functioning as targeting ligands or vaccine antigens. Any studies of these ―cryptic epitopes‖ or more severe structural changes in proteins will require well-characterized nanoparticle systems and proteins as well as techniques that can detect small changes in secondary and tertiary structure [2]. Numerous techniques are available to characterize protein secondary structure including; Fourier transform infrared spectroscopy, differential scanning calorimetry, NMR spectroscopy and circular dichroism spectroscopy. Of the available techniques, circular dichroism spectropolarimetry is, in the view of these authors, one of the simplest and most useful and hence is the focus of this chapter.

3. CIRCULAR DICHROISM Electronic circular dichroism spectropolarimetry is an optical technique in which leftand right-handed circularly polarized light come in contact with a solution that contains a chiral (optically active) substance. Whenever light impinges on matter, two things can happen: some of the light can be absorbed by the matter and/or the velocity of the light can be changed. When the light impinging on the matter is circularly polarized and the matter is composed of asymmetric (or chiral) molecules, differential absorbance (extinction) of leftand right-handed circularly polarized light gives rise to circular dichroism and differential changes in velocity (refraction) for the left- and right-handed circularly polarized light, resulting in circular birefringence. The former phenomenon is the basis for circular dichroism spectropolarimetry and the latter for optical rotary dispersion.

3.1. Theory The theory of circular dichroism has been covered in several reviews and textbooks [2634] and will not be explained in detail here. András Szilágyi, of the Hungarian Academy of

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Sciences has developed an excellent series of animated graphics that explain how electromagnetic radiation (and light) can be circularly polarized and how the interaction of such light with an optically active compound will result in circular dichroism and ellipticity. Readers are referred to his website (http://www.enzim.hu/~szia/cddemo) for a more detailed explanation.

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3.2. Circular Dichroism of Proteins Circular dichroism is one of several physico-chemical techniques used in the routine analysis of protein conformation. At appropriate concentrations, information on both the secondary structure and the tertiary structure of a protein can be gleaned. While CD is considered a low-resolution technique in that it does not give information about the conformation of specific amino acid residues within the protein, it does offer several advantages. It uses relatively low concentrations of protein (in the order of 0.05 to 1.0mg/mL for secondary structure analyses and of 0.5 to 2.0 mg/mL for tertiary structure analyses) making it much more sensitive than higher resolution techniques like NMR or X-ray crystallography. CD is, in and of itself, non-destructive and unless the experimental protocol dictates the exposure of the protein to denaturants or extremes of pH or temperature, protein samples can be recovered and used in other experiments after CD spectra have been obtained. CD is a solution technique and thus allows the observation of proteins in conditions that can approximate physiological conditions. Experiments can be completed in a very short time: a single determination in less than half an hour and a titration or temperature series in less than a day. Because only asymmetric molecules give rise to circular dichroism, the CD spectra of proteins can be determined in the presence of other substances as long as those substances are not completely opaque to light at the wavelengths where the protein spectra are measured. Indeed, protein spectra can often be successfully determined in the presence of other chiral molecules (like DNA, sugars, lipids) as long as those other molecules do not show significant ellipticity at the wavelengths where the protein spectra are being measured. Circular dichroism can be used to determine the secondary structure of proteins (percent helix, percent sheet, etc. See below, Section 4.3) but it is particularly useful in measuring changes in the secondary or tertiary structure of a given protein in response to changes in that protein‘s environment. As a result, CD spectropolarimetry has seen much service in the study of protein folding or unfolding as well as in studying conformational changes that result when a protein interacts with other molecules. It is in this latter context that CD spectropolarimetry is likely to be most useful in the study of nanoparticles (Section 3.5, below).

3.3. Estimation of Protein Secondary Structure by Circular Dichroism Three regions of the electronic CD spectrum are important for the analysis of protein structure: the far UV (below 250 nm and now extending into the vacuum ultraviolet region at 178 nm), the near UV (from 250 to 300 nm) and the near UV-visible region (300 to 700 nm)[35]. These regions contain information about protein secondary structure, protein tertiary structure and protein prosthetic groups (such as heme, iron-sulphur or flavin [36]),

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respectively. By far the most studied and most often analyzed region of CD spectra is the far UV. The major chromophore in the far UV spectral region (190 to 250 nm) is the peptide bond, an amide linkage with 4  electrons in 3  orbitals and 2 non-bonding electrons that can absorb light to undergo n * and  * transitions[37]. In folded proteins, the amide bonds are arranged in regular, repeated structures such as -helices and parallel and antiparallel -sheets. The ―ordered array‖ of these secondary structural elements places several identical chromophores (peptide bonds) in close proximity allowing energy exchange between adjacent chromophores and the ensuing ―exciton splitting‖[37;38] as well as hypochromism (in the case of -helices) or hyperchromism (with -sheet structures) observed in typical protein spectra[32;39]. These theoretical calculations (which have recently been reviewed and updated [40-42]) predict that -helical structures should have a positive CD signal at 190 nm and a negative signal at 208 nm, both of which result from the exciton splitting of the  * transition, as well as a negative ellipticity at 222 nm resulting from the n * transition. Experimental CD spectra of ―pure‖ -helices do show the predicted strong negative bands at 222 and 208 nm as well as the strong positive band centered around 190 nm. Similarly, theoretical calculations [43] for pure -sheets predict that the n * transition will give a negative band near 215 nm and that the  * exciton split will produce a positive band near 198 nm coupled with a negative band near 178 nm. These bands, however, are less intense than those observed for -helices. Experimentally, obtaining ―pure‖ -sheet structures has proven rather more difficult because the geometry of -structures in proteins and peptides are varied (parallel and anti-parallel, for example) and tend to twist [44;45]. In addition, peptides in ―all-‖ conformers exhibit limited solubility. Generally, however, CD spectra of -sheet structures confirm the negative ellipticity centered near 215nm and the positive band near 198 nm. While the theoretical calculations can predict many of the features observed in experimentally determined CD spectra, practical applications using circular dichroism spectropolarimetry to estimate the secondary structure content of proteins have relied more heavily on empirical data. In 1969, Greenfield and Fasman published circular dichroism measurements and spectra of poly-L-lysine under conditions where it existed as ―100% helix‖, ―100% ‖ and ―100% random coil‖ [46]. This now classic depiction of ―reference spectra‖ (reproduced in Figure 1, from the data in the original paper ) is now standard in all introductions to circular dichroism spectropolarimetry, though in more recent reviews (see, for example, Greenfield, 2007 [47]), often supplemented with standard spectra for collagen, -turns etc [48]. Linear combinations of these standard reference spectra are then used to ―deconvolute‖ the experimentally obtained spectra of proteins of unknown secondary structure compositions. Despite recent refinements, the use of such reference spectra to estimate secondary structure does not always give good agreement with data from higher resolution methods like X-ray diffraction or solution NMR.

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1e+5

Mean Residue Elipticity

8e+4 6e+4 4e+4 2e+4 0 -2e+4 -4e+4 -6e+4 190

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Wavelength (nm) Figure 1. Reference spectra for ―pure‖ alpha helix (), beta-sheet () and random coil (). (Replotted from data in Greenfield and Fasman [46]).

Mean Residue Elipticity

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-40000 190

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Wavelength (nm) Figure 2. Five protein reference spectra for deconvolution of proteins based on known structures in the protein data base. Myoglobin (), Lysozyme (), Lactate Dehydrogenase (), Papin ()and Ribonuclease (). (Replotted from data in Chen, Yang and Martinez [49]).

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As more and more protein structures have been deposited in the protein database, a variety of methods using the secondary structural content of proteins of known structure have been developed. One of the earliest of these [49], used the CD spectra for 5 such proteins to determine a reference optical activity of helices (X"-forms‖ (X), and ―unordered forms‖ (XR), and expressed the optical activity (X) of a protein as X = fHXH + fX + fRXR where the f‘s represent the fraction of the total protein in each particular form. (This set of ―reference spectra‖ is reproduced in Figure 2, also from data in the original paper [49].) The method gave results that were, in the authors‘ words, ―satisfactory to good‖ as did several other similar methods based on the then limited protein database (eg.[50;51]). Today, with the much more extensively populated protein database and the availability of computer algorithms and predictive approaches, a number of programs are available for calculating the secondary structural content of a protein from its CD spectrum. Many of the major programs (SELCON3[52;53], CONTIN and CONTINLL, [54],CDSSTR[55], LINCOMB[56], VARSLC[57], K2D[58], CCA) were developed in the 1990‘s. They use a variety of approaches and algorithms including linear regression, ridge regression, variable selection, self-consistent methods, neural networks, etc. All methods assume that the spectrum obtained experimentally for a protein (or proteins) with several structural elements can be reconstructed mathematically by a linear combination of the contribution of each structural element. Each of these approaches has inherent strengths and weaknesses (which have recently been reviewed [59;60]). Experience has shown that the best estimations of secondary structure from CD spectra are obtained by using several of these algorithms in combination [61]. Indeed, many web-based servers (eg, Dichroweb[62]) and deconvolution packages available with commercial circular dichroism instruments and software do just that. Estimations of secondary structure content obtained, while not in exact agreement with data from X-ray and NMR structures, are more than acceptable for most applications and differences in secondary structure content caused by mutations in a protein, exposure to different solvent conditions and/or binding of a ligand or prosthetic group are reliably detected.

3.4. Examination of Tertiary Structure by Circular Dichroism Circular dichroism also has application to studies of protein tertiary structure although such studies are much less common than those examining secondary structure, perhaps because the interpretation of these data are less straight forward. The side chains of tryptophan (Trp), tyrosine (Tyr), phenylalanine (Phe) and histidine (His) and the disulphide groups are all chromophores that give rise to CD signals. The side chain of Phe is a benzene ring and the side chain of Tyr, a phenol and akin to the well-studied chemical aromatic compounds. Four possible transitions (all  *) can be expected for Phe side chains: Lb at 260 nm, La at 210 nm and Bb and Ba both at 185 nm. While L transitions have considerably more intensity than B, neither is particularly strong, particularly compared to the far UV CD signal arising from the repeated peptide bond chromophore[63]. Phenolic side chains of tyrosine have similar transitions, but the stronger CD signal results from the Lb transition at 275nm, the La at 230 and both B transitions at 190 nm. Trp has an indole ring as a side chain and that chromophore gives rise to six separate transitions [64], of which the Lb and La

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transition signals seen between 270 and 280 nm are the most important. It has been shown experimentally that the La transition is quite sensitive to the local environment of the side chain, an attribute that makes this signal a particularly good probe of tertiary structure and induced changes in tertiary structure[65]. Similarly, theoretical and empirical studies have also determined the expected contributions for His side chains and the disulphide chromophore (see Woody and Dunker[66] for a comprehensive review). CD signals from the disulphides and the side chains of Phe, Tyr and Trp are dominant in the near UV (250 to 300 nm), but it takes relatively high concentrations of protein (about 10 fold higher than that typically used to probe secondary structure content) and cells of longer pathlengths (typically 1 to 2 cm) to obtain useful spectra. All of these chromophores also make contributions to the far UV although, as noted above, the signals resulting from side chains are usually less pronounced than those from the peptide backbone (particularly at the lower protein concentrations used for estimating conformations of the latter) and are usually ignored in calculations of secondary structure content. In some cases, however, amino acid side chain contributions can interfere with secondary structure estimations [64;67]and it is prudent to consider this possibility in the interpretation of the data. While the side chain chromophores of proteins have been shown to be sensitive to environment, interpretation of individual near UV spectra of proteins can be challenging. The intensity of the signals is low, in part because there are relatively few optically active side chains per protein molecule and in part because increased side chain mobility lessens the signal. Interactions between adjacent chromophores will also result in energy transfers and exciton splitting, which serve to further dilute the signal[66;68]. A number of successful studies have been conducted that use near UV spectra to garner information as to changes in tertiary structure during protein folding and/or unfolding, in response to changes in solvent conditions, or resulting from site-directed mutagenesis. These studies are too numerous to recount here but references to seminal ones can be found in recent reviews [66;69;70].

3.5. The Use of Circular Dichroism to Monitor Changes in Protein Structure CD is a useful and exceptionally sensitive tool for the detection of changes in protein structure, whether these changes result from variations in a protein‘s primary structure (following mutagenesis or chemical modification) or changes in its environment (from a change of solvent or pH, the addition of a stabilizing/destabilizing agent or an interaction with another molecule). CD has long been used to follow protein unfolding on the addition of increasing amounts of denaturants, or as the ambient temperature of the protein solution is increased. Similarly, CD has been used to determine the effect of osmolytes, ligands or cofactors on protein stability. As evidenced by recent summaries of pertinent CD echniques and literature [71-74], data from such experiments have been most useful in estimating the stability of a protein, the enthalpy and entropy of the unfolding reaction and the binding constant in protein-protein or protein-ligand interactions. More recently, CD has been found to be an effective tool for following the helix-to-sheet transition associated with amyloid formation[32;75;76]. The basic strategy for such explorations is simple: incremental changes are made in some factor of interest (eg. pH, temperature, ligand concentration, binding partners such as nanoparticles etc.) and the dependence of the protein ellipticity at a particular wavelength is

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followed. In a slightly more complex variation on this approach, the resistance of the protein to unfolding under each condition is followed by CD. Theoretically, any change in spectral features can be tracked and ellipticity measurements can be taken in either the far UV or the near UV. In practice, such studies more often follow the loss or gain of secondary structure (particularly of -helical structure) than changes in tertiary structure, perhaps because of the stronger signal associated with the former. Nevertheless, important information about subtle changes in tertiary structure without concomitant changes in secondary structure have been gleaned, either by following changes in the near UV spectrum or by monitoring protein structural stability in response to changes in protein environment or sequence[77-79]. As noted above, when ligand binding results in a change in protein conformation, the binding event should be evidenced by a change in the protein CD spectrum. Conversely, the resultant spectrum of two or more non-interacting entities is expected to be the sum of the spectra of each of the individual contributing chromophores. Consequently, CD provides an excellent tool with which to probe for potential interactions of proteins with nanoparticles and to ascertain whether such interactions, when they do exist, result in changes in protein structure that may warrant concern and/or further investigation.

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4. APPLICATIONS OF CIRCULAR DICHROISM TO PROTEIN/NANOPARTICLE INTERACTION STUDIES A number of studies have been published in which proteins have been intentionally associated with nanoparticles, either as an encapsulated therapeutic payload or coupled to the surface as a targeting ligand or vaccine antigen. The adsorption of protein(s) from the environment onto nanoparticles has also been investigated to some extent. As mentioned previously, many biophysical techniques have been utilized to characterize nanoparticle associated proteins; we provide here specific examples of one of the most useful: circular dichroism spectropolarimetry.

4.1. Characterization of Encapsulated Protein Encapsulation of bio-macromolecules, such as proteins, in NDSS is more challenging than encapsulation of small molecules due to the necessity of maintaining not only the correct chemical formula of the protein, but also its correct structure in order to ensure efficacy and safety. While many studies have been conducted where therapeutic proteins have been encapsulated in nanoparticles, very few studies have actually characterized the structure of these proteins when encapsulated [80]. The studies described here are representative of the subset that utilized CD in the characterization of encapsulated proteins. In 2000, van Slooten and coworkers utilized far and near UV CD to characterize the structural conformation of human interferon-gamma (hIFN prior to association with, and post-dissociation from, dipalmitoyl phosphatidylcholine/ dipalmitoyl phosphatidylglycerol/ cholesterol lipid nanoparticles [81]. These formulations were developed as adjuvants for vaccination against cancer and a number of viral infections such as HIV. These researchers determined that both secondary and tertiary structure of hIFN was preserved post-

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dissociation with the lipid nanoparticles. The study also examined the protein when associated with the lipid nanoparticle and, while no CD measurements below 220nm (where data related to structural elements other than -helix would be observed) were made, these researchers concluded that no gross changes in secondary structure were occurring in this largely helical protein while encapsulated, [81]. Although no explanation was given for the inability to examine the spectra below 220nm it was most likely due to light scattering effects of the particles, a potential drawback with using UV CD in the study of non-helical proteins and nanoparticles, as noted in studies discussed below. A 2003 study by Tiyaboonchai et al. further demonstrated the utility of UV CD in assessing the structure of an encapsulated protein. These experiments were focused on developing a formulation of insulin encapsulated in polyethylenimine-dextran sulphate nanoparticles [82]. Data were collected to wavelengths as low as 190nm which allowed for the calculation of secondary structure using SELCON3, CONTINLL and CDSSTR algorithms (see section 4.3). It was determined that under certain encapsulation conditions (protein/polymer ratio < 2:1, increasing [ZnSO4] and polymer solutions pH