Vibrational Dynamics of Heme Proteins: a Study by Nuclear Resonance Vibrational Spectroscopy and Resonance Raman Spectroscopy

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1 . Vibrational Dynamics of Heme Proteins: a Study by Nuclear Resonance Vibrational Spectroscopy and Resonance Raman Spectroscopy A dissertation presented by Weiqiao Zeng to The Department of Physics In partial fulfillment of the requirements for the degree of Doctor of Philosophy in the field of Physics Northeastern University Boston, Massachusetts August,

2 . Vibrational Dynamics of Heme Proteins: a Study by Nuclear Resonance Vibrational Spectroscopy and Resonance Raman Spectroscopy by Weiqiao Zeng ABSTRACT OF DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Physics in the Graduate School of Arts and Sciences of Northeastern University, August,

3 ABSTRACT In this thesis, vibrational dynamics of heme proteins are studied with nuclear resonance vibrational spectroscopy (NRVS) and resonance Raman (RR) spectroscopy, with assistance from vibrational predictions and analysis by density functional theory (DFT) computations. The first chapter is a brief introduction to heme proteins, focusing on myoglobin and to the role of vibrational spectroscopy in the study of heme proteins. It will address the advantages and importance of vibrational spectroscopies as a key to understanding protein dynamics, structures and functions. Chapter 2 describes the vibrational spectroscopic methods used in the thesis projects. Both the emerging synchrotron-radiation-based NRVS and the traditional resonance Raman spectroscopy will be explained. Application of these vibrational spectroscopies to study the dynamics of heme proteins are the main purpose of Chapter 3, 4, and 5 in this thesis. Cryogenic instrumentations, general methods of protein sample preparation and methods of vibrational predictions and analysis by DFT computations are also addressed. In Chapter 3, Compound II is an essential intermediate for heme proteins in activation of oxygen. Previous EXAFS measurements have shown that the Fe O distance in heme compound II is about 1.7 Å, suggesting that the iron oxo is double bonded and unprotonated (i.e., Fe(IV)=O). However, recent X-ray diffraction of crystals of heme protein compound II show that the iron-oxo bonds are long enough ( 1.9 Å) to be single bonds thus the iron-oxo groups are protonated (i.e., Fe(IV) OH). Motivated by the this controversial results on compound II, we visit the subject by studying the vibrational nature of monooxygenated myoglobin derivatives that have a single oxygen atom bound to the heme iron from the distal coordination: Mb compound II (ferryl Mb, also Mb(IV)=O), hydroxymetmb (Mb(III) OH) and aquometmb (Mb(III) OH 2 ). DFT computation tells us that if Mb(IV)=O is protonated, its vibrational characteristics resemble those of Mb(III) OH. We found that the vibrational characteristics of Mb(IV)=O do not feature any of 3

4 the three protonation signatures that Mb(III) OH characterizes: (i) 250 cm 1 down shift of the Fe O stretching frequency when protonated; (ii) 30 cm 1 split of the in-plane Fe-N pyr /Fe O tilt modes and (iii) 13 cm 1 H/D isotope shift of the Fe O strech mode. Thus the oxo in Mb(IV)=O is not protonated. The long Fe O bond in structural models derived from X-ray diffraction experiments might be due to the photoreduction of the heme iron by the high flux x-ray beam. In Chapter 4, we study ferrous nitrosyl myoglobin (MbNO) and address a long time issue of the vibrational mode assignment of the Fe NO stretching and Fe N O bending motions in the protein. Vibrations involving the FeNO fragment appear at 450cm 1 and 560cm 1. Vibrational assignments of these two modes have been controversial for the past 30 years. The nonlinear Fe N O geometry leads to significant mixing of Fe NO stretching and Fe N O bending contributions to these modes. The FeNO vibration near 450 cm 1 is easily identified in both NRVS and Raman data. NRVS measurements on oriented single crystals of [Fe(TPP)(1-MeIm)(NO)] reveal that the Fe motion is primarily perpendicular to the plane of the porphyrin, as expected for stretching of the Fe NO bond. Quantitative comparison of isotopic frequency shifts with NRVS data suggests that motion of the nitrosyl N atom accounts for 80% of the mode energy for the mode near 560 cm 1. The Fe amplitude, and consequently the NRVS signal, is thus relatively low for this mode. We conclude that it is mainly an Fe N O bending motion. In Chapter 5, nitrosyl Cu B -myoglobins (Cu B MbNO) are studied. Cu B Mb is a mutant of myoglobin in which a non-heme metal-binding site is designed into the distal heme pocket to simulate the active site of heme copper oxidase (for example, cytochrome c oxidase, the terminal enzyme of the mitochondrial respiratory chain). The metals in this site can change the binding properties of ligands to the heme iron and also affect the heme conformation. Previous UV-Vis absorption and EPR studies have found that for Cu B MbNO, a Cu(I) in this site weakly perturbs the heme, while Zn(II) actually breaks the Fe-His93 bond, leaving a 5-coordinate (5c) Fe-NO heme structure. NRVS and cryogenic Raman spectra confirm the 5c nature for Zn(II)-Cu B MbNO and 6c nature for Cu(I)-Cu B MbNO. NRVS data of Zn(II)-Cu B MbNO are very similar to that of 4

5 Fe(PPIX-DME)(NO), a 5c heme model. Cryogenic Raman spectra show that Zn(II)-Cu B MbNO resembles the H93G mutant MbNO, where the Fe-His93 link is absent. Further Raman photolysis measurements show that when the NO is photolyzed, the Fe-His stretch mode recovers and appears at 226 cm 1. With the help of DFT vibrational analysis, we propose that NO binds to the iron from the proximal side, like what happens to cyt c. Implications for heme copper oxidase and nitric oxide reductase will be discussed. A brief summary, as well as future opportunity and challenge in NRVS will be presented in Chapter 6. 5

6 Acknowledgement First and foremost I offer my sincerest gratitude to my advisor, Professor J. Timothy Sage, who has instructed me from preparation of my first buffer to this concluding stage of my research. I appreciate his great patience and prolonged support. His serious attitude and independent thinking towards SCIENTIFIC research are what I should follow life long. I am very grateful to Professor Paul Champion for serving as member a in my thesis committee. His profound knowledge, broad interest, and acute insight on biophysics have always been the source of inspiration for me. His questions, critics and suggestions have helped me made advances in my research. I want to thank Prof. Jeffrey Sokoloff for the knowledge of solid state physics he conveyed to me in class and valuable advice he provided as a member in my thesis committee. I am indebted to former members of the lab, Dr. Georgi Georgiev, Dr. Bogdan Leu, Dr. Alexander Barabanschikov, Yunbin Zhang, Ashenafi Dadi and Yang Zhang for their help and cooperation on research and for the friendship they ve shared with me. I appreciate Alexander s great effort on DFT computations and his generosity in allowing me to include them in this thesis. I would also like to thank Mr. Ben Cooper for his help in designing the Beryllium dome and cryostat for use in NRVS experiments. I would like thank friends from Professor Champion s lab, Dr. Wenxiang Cao, Dr. Xiong Ye, Dr. Zhenyu Zhang, Dr. Anchi Yu, Dr. Abdelkrim Benabbas, Dr. Karunakaran Venugopal and Yuhan Sun for their help and useful discussion on biophysics subjects. If it were not Wenxiang and Xiong Ye s guidance in sample preparation at the beginning, I would not have gained enough confidence to continue my way on experimental biophysics. I am grateful to Dr. Fei Wang for his help in changing dialysis buffers or shut down laser cooling water for many times. I want to show my appreciation for Dr. Micah McCauley for taking care of our valuable NRVS samples unexpectedly returned by express delivery services several times when everyone in our lab were out at Argonne. 6

7 I want to say Thank You to the BIG biophysics group for their useful suggestions in the seminar. I would like to thank scientists at sector 3 of Advanced Photon Source, Dr. Ercan Alp, Dr. Jiyong Zhao, Dr. Wolfgang Sturhahn. Without their cooperation, support and help, NRVS experiments would not be possible. I also appreciate help from Dr. Yumin Xiao. I would like to thank Professor W. Robert Scheidt and his group, Dr. Nathan Silvernail, Dr. Chuanjiang Hu, Dr. Jianfeng Li and Jeffrey Pavlik for the fruitful cooperation on NRVS. Bob s serious attitude as a scientist has deep impression on my mind. It is always a great honor to run NRVS together with him. Whenever I feel hungry, I can still think of the taste of the snack he brought from South Bend. Many thanks go in particular to Professor Yi Lu and his students, Dr. Natasha Yeung and Dr. Ningyan Wang for providing valuable mutant proteins for the projects. Last, but not least, I wish to thank my family for unlimited love and support they have for me throughout these many years. 7

8 Contents Abstract 2 Acknowledgement 6 List of Figures 11 List of Tables 15 Abbreviations, Acronyms and Notations 18 1 Introduction Heme Proteins: Structure and Function Protein Dynamics and Vibrational Spectroscopy Experimental Methods General Introduction Nuclear Resonance Vibrational Spectroscopy (NRVS) Introduction to the principle of NRVS Overview of NRVS Experiment Source Characteristics And Detection in NRVS NRVS Data collection NRVS Data analysis

9 2.3 Resonance Raman Spectroscopy Cryogenic Instrumentations Cryogenic Raman Setup Cryostat for NRVS General Sample Preparation Reconstitution of Myoglobin Sample Preparation for Raman Measurements Sample preparation for NRVS measurements Computational Methods Relationship between Raman Isotope Shift and KED Vibrational Dynamics of Monooxygenated Myoglobins Introduction Compound II: an Intermediate in Oxygen Activation Controversial Pictures of Compound II Vibrational Investigation of Myoglobin Compound II Methods RESULTS NRVS Results Computational Results Raman Results Discussion Vibrational Features in Myoglobin Compound II Protonation Status of Mb(IV)=O Photoreduction Issue of Mb(IV)=O Summary Supplemental Data

10 3.6.1 Spin density map obtained in DFT computation Fe VDOS comparisons between new and old DFT models of myoglobin: Mb(IV)=O and Mb(IV) OH Vibrational Dynamics of Nitrosyl Myoglobin (MbNO) Introduction Methods Results and Discussions Summary Supplementary Data Details in Raman Isotope Shifts Details in NRVS Data Fitting Extra figures related to MbNO project Photolysis Raman measurement on MbCO, MbNO (100 K and 293 K) Depolarization Raman Measurements on The Fe-NO Vibrations Vibrational Dynamics of Cu B MbNO Introduction Methods Results NRVS Results Raman Results Computational Results Discussion Influence of second metal on heme-o 2 complexes Influence of second metal on six-coordinate heme-no complexes Rupture of the Fe-Im bond Proximal NO binding

11 5.4.5 Consequences for HCO, NOR enzymatic mechanisms Summary Supplementary Data A room-in view of the Raman spectra of oxymyoglobins in Fig Two separate NRVS runs of horse MbO Summary and Future Opportunity 157 Appendix A: Reconstitution of horse myoglobin 159 References

12 List of Figures 1.1 Structure of Fe-protoporphyrin (Fe-PPIX), and the active site of myoglobin Structural view of water bound sperm whale myoglobin Importance of protein dynamics Excitation of the 57 Fe Experimental arrangement for measurements of the 57 Fe nuclear resonance at the Advanced Photon Source (APS) The excitation probability Cryogenic Raman setup Cryostat for NRVS measurement Temperature dependence in NRVS Monooxygenated heme species relevant to activation of molecular oxygen by heme proteins (Reaction cycle) Controversial pictures for myoglobin compound II The absorption spectrum of the NRVS sample of Mb(IV)=O Absorption spectrum of the NRVS sample of MbOH Picture of crystal myoglobin compound II Optimized structures of the Mb(IV)=O and Mb(IV) OH models by DFT The Fe VDOS and stiffness determined from NRVS measurements on Mb(IV)=O, Mb(III) OH and Mb(III) OH

13 3.8 Predicted Fe VDOS for models of Mb(IV)=O, Mb(IV) OH, Mb(III) OH, and Mb(III) OH 2 active sites Coordinate system (xyz) in DFT vibrational analysis Predicted Fe-ligand vibrations of the Mb(IV)=O model Resonance Raman spectra of Mb(IV)=O isotopically labeled with Fe, O and H atoms A detailed analysis of Fe O tilting and Fe O stretching frequency regions of Mb(IV)=O, showing both NRVS and Raman results. (Prediction of NRVS from Raman isotope shifts.) Resonance Raman spectra of Mb(III) OH isotopically labeled with Fe, O and H atoms A detailed analysis of Fe O tilting and Fe O stretching frequency regions of Mb(III) OH, showing both NRVS and Raman results.(prediction of NRVS from Raman isotope shifts.) Resonance Raman spectra of Mb(III) OH 2 isotopically labeled with Fe, O and H atoms A detailed analysis of cm 1 region of Mb(III) OH 2, showing both NRVS and Raman results. (Prediction of NRVS from Raman isotope shifts.) Photoreduction of myoglobin compound II Predicted electronic spin density surface Comparison of the Fe VDOS between the two DFT models: Mb(IV)=O and Mb(IV)=O with -NH 3 H-bonded to one of the propionate (1) Comparison of the Fe VDOS between the two DFT models: Mb(IV) OH (1) and Mb(IV) OH with one of the propionates protonated Optimized structures of the full heme MbNO model used in DFT computation and portion of the crystal structure of MbNO Comparison of NRVS and resonance Raman data on MbNO

14 4.3 Fe VDOS determined from NRVS measurements on a powder and on a crystal (Out-of-plane) of Fe(TPP)(1-MeIm)(NO) Mode pictures of Fe-NO vibrations at 429 cm 1 (Fe NO stretching) and 560 cm 1 (Fe N O bending) Fits to Raman spectra of reconstituted MbNO Raman spectra of MbNO labeled with 15 NO and 14 NO Fitting to the Fe VDOS determined from NRVS measurements on MbNO Fitting to the Fe VDOS determined from NRVS measurements on Fe(TPP)(1- MeIm)(NO) DeoxyMb, 293 K and 100 K photolysis, MbCO, 293k photolysis, MbCO, 100k photolysis, MbNO, 293k photolysis, MbNO, 100k Depolarization Raman measurements on ferrous MbNO, 293k The Fe a3 Cu B site of bovine heart cytochrome c oxidase Optimized DFT models for six-coordinate Cu(I)-Cu B MbNO (A), six-coordinate (B) and five-coordinate (C) Zn(II)-Cu B MbNO The Fe VDOS and stiffness determined from NRVS measurements on Zn(II)- Cu B MbNO, Fe(PPIXDME)(NO), Cu(I)-Cu B MbNO and horse MbNO The Fe VDOS and stiffness determined from NRVS measurements on Ag(I)-Cu B MbO 2 and horse MbO High frequency Raman spectra of Zn(II)-Cu B MbNO, Cu(I)-Cu B MbNO and horse MbNO taken at 100 K Low frequency Raman spectra of Zn(II)-Cu B MbNO, Cu(I)-Cu B MbNO and horse MbNO taken at 100 K

15 5.7 High frequency Raman spectra of Zn(II)-Cu B MbNO, Cu(I)-Cu B MbNO, horse MbNO and deoxymb taken at 100 K in photolysis experiment Low frequency Raman spectra of Zn(II)-Cu B MbNO, Cu(I)-Cu B MbNO, horse MbNO and deoxymb taken at 100 K in photolysis experiment High frequency Raman spectra of Ag(I)-Cu B MbO 2, horse MbO 2 with 54 Fe taken at 100 K Low frequency Raman spectra of Ag(I)-Cu B MbO 2, horse MbO 2 ( 57 Fe) and horse MbO 2 ( 54 Fe) taken at 100 K Electron spin density map for DFT models of six-coordinate Cu(I)-Cu B MbNO, six-coordinate and five-coordinate Zn(II)-Cu B MbNO Schematic description of the NO binding mechanism in ferrous Zn(II)-Cu B Mb Schematic description of the proximal binding of NO in ferrous Zn(II)-Cu B Mb A room-in view of Fig Comparison of two NRVS experiments results on horse MbO

16 List of Tables 3.1 Survey of Fe ligand bond lengths reported for monooxygenated heme proteins Stiffness of Fe in monooxygenated myoglobin compounds determine by Fe VDOS measured by NRVS Structural parameter, stiffness and O H stretching frequency predicted for Mb(IV)=O, Mb(IV) OH, Mb(III) OH and Mb(III) OH 2 models KED for the iron atom (e 2 Fe ) in the Fe O stretching/tilting regions Measured and predicted vibrational kinetic energy distribution (e 2 ) on the FeNO fragment in MbNO for selected Fe-ligand vibrations Selected geometry parameters of the full heme MbNO model optimized in DFT computation, together with those obtained through X-ray absorption fine structure (XAFS) spectroscopy and X-ray diffraction (XRD) on ferrous (Fe(II)) MbNO Fit parameters describing the Fe VDOS for MbNO Fit parameters describing the Fe VDOS for Fe(TPP)(1-MeIm)(NO) Conditions of the NRVS samples Measured Fe-NO vibrational frequencies, corresponding KED on Fe (e 2 Fe ) and stiffnesses for nitrosyl myoglobin proteins or models by NRVS Measured Fe-O 2 vibrational frequencies (corresponding e 2 Fe ) Measured Raman frequencies at 100 K for nitrosyl and oxymyoglobins

17 5.5 Predicted structure, total energy and imidazole dissociation energy for nitrosyl models Predicted spin, vibrational frequency and stiffness for nitrosyl models Measured Fe-O 2 vibrational frequencies ( ν), corresponding kinetic energy distribution on Fe (e 2 Fe ) and stiffnesses (k s) for oxygen bound horse myoglobin and Ag(I) Cu B MbO

18 Abbreviations, Acronyms and Notations 1-MeIm methyl imidazole 4c-, 5c-, 6c four-, five-, six-coordinate CAT catalase CcO cytochrome c oxidase CCP cytochrome c peroxidase CPO chloroperoxidase Cu B Mb mutant sperm whale myoglobin (L29H, F43H) cyt c cytochrome c deoxymb Fe(II)-myoglobin ligated by only histidine as axial ligand DFT density functional theory e 2 jα mode composition factor of atom j in modeα also: i.e., KED on atom j in modeα Fe VDOS Fe vibrational density of states EPR electron paramagnetic resonance Fe(II) ferrous iron ion (charge+2e) Fe(III) ferric iron ion (charge+3e) Fe(IV) ferryl iron ion (charge+4e) Fe(PPIX) iron protoporphyrin IX (heme b) Fe(PPIXDME) Fe protoporphyrin IX dimethyl ester FWHM full width at half maximum Hb hemoglobin HCO heme copper oxidase hh Mb horse heart myoglobin His histidine 18

19 HS high spin Im imidazole IR Infrared k s stiffness KED kinetic energy distribution LS low spin Mb myoglobin MbCO carboxyl myoglobin Mb(IV)=O myoglobin compound II; Mb II; ferryl myoglobin Mb(III) OH MbOH Mb(III) OH metMb MbNO ferrous nitrosyl myoglobin MbO oxymyoglobin MbOH hydroxymetmyoglobin metmb metmyoglobin; aquometmyoglobin NOR nitric oxide reductase NRVS Nuclear Resonance Vibrational Spectroscopy N pyr pyrrole nitrogen(s) OEP ,3,7,8,12,13,17,18-octaethylporphyrin dianion PHOENIX PHOnon Excitation by Nuclear Inelastic scattering of X-rays also: (computer program used for NRVS data analysis) sgc soluble guanylate cyclase sw Mb sperm whale myoglobin TPP ,10,15,20-tetraphenylporphyrin dianion δ(fe-no) orδ Fe NO Fe-N-O bending ν(fe-no) orν Fe NO Fe-NO stretching ν(fe-his) orν Fe His Fe-Histidine stretching 19

20 Chapter 1 Introduction This chapter is a brief introduction to heme proteins, focusing on myoglobin and to the role of vibrational spectroscopy in the study of heme proteins. We will address the advantages and importance of vibrational spectroscopies as a key to understanding protein dynamics, structure and function. 1.1 Heme Proteins: Structure and Function Life phenomena rely on the macromolecules: nucleic acids (RNA and DNA), proteins, carbohydrates and lipids (2). Proteins play important role in many life processes at molecular level. Prosthetic groups are required for proteins to exert their functions. Metalloproteins are large variety of proteins that contain metal ions in there prosthetic group (3). The metal ion plays central roles in the protein activity. Heme proteins are metalloproteins that contain iron porphyrins (i.e., the heme) as their prosthetic group (3). Heme proteins perform a variety of physiological functions, which are critical to fundamental life process, for example, electron transfer (cytochrome c), oxygen transport and storage (hemoglobin, myoglobin) and catalyzing many biochemical reactions such as oxygen activation (peroxidase, cytochrome P450, catalase, cytochrome c oxidase, etc.). 20

21 There exist different types hemes in nature, distinguished by different side chains attached to the porphine, the common part of all porphyrins. The chemical structure of a typical heme is shown in Fig. 1.1(A). It is named as b-type heme (heme b) or iron protoporphyrin IX (Fe(PPIX)), found in many heme proteins such as hemoglobin (Hb), myoglobin (Mb), horseradish peroxidase (HRP), chloroperoxidase (CPO), nitrophorins, soluble guanylate cyclase (sgc) and in most catalases. The formula for Fe(PPIX) is C 34 H 32 FeN 4 O 4 and its molecular weight is 616 (4). HN (His64) pyrrole nitrogen (N pyr ) distal site N CH CH 2 CH 3 H 3 C N N Fe 2+ CH CH 2 Fe 2+ H 3 C N N CH 3 N CH 2 HOOCCH 2 CH 2 CH 2 COOH (His93) N H proximal site (A) Fe(PPIX) (B) Mb active site Figure 1.1: Schematic structure of the Fe-protoporphyrin (Fe-PPIX) (A), and the active site of myoglobin (B). For Fe(PPIX), typical distance between the Fe atom and its nearest neighbors (N pyr, the pyrrole nitrogen atoms, total number= 4) is around 2.0 Å. The distal and proximal sites of the heme may allow certain small molecules to stay in or bind to the heme iron. This figure is drawn with ChemWindow (Bio-Rad Inc., Hercules, CA). The heme iron is the most important part of a heme protein. It is the center for all heme protein activities. Iron is a transition metal and capable of coordinating to six ligands in an octahedral geometry (5). In the heme structure, the iron sits in the center of the molecule and coordinates with the four pyrrole nitrogen atoms (N pyr ) in the porphyrin. These four pyrrole nitrogen atoms locate almost symmetrically around the iron atom in a plane and are the nearest neighbors of the iron when there exists no other ligand. The average distance between the iron 21

22 and these four nitrogen atoms is approximately 2.0 Å. In heme proteins, a fifth ligand to the iron, is from the amino acid residue of the protein. This iron-ligand bond is usually formed between the iron (Fe) and a nitrogen atom (N) belonging to a histidine residue (for example, in Mb, Hb, HRP, cytochrome c oxidase), or a sulfur atom (S) belonging to a cystine residue (for example, in CPO, cytochrome P450, nitric oxide synthase), or an oxygen atom (O) belonging to a tyrosine residue (for example, in catalases). This fifth ligand to the iron, is usually called the proximal ligand and corresponding Fe-ligand bond is nearly perpendicular to the heme plane which can be defined as the mean plane of the four N pyr atoms. For many heme proteins, such as those with heme b, this is the only covalent bond that connects the heme and the protein. Opposite to this bond, the iron can accept a sixth ligand such as external molecules or another amino acid residue of the protein. This ligand is called the distal ligand of the heme iron. Small molecules, such as H 2 O, O 2, NO, CO, H 2 O 2, NO 2 etc., can be the distal ligands in heme proteins. These ligands do not come in to stay forever. In some cases, they can bind to the iron reversibly (6), for example, the binding of H 2 O, O 2, NO or CO to myoglobin. In other cases, they will be reduced and moved away from the distal binding site, like O 2 in cytochrome c oxidase (7) or H 2 O 2 in most heme proteins (8)(9)(10) (reduced to water) and NO in nitric oxide reductase (reduced to nitrous oxide) (11). None of these binding properties are trivial. They are part of the ways that how heme proteins play there roles physiologically. The iron is the center for heme protein functions, but it needs help from the protein environment to play the role. In heme protein, the heme group is usually buried in a structure formed by the peptide chain of the protein but with channels for substrates to come in to and go away from the iron. The heme, together with the amino acid residues and possibly some metals nearby, forms the so-called active site of the protein. Proteins conduct important biochemical functions (catalytic reaction, electron transfer, diatomic molecule storage and transportation, etc.) mainly through their active sites. A bare heme might possess some of those heme protein abilities, but away from an active site environment surrounded by the protein, the efficiency of those activities are usually lower or totally lost. 22

23 Figure 1.2: Structural view of water bound sperm whale myoglobin obtained in X-ray diffraction. The heme (iron protoporphyrin IX, i.e., Fe(PPIX)), amino acid residuals of histidine 64 and 93 are highlighted as sticks. The heme iron and the oxygen of the iron-bound water are shown as spheres. All other parts of the protein are shown in ribbon style. The PDB entry for this structure is 1A6K. This figure is made with PyMol (12). 23

24 The heme proteins studied in this work are mainly myoglobin and its mutants. Fig. 1.2 depicts the structure of water bound sperm whale myoglobin obtained in X-ray diffraction (13). Myoglobin belongs to the category of globular proteins. The heme, His64 and His93 are components of the active site of the protein (see also in Fig. 1.1(B)). Since its structure was discovered in the 1950 s (14), myoglobin has become an ideal and popular model in many fields of protein research (15). The structure function relationship for myoglobin has been a classic model for protein studies (2). The wild type myoglobin contains 153 amino acid residues (13) with a total molecular weight of about 17,000 (16). Even through its main role in physiology is to store oxygen in muscles, myoglobin can bind to or react with the small molecules mention above. Its relatively simple structure makes it the gateway for understanding corresponding functions of more complicated proteins such as cytochrome c oxidase, horseradish peroxidase, etc. However, for proteins as simple as myoglobin, we are still far from fully understanding on their physiological functions. This makes myoglobin a long-lasting interest for biochemists and biophysicists. 1.2 Protein Dynamics and Vibrational Spectroscopy From a biophysical view point, the most important aim of protein research is to discover the mechanism for protein functions at molecular or atomic scale. The equilibrium structure of a protein, especially of its active sites, establishes the foundation of its function. A specific structure usually is good for some specific function. In turn, to play some specific role, a protein must possess a special structure (2). This structure function relationship is very useful in investigating the protein structure and understanding its function. Undoubtedly, structure determination methods for macromolecules such as X-ray diffraction (XRD), NMR spectroscopy have contribute the most to the knowledge of protein structure. With the advances of synchrotron radiation and NMR techniques, more and more structures of proteins are being solved rapidly. Mechanisms of protein function are being proposed based on biochemical studies combined with 24

25 + these structures. X-ray absorption methods such as X-ray absorption fine structure (XAFS) and X-ray Absorption Near Edge Structure (XANES) are also very useful in obtaining knowledge about protein structure, but usually limited to the metal-ligand geometries. These are direct methods to see the protein structure : 6 ; 7 4 <= ; 5 8 >? 4 <= ; < A! "! # $ % 1 2 & ' & ( & ) * össbauer, ), * -. / & 0 $ % Figure 1.3: The diagram shows the relationship among protein dynamics, structure and function. The dynamics plays a central role in revealing the protein structure and understanding its function. vibrational spectroscopy provides an efficient way to uncover the protein dynamics. Thus, it is an important approach to understand protein structure and function. Based on the foundation established by the equilibrium structure, protein dynamics plays the key role in understanding the mechanism of its function. Protein structure is constructed by atoms with bonds connecting to each other in space. According to quantum mechanics, atoms vibrate perpetually. Any structural change in the protein will result in different molecular vibrational dynamics and is observable in vibrational spectrum. For example, the structural changes will alter bond length, bond strength, bond angle, which must correspond to different vibrational dynamics that can be observed through vibrational spectroscopies. Thus, appropriate vibrational spectroscopies can provide insight into the protein structure through its dynamics. The vibrational spectra of heme proteins and their derivatives reveal ample structural and dynamical information 25

26 (vibrational frequency, amplitude, direction and depolarization ratio etc.) on the active sites, which helps to understand their physiological functions. Fig. 1.3 shows the relationship among protein structure, function, dynamics and vibrational spectroscopy methods. It tries to demonstrate the importance of vibrational dynamics of protein and to understand the role of vibrational spectroscopies in the exploration of protein structure and function. As we will see in this thesis, vibrational dynamics plays an important role in understanding protein structure and function while vibrational spectroscopy provides an advantageous approach to obtain knowledge of vibrational dynamics. Traditional vibrational spectroscopies like Raman, IR have been used in protein study successfully. The spectral marker bands for the coordination and spin status of the heme iron have been well established. The newly available vibrational spectroscopy of Mössbauer nucleus, nuclear resonance vibrational sepctroscopy (NRVS), has played a unique role in obtaining iron dynamics in hemeproteins, contributing new insight and knowledge to protein dynamics. In this thesis, the vibrational characteristics of mono-oxygenated myoglobins (Mb compound II, hydroxymetmb and aquometmb) (chapter 3), nitrosyl myoglobin (MbNO) (chapter 4) and Cu B MbNO (chapter 5) are investigated with nuclear resonance vibrational spectroscopy (NRVS), resonance Raman (RR) spectroscopy, and theoretically with vibrational predictions and analysis based on density functional theory (DFT) computations. 26

27 Chapter 2 Experimental Methods 2.1 General Introduction Conventional molecular vibrational spectroscopies include infrared (IR) absorption and Raman scattering. IR absorption results from changes in the dipole moment of a vibrating molecule. The Raman scattering process relies on changes in molecular polarizability. The Raman signal is usually very weak due to the small scattering cross section. Resonance Raman excites molecule at a frequency coincident with an electronic transition of the molecule. This resonant excitation enhances the Raman signal greatly. For macromolecules like heme proteins containing visible chromophores, resonance Raman is an extremely important vibrational technique. In heme proteins, when excited by a laser line resonant with a heme electronic transition, the Raman signal will mainly consist of vibrations of the heme and Fe ligands. Thus resonance Raman becomes highly selective vibrational method for studying vibrational dynamics of heme protein and other macromolecules. Nuclear resonance vibrational spectroscopy (NRVS) is a newly developed vibrational technique which utilizes synchrotron radiation generated at brilliant 3rd generation synchrotron radiation facilities like the Advanced Photon Source at Argonne National Lab. NRVS is closely 27

28 related to Mössbauer spectroscopy, in which certain isotopes are constrained in solids to allow recoilless resonant absorption of incident gamma rays by the nucleus. Thus, the hyperfine structure of the probe nuclei can be observed. The probe nuclei vibrate along the molecular potential surface with vibrational energies on the order of tens of mev. The nucleus can resonantly absorb photons with excess energy ( E) relative to the transition energy (E 0 ) of the probe nuclei, if E happens to create one vibrational quantum. If the energy is scanned over a reasonably large range, for example, mev around E 0, a phonon spectrum of the probe nuclei can be obtained. NRVS is the technique that fulfills this task. 57 Fe is one of the most studied Mössbauer nuclei. Its nuclear transition energy is kev. The vibrations of the iron atom in the heme yield valuable insights into the structure and physiological function of the protein. Once the proteins are reconstituted and enriched with 57 Fe, the iron vibrations can be studied with NRVS. Compared to resonance Raman spectroscopy, NRVS is much more selective. Here we take heme proteins as examples. NRVS observes all but only the vibrations in which the iron participates and with significant amplitude of motion. Resonance Raman usually fails to see all the iron modes due to selection rules. NRVS can also provide quantitative properties of the iron motions including frequencies, amplitudes of vibrations and directions of vibration in oriented crystalline samples. Both resonance Raman and NRVS have their own merits and we will make use of both in the projects described in this thesis. 2.2 Nuclear Resonance Vibrational Spectroscopy (NRVS) Introduction to the principle of NRVS Mössbauer experiments rely on constraining the probe nucleus in a solid in order to enable the recoilless absorption of incidentγ-rays (18). However, this does not stop the probe nucleus from undergoing vibrational motions. Soon after the Mössbauer effect was discovered, it was 1 This section is based on (17). 28

29 suggested that it can be extended to measure the vibrational spectrum of the Mössbauer nucleus in the solids by tuning the photon energy to excite vibrational energy levels in addition to the nuclear excitation (19)(20). This suggestion is the genesis of nuclear resonance vibrational spectroscopy (NRVS). Typical vibrational quanta lie in the order of tens of mev (1 mev 8 cm 1 ), however, corresponding to inconveniently large Doppler velocities on the order of hundreds of meters per second. As a result, practical experimental realization of this idea required the development of appropriate technology at brilliant third generation synchrotron radiation facilities, where X-rays can be generated and tuned over the range needed to excite vibrational quanta. This was first accomplished slightly more than a decade ago (21)(22)(23). NRVS has become the most common terminology for applications of this method to inorganic and bioinorganic systems (24)(25). However, the same technique is described in the literature using alternate names, including nuclear resonant inelastic X-ray scattering (NRIXS) (26), nuclear inelastic scattering (NIS) (27), and the phonon-assisted Mössbauer effect (28). In traditional vibrational methods such as Raman or infrared (IR) spectroscopy, only vibrational modes allowed by selection rules appear in the spectra. To help assign the modes, isotope difference spectra are used. But due to selection rules, some modes do not appear in the spectrum. Spectral congestion also raises difficulty in resolving modes with close frequencies, particularly for macromolecules containing thousands of atoms. NRVS is both more selective and more comprehensive than Raman or IR. NRVS reveals all vibrations of the probe nucleus, ignoring motions of all other atoms. 57 Fe, with a nuclear resonance energy E 0 = kev, is a Mössbauer isotope with favorable properties for currently available synchrotron light sources. Moreover, iron plays important roles in many proteins, including heme proteins and iron-sulfur proteins (29). Synchrotron-based nuclear resonance methods have revealed the vibrational dynamics of the iron atom in numerous systems, including alloys, amorphous materials, nanomaterials, and materials under high pressure (26)(30)(31)(32). The above-mentioned selectivity for the probe 29

30 nucleus is particularly valuable for biological macromolecules, which may contain many thousands of atoms, but a localized active site is often the true center of interest. Since its availability (21)(22)(23), NRVS has been applied to study the vibrational dynamics of Fe in proteins (24)(28)(33)(34)(35)(36), porphyrin model compounds (25)(37)(38)(39)(40)(41)(42)(43) and iron-sulfur clusters (44)(45)(46). It is shown that NRVS can provide frequencies, amplitudes, and directions for Fe vibrations in the samples. It helps to clarify mode assignments in vibrational spectra and reveals many important vibrational modes of Fe which cannot be seen by other methods. In particular, NRVS reveals low frequency motions of the Fe down to below 100 cm 1 that control biological reactions. The applications presented here use 57 Fe as the probe nucleus, but the principle applies to other Mössbauer isotopes such as 119 Sn, 83 Kr, 61 Ni and 67 Zn if appropriate sources are available Overview of NRVS Experiment NRVS is related to Mössbauer spectroscopy, but cannot easily be realized using conventional Mössbauer equipment. Practical NRVS experiments target the sample containing the probe nucleus ( 57 Fe, for example) with X-rays generated by a synchrotron radiation facility. The incident photon energy varies around the nuclear resonance energy E 0 = kev with a typical resolution of about 1 mev 8 cm 1 sufficient to provide vibrational resolution. It can be tuned to more than 100 mev from E 0 to explore sidebands that result from excitation of vibrational quanta coincident with the nuclear excited state. The energy range must be large enough to include all vibrations with significant Fe amplitude, with a resolution sufficient to resolve individual vibrational modes. The energy bandwidth is much larger than the hyperfine splittings detected in conventional Mössbauer measurements, and all of the nuclear sublevels are excited in these synchrotron-based experiments. Fig. 2.1 depicts a typical sequence of events started by absorption of an incident photon with an energy near the nuclear excited state energy E 0. The 57 Fe nucleus has an excited state lifetime 30

31 of 141 ns, and excited nuclei have two decay channels. About 10% of them re-emit a 14.4 kev photon. For recoilless absorption, where no vibrational levels are excited, time-resolved measurements of 14.4 kev photons scattered in the forward direction reveal information on hyperfine interactions comparable to conventional Mössbauer spectroscopy. The remaining nuclei expel electrons from the atomic K shell, followed by 6.4 kev atomic fluorescence when an electron drops from a higher level to fill this hole. These delayed signals at 6.4 and 14.4 kev indicate nuclear resonance absorption of the X-ray and constitute the NRVS signal. The relative contribution of 6.4 and 14.4 kev photons will depend on sample thickness and on detection efficiency Source Characteristics And Detection in NRVS Because of the extremely narrow energy window selected, practical NRVS measurements require the highest X-ray brilliance currently available at third-generation light sources. At present, there are 3 major facilities for nuclear resonance experiments, beam lines 3-ID and 16-ID at the Advanced Photon Source (APS) at Argonne National Lab, in the USA (47), beam lines ID18 and ID22N at the European Synchrotron Radiation Facility (ESRF) in France (48) and beam lines BL35XU (49) and BL09XU (50) at SPring8 in Japan. These are public beam lines and users can submit research proposals to apply for beam time for experiments. Fig. 2.2 illustrates the experimental set up at the APS. Separated electron bunches circulate at a speed very close to the speed of light in the storage ring, which is 1100 meters in circumference. X-rays are generated over a broad bandwidth when the electrons pass through the undulator. Diffraction from perfect single crystals selects a narrow range of energies that meet the Bragg diffraction condition. Following the heat-load monochromator, the X-ray bandwidth is narrowed to approximately 1 ev and centered on the nuclear resonance energy (14.4 kev for 57 Fe). The high resolution monochromator (51) further reduces the X-ray bandwidth to about 1 mev and motorized scanning of this monochromator tunes the energy over a range (typically 31

32 Figure 2.1: Excitation of the 57 Fe resonance at E 0 = kev. Absorption of a 14.4 kev photon by a hypothetical free nucleus (top) in an initial state i would leave it in a final state f =exp ( ) i k r Fe i, in order to conserve momentum. The primary decay channel for the nuclear excited state is to expel one electron from the atomic K shell, which is followed by 6.4 kev fluorescence when an electron drops from a higher energy level to fill the resulting vacancy. Emitted 6.4 kev photons, together with 14.4 kev photons emitted from the nuclear excited state, are delayed with respect to the excitation by a time on the order of the 141 ns nuclear excited state lifetime, and constitute the detected nuclear resonance signal. In a realistic experimental situation (bottom), the nucleus is bound to neighboring atoms, final states are quantized, and a series of vibrational sidebands appear, corresponding to transitions to a final vibrational state f with energy hc ν coincident with the nuclear excitation. Each transition appears at an energy E 0 +hc ν with a relative area f exp ( ) 2 i k r Fe i. Unlike conventional Mössbauer measurements, synchrotron-based measurements do not directly resolve hyperfine splittings of the recoilless resonance ( f = i ) at E=E 0. 32

33 within 100 mev of the resonance) adequate to explore excitation or annihilation of vibrational quanta. The X-ray flux at the sample is about 10 9 photons/s ( 10µW), which is very low compared to typical mw beam powers in laser-based Raman experiments. Additional X-ray optics may reduce the beam size. The cross section of the beam at the sample point is currently about mm 2 at station D of beam line 3ID at APS. Detection of nuclear resonance signals exploits the time structure of the electron bunches circulating in the storage ring. The standard fill pattern at the APS, with bunches separated by 153 ns, is favorable for 57 Fe measurements. Ideally, each bunch is about 100 ps in length. When the resulting X-ray pulse hits the sample, it interacts with the 57 Fe nuclei, as well as with electrons. Strong prompt signals as high as 6 MHz result from electronic scattering coincident with the X-ray pulse. This signal is not related to the nuclear resonance at all, and the counting electronics are gated off during a time interval surrounding the arrival time of the X-ray pulse (see inset in Fig. 2.2). The X-ray photon can be absorbed by the 57 Fe nucleus only when its energy matches the nuclear resonance transition energy (with or without excitation or annihilation of vibrational quanta). Photons emitted as a result of nuclear excitation arrive with a delay on the order of the lifetime of the nuclear excited state (141 ns for 57 Fe). The maximum delayed count rate near E 0 is typically on the order of 100 Hz for protein samples and 1000 Hz for model compounds with appropriate concentrations described in the next section. The vibrational signal is substantially weaker. The avalanche photodiode detector (APD) has nanosecond time resolution and is controlled by timing circuits so that only delayed signals are counted to give a NRVS spectrum. Under favorable operating conditions, electronic noise is the main source of background. The APD is designed to work at room temperature, and care must be taken to avoid unwanted noise generated by cold air from a nearby cryostat. Electronic timing errors or beam fill errors may also contribute to background noise by causing electronically scattered photons to register as delayed counts. An acceptable noise level of 0.03 Hz or less can usually be achieved with an X-ray flux of 10 9 photons/s. 33

34 Figure 2.2: Experimental arrangement for measurements of the 57 Fe nuclear resonance at the Advanced Photon Source (APS). In the standard fill pattern, electron bunches with a duration of 100 ps are separated by 153 ns. X- ray pulses are generated when alternating magnetic fields in the undulator accelerate these electron bunches. The spectral bandwidth of the X-rays can be narrowed down to 1 ev by the heat-load monochromator and to 1 mev by the high resolution monochromator. At the sample, the flux of the beam is about 10 9 photons/s. APD indicates the avalanche photodiode used to detect emitted X-rays. The lower right inset illustrates that counting is enabled only for times well-separated from the X-ray pulse, so that only delayed photon emission resulting from decay of the nuclear excited state contributes to the experimental signal. 34

35 2.2.4 NRVS Data collection As with all beam line experiments, advance planning is essential. The availability of beam time is not entirely predictable, may be awarded with relatively short notice, and cannot be rescheduled because of the large number of users affected. Facilities for preparing or modifying samples will be very limited or nonexistent. Moreover, the round-the-clock attention required for successful NRVS data collection, particularly on samples with low count rates, provides little opportunity for sample modification. If a previous user has performed measurements using the same nuclear resonance, data collection may commence near the start of the assigned beam time. Otherwise, time must be invested in adjusting the undulator, aligning the monochromator, finding the resonance, optimizing energy resolution and throughput, and establishing appropriate voltage thresholds and timing for detection of delayed counts. These are specialized operations that are usually performed by trained beam line personnel, who may also handle certain local arrangements such as the availability of cryogens. Users take primary responsibility for all other aspects of data collection and analysis, although further guidance from beam line personnel may be required if problems arise. Because experimental problems occur, data are nearly always recorded as multiple energy scans, which are subsequently summed. The energy sampling interval is usually chosen to be smaller than the energy resolution (typical values are 0.25 mev and 1 mev, respectively), so that scans containing unphysical features narrower than the experimental resolution can be excluded. Other reasons for excluding individual scans include high background count rate and interruptions in the X-ray beam. Excluded scans may indicate a problem that will compromise further data collection, and such problems should be identified and addressed before continuing. The actual beam energy typically deviates slightly from the value selected by the nominal monochromator position, because the lattice constants of the crystals respond to temperature variations. Small energy corrections are automatically determined at each monochromator setting 35

36 from temperature sensors in thermal contact with the crystals. Data summation software must account for the resulting small scan-to-scan variations in energy values. Crystal temperatures should be continually monitored for changes larger than this level, and the start of new scans is usually delayed to allow reestablishment of equilibrium following any event that substantially alters crystal temperature, such as an interruption in the X-ray beam. Ideally, the monochromator is housed in a separate enclosure upstream from the experimental station containing sample and detector, in order to keep temperature variations below 10 mk over the course of an energy scan. Energies should be reproducible from scan to scan, with the exception of the small variations just described. However, it is customary to obtain data on a standard sample to verify the accuracy of the overall energy scale. This may be a sample whose vibrational frequencies have been well established in the scientific literature, or a sample measured at a previous data collection run. An alternative procedure involves measuring a concentrated sample, such as an 57 Fe foil whose temperature can be accurately measured, and adjusting the energy scale to ensure that S (E)/S ( E)=exp (E/k B T). Such overall energy scale corrections may be on the order of 1%. Data analysis usually involves subtraction of the recoilless absorption line at E=E 0, which has the shape of the monochromator energy resolution function, because the fundamental linewidth is orders of magnitude smaller than the experimental resolution. Delayed 14.4 kev photons scattered in the forward direction from a 57 Fe foil carry no vibrational signal and provide a straightforward experimental determination of the resolution function. Appropriate experimental design may allow this measurement in parallel with the NRVS measurement, using the X-ray beam transmitted through the sample (Fig. 2.5). However, if the monochromator is stable, it may be sufficient to average 2 3 scans of the delayed forward scattering measured over a limited energy range (typically±10 mev) at occasional intervals during the data collection period. Continuous monitoring of experimental performance is essential in order to minimize the number of scans that ultimately need to be excluded because of experimental problems, and thus to ensure optimal use of limited beam time. Individual scans should be compared periodically to 36

37 monitor sample stability, although experience to date has revealed no evidence for radiation damage resulting from exposure of cryogenic samples to the low X-ray flux density in NRVS measurements. Sample temperature must also be monitored because averaging of scans at different temperatures may interfere with accurate data analysis. Monochromator throughput should be recorded at the beginning of each scan, along with user-determined experimental parameters such as energy sampling interval and dwell time. Efficient use of measurement time requires maintaining the incident X-ray flux, and may necessitate occasional adjustments to monochromator alignment to maximize throughput, with guidance from beam line personnel if needed. Depending on monochromator design and on which crystal is adjusted, this may require redetermination of the experimental resolution function. It is especially important to systematically monitor the level of background noise from the detector, because apparently unobtrusive increases in background noise may degrade the experimental signal-to-noise ratio as badly as decreases in X-ray flux. A straightforward noise check is to monitor the detector signal after setting the energy 200 mev below the recoilless resonance energy E 0, where delayed counts cannot be attributed to genuine nuclear resonance signal. Under favorable operating conditions at the APS, the count rate may be counts/s. Action must be taken if the background count rate rises significantly above this level, particularly for low count rate samples such as protein solutions. The most common reasons for elevated background levels are electronic detector noise and timing problems. Sources of electronic noise, particularly machinery such as vacuum pumps, must be placed outside the experimental station and the detector must be protected from possible temperature variations resulting from proximity to cryogenically cooled samples. Users can exercise limited control over noise levels by setting the voltage threshold of a discriminator to exclude low amplitude voltage pulses while registering larger pulses due to genuine photon detection events. Beam fill errors can create stray electrons that are temporally separated from the main bunch, leading to detection of electronically scattered photons within the time interval where delayed 37

38 emission from the nuclear excitation is expected. This signal will vary weakly across the narrow energy window of a NRVS scan, and thus contribute a uniform background. In many cases, adjustments to the width and delay time of the gate signal can eliminate this contribution to background. Software available at the beam line allows individual energy scans to be selected and added, and the summed scans should be periodically examined during data collection in order to identify any unanticipated experimental problems. The software calculates each experimental energy from the monochromator position, with correction for temperature variations of the monochromator crystals if needed. A fit in the region of the intense recoilless absorption line determines zero energy precisely. Measured counts are then binned according to the calculated energies and added. Variations of the incident X-ray flux during each energy scan are usually small, but are ordinarily measured and used to normalize the measured counts energy-by-energy in individual scans before summing. An optional input scale factor allows rescaling of the energy axis, if needed to agree with energy calibration measurements. The data in Fig. 2.6 are a sum of 3 4 scans, followed by an overall normalization described in the following section NRVS Data analysis The measured NRVS signal is proportional to the number of resonant 57 Fe nuclei in the effective sample volume and to an excitation probability (19) S ( ν)= p i f e i k r 2 Fe i L( ν ν i f ), (2.1) i f measured as a function of the energy separation hc ν=e E 0 from the resonance energy E 0. Here, i and f represent the initial and final states of the nuclear center of mass. In thermal equilibrium, the occupation probabilities p i = exp ( E i /k B T)/ i exp ( E i /k B T) weight the relative contribution of each initial state to the sum in Eqn. (2.1), while the matrix element f e i k r Fe i determines the contribution of the final states. 38

39 In the hypothetical scenario of absorption by a free nucleus (Fig. 2.1, top), initial and final states both correspond to free translation of the nucleus and the only allowed final state f =e i k r Fe i corresponds to the absorbing nucleus recoiling with the momentum k of the incident photon. In this hypothetical situation, the excitation probability would consist of a single feature at an energy E 0 + hc ν R exceeding the nominal resonance energy E 0 by the amount of the nuclear recoil energy hc ν R = 2 k 2 /2m Fe. (2.2) This feature would have unit area, since the line shapes and the initial state probabilities are both normalized, L( ν)d ν=1and i p i = 1. However, this freely recoiling state is not a stationary state of the Hamiltonian in relevant experimental situations, where the 57 Fe nucleus is bound to other atoms in a condensed phase. In general, a series of discrete lines appear in the spectrum (Fig. 2.1, bottom), corresponding to a range of possible final states. Conventional Mössbauer spectroscopy relies on the presence of a narrow line ( f= i) at E 0, with an area proportional to the recoilless fraction f= i p i i e i k r 2 Fe i, (2.3) to perform extremely high resolution measurements of hyperfine interactions. In contrast, NRVS measurements exploit the appearance of a number of sidebands at energies separated from the resonance energy E 0 by the energy difference hc ν i f = E f E i between initial and final energy levels. Each sideband has an area φ= i f p i f e i k r 2 Fe i (2.4) that can be considered a recoil fraction. (Here, the sum over f is restricted to final states with a constant energy separation with respect to the initial state.) 39

40 The total spectral area is normalized, S ( ν)d ν=1, independent of the nuclear environment, since L( ν)d ν=1, and a simple closure argument ensures that f e i k r Fe i 2 = 1. As a result, f f+ φ=1, and situations that reduce the Mössbauer signal correspondingly strengthen the integrated NRVS signal. Lipkin (52) has shown that the first moment νs ( ν)d ν= ν R (2.5) of the excitation probability yields the recoil energy. Since the recoil energy (Eqn. (2.2)) has a precisely determined value ( ν R = 15.8 cm 1 for 57 Fe), Eqn. (2.5) provides a practical recipe for normalizing the experimental data to obtain a signal proportional to the excitation probability. NRVS data are commonly interpreted within an harmonic approximation (25)(53), which describes molecular vibrations in terms of independent oscillations along a set of normal coordinates Q a = j e jα r j m 1/2 j related through a linear transformation to the Cartesian coordinates r j of atoms j weighted by their masses m j. Molecular rotation and translation lead to six modes having zero frequency. Projection of the transformation coefficients e jα onto the direction ˆk of the X-ray wave vector k=(e 0 / c) ˆk determines the recoil fraction φ α = ν R ν α f ( n α + 1) (ˆk e jα ) 2, (2.6) which is the fractional contribution of a feature appearing at frequency ν α to the area of the excitation probability S j ( ν) of atom j resulting from a single excitation of vibrational modeα. These fundamental transitions (n α n α + 1) dominate the observed data at high frequencies and low temperatures, but weak vibrational overtones and combinations can be resolved under favorable conditions (54). Spectral features corresponding to deexcitation of modeαappear at frequency ν α, with an area given by an expression identical to Eqn. (2.6) but with the factor n α + 1 replaced by n α.(this statement is actually implicit in Eqn. (2.6) because n α ( ν)/ ν=( n α ( ν)+1)/( ν).) The latter features become significant at temperatures high 40

41 enough (or frequencies low enough) that the mean occupation number n α = [ exp (hc ν α /k B T) 1 ] 1 of modeαbecomes significant (e.g., Fig. 2.6). The spectral area provides quantitative information on the amplitude and direction of motion of the probe nucleus through the final factor (ˆk e jα ) 2 in Eqn. (2.6). This information can be determined for each mode using Eqn. (2.6). Alternatively, further analysis of the data (55) can yield an estimated vibrational density of states (VDOS) Dˆk ( ν)= ) (ˆk e jα 2L( ν να ) (2.7) α for the probe atom. Dˆk ( ν) is normalized such that Dˆk ( ν) d ν=1and represents the contribution of motion of the probe atom along ˆk to the total vibrational density of states D ( ν)= αl( ν ν α ), with D ( ν) d ν=3n. Practical measurements involve averaging over a large ensemble of molecules. For randomly ) 2 oriented molecules, as in a solution or a polycrystalline powder, (ˆk e jα = 1 3 e2 jα, the recoil fraction becomes φ α = 1 3 ν R ν α f ( n α + 1) e 2 jα, (2.8) and the partial VDOS D ( ν)= e 2 jαl( ν ν α ) (2.9) α represents the contributions from probe motion in all three directions. (Note that D ( ν) d ν=3.) However, the directional information implicit in Eqs. 2.6 and 2.7 is partially or completely retained in measurements on oriented single crystals (e.g., Fig. 2.6), where the crystal structure restricts molecular averaging to a discrete set of orientations. Fig. 2.3 presents an example of the excitation probability S ( ν) and the VDOS D ( ν) for the iron atom in the molecule Fe(TPP)(1-MeIm)(CO), as determined from measurements on a polycrystalline sample. Sharp features in both representations of the experimental data clearly identify vibrational frequencies above 100 cm 1, although low frequency vibrational features are 41

42 more apparent in the VDOS representation. The VDOS also provides the most convenient estimate of the mode composition factor e 2 jα, since the area of each feature directly yields the sum of e 2 jα values for all contributing vibrations. This avoids the need to remove the additional factors in Eqn. (2.8) that contribute to the area of a feature in S ( ν), with the subtleties associated with determining an appropriate value for the recoilless fraction f (25)(54). However, calculation of D ( ν) from S ( ν) involves implicit assumptions that may not be valid in some situations, for example, when more than one molecular species contributes to the experimental signal or when vibrational anisotropy is significant S(ν) (cm) Fe(TPP)(1-MeIm)(CO) T=20K (a) D(ν) (cm) 0.02 (b) frequency (cm -1 ) Figure 2.3: The excitation probability S ( ν) (a) and corresponding Fe vibrational density of states D ( ν) (b) of polycrystalline Fe(TPP)(1- MeIm)(CO). S ( ν) results from normalization of summed experimental scans according to Eqn. (2.5), and D ( ν) results from Fourier-log deconvolution as implemented by the program PHOENIX(56). The program PHOENIX (56) implements the calculation of D ( ν) from S ( ν), using the Fourier-log deconvolution method (57). This program reads two input data files containing the summed sample data and the experimental resolution function, and two input parameters, 42

43 background and temperature, must be specified. The background is typically estimated from the counts in the high or low energy limit of the sample data, where no genuine vibrational signal is expected. The initial temperature can be estimated from a temperature reading or from the relative size of features at negative frequency, but is usually iterated to obtain a consistent analysis. Most protein solutions and polycrystalline porphyrin samples are measured in a helium-flow cryostat at K, while the single crystals are typically measured in a cold gas stream near 100 K. After subtraction of the background, the data are normalized to satisfy Eqn. (2.5), thus providing the excitation probability S ( ν). Subtraction of the resolution function reveals the vibrational contribution S ( ν) to the excitation probability. PHOENIX adjusts the subtraction weight to achieve the best match to the one-phonon contribution to the vibrational signal near E 0 expected for a Debye frequency distribution ( D ( ν) ν 2). The Fourier-log algorithm (22)(57) then yields the dominant first-order vibrational contribution S 1 ( ν)= 1 3 ν R ν α ( n α + 1) D ( ν) (2.10) to the excitation probability, from which the VDOS D ( ν) is readily calculated. Output results include a quantitative indication of how consistent the input temperature value is with the detailed balance condition S ( ν)/s ( ν)=exp (hc ν/kt). The recoilless fraction f and other vibrational properties that can be calculated directly from moments of S ( ν) according to sum rules given by Lipkin (52) are compared with values calculated from D ( ν) as further consistency checks. Small adjustments in the values input for temperature and background are typically needed to achieve self-consistent results. In our experience, the resulting estimate of the sample temperature may be 10 K or more higher than the reading of a nearby sensor because of temperature gradients. Output spectral files include first-, second-, and higher-order contributions S 1 ( ν), S 2 ( ν), and n>2 S n ( ν), to the excitation probability as well as the total vibrational contribution S ( ν)= n 1 S n ( ν) and the VDOS D ( ν). 43

44 As noted above, the area of a peak in the VDOS provides a straightforward measure of the mode composition factor e 2 jα according to Eqn. (2.9) (possibly summed over a number of unresolved modes). However, there are non-trivial approximations implicit in the calculation. In addition to the Debye approximation used to subtract the recoilless contribution, the Fourier-log algorithm assumes a unique environment for the probe atom and neglects vibrational anisotropy. The resulting errors are often smaller than the experimental uncertainty, particularly for protein samples. However, there may be situations where these assumptions are questionable, for example, if the probe nucleus occupies more than one distinct site. If there is reason to believe that this is not adequate, careful analysis of the recoil fraction according to Eqn. (2.8) provides an independent estimate of e 2 jα. Stiffness: The stiffness (36, 58, 59) k s = m Fe ω 2 =m Fe (2πc) D( ν) ν 2 d ν (2.11) determined from the VDOS measures the average strength of nearest neighbor bonds to the iron. It turns out that the stiffness is sensitive to the measurement of background and resolution function, which are inputs in the PHOENIX program to generate VDOS. An appropriate background can be determined by averaging the high energy end of the NRVS data where appears no iron vibrations. The resolution function should also be measured at the same X-ray beam configuration as the NRVS data collection on protein samples. 2.3 Resonance Raman Spectroscopy In resonance Raman spectroscopy, the heme protein samples are excited by appropriately chosen laser line close to resonance with an excited electronic energy level of the heme. The Raman scattering signal is greatly enhanced in this way, and also selectively originates from vibrations in the active site of the protein (instead of the whole protein and solvent), the heme and 44

45 its axial ligands. Through out this thesis, we used nm laser line from krypton (Innova 302, Coherent.) laser as excitation. Raman spectra are obtained by utilizing commercial Raman spectrometer (LabRam HR800, JY Horiba) in the lab. It is a confocal Raman microscope and Raman signals are collected in a back-scattering configuration. Solution samples can be measured at room temperature in spinning NMR tubes or at cryogenic temperatures either as free standing films in a cold gas stream or in a He-cooled cryostat. Under cryogenic condition, spectral peaks are better resolved and some samples are much more stable. Resonance Raman reveals vibrations of the porphyrin excellently, and iron-ligand vibrations are sometimes present. 2.4 Cryogenic Instrumentations Biological samples are often perishable under ambient temperature, especially for intermediates of proteins which might only exist for a few milliseconds. We often conduct our measurements under cryogenic conditions. Besides enhancement of sample stability, the advantage of working under cryogenic temperature is that the spectral linewidth is much narrower than at room temperature. As also mentioned in the section on NRVS, measuring NRVS at low temperature also helps to minimized multiphonon contributions to the NRVS spectrum, which is a key point in obtaining good quality Fe vibrational density of states in limited time Cryogenic Raman Setup The mostly used cryogenic Raman setup used in this thesis work is demonstrated in Fig 2.4. The setup has several advantages. (a) It does not need vacuum system; (b) samples can be loaded and unloaded easily, which is very important for intermediate protein samples; (c) only very small amount sample is used for one measurement; (d) It works for frozen solutions or crystals. The laser focal spot on the sample is 4µm in diameter for an objective with 50 45

46 magnification and 20µm for an objective with 10 magnification. A scanning mirror equipped in the confocal microscope can generate line focusing on the sample to reduce average laser intensity on the sample. This setup also provides convenience for studying the photochemistry of frozen samples. With the help of the confocal imaging system, one can focus the laser beam onto a specific sample spot and conduct photochemical measurements at different laser power levels and/or temperatures. The cryostream temperature is set to 100 K for the cryogenic Raman measurements in this thesis, if not specifically stated. Figure 2.4: Cryogenic Raman setup. Laser excitation is focussed by the objective of a confocal microscope and scattered photons are collected through the same objective. The cryogenic nitrogen stream is generated by a 700 series Cryostream (Oxford Cryostream). The sample is loaded on a nylon cryoloop mounted on a magnetic base Cryostat for NRVS Fig. 2.5 shows a typical design of a helium-cooled cryostat which balances the competing requirements for X-ray detection and temperature control. Samples are loaded in a

47 mm 3 channel milled in a polyethylene, which has good thermal contact with the cold head. The cryostat chamber is kept in a vacuum state of 10 5 mbar during experiments. The beryllium dome is transparent to X-rays. The APD detector is placed as close as possible to the sample to maximize the solid angle over which X-rays are collected. The dome features a large span so that the transmitted or forward scattering X-ray beam can pass through the sample and propagate away from the cryostat. If desired, a second APD can detect the forward scattering beam simultaneously and the result can be used for the resolution function which is essential to NRVS data analysis. transmitted beam sample sample cell APD X-ray emission incident X-ray beam beryllium window sapphire plate sample cell base (OFHC copper) cold head extension (OFHC copper) O-ring radiation shield 10 mm helium-cooled cold head Figure 2.5: Typical cryostat design for solution and powder samples. This design features an expanded beryllium dome, which allows detection of the transmitted beam as well as the emitted X-rays that contribute to the NRVS signal. The Be dome and a thin polyethylene window on the front face of the sample cell minimize the absorption at 6.4 and 14.4 kev. A sapphire plate provides excellent thermal contact between the sample cell and the cryostat cold head, as well as allowing optical access for off-line Raman measurements to monitor sample integrity. Sample temperatures in the K range are typically achieved for both solutions and powders. 47

48 2.5 General Sample Preparation In this section, we only address general sample issues. Individual sample preparation procedures will be shown in chapter 3, 4, and 5 when necessary Reconstitution of Myoglobin In NRVS measurement, we need to use 57 Fe labeled myoglobin instead of natural abundance ones to enhance NRVS signal and make optimal use of precious beamtime offered by the synchrotron radiation facility. One way to enrich 57 Fe in the sample is to replace the native heme (Fe(PPIX)) in the protein with 57 Fe(PPIX) by a procedure called reconstitution. To observe the Fe isotope difference in Raman, we need to compare 57 Fe and 54 Fe labeled proteins, thus we also need to replace the heme with 54 Fe(PPIX). The brief steps for reconstitution of horse heart myoglobin are described below. 54 Fe or 57 Fe labeled myoglobin was obtained through reconstitution of the native horse heart myoglobin following published procedures (60)(61)(62). Briefly, the hemes were first extracted by mixing 2-butanone with a solution of the protein at ph 1.0 and 4 o C and allowing the clear aqueous phase (containing the apoprotein) and the dark-colored organic phase (containing heme) to separate (60). Following sequential dialysis of the resulting apoprotein solution against 0.01 M NaHCO 3 and 0.01 M potassium phosphate, ph 7.0 (62), addition of 57 Fe(PPIX)(Cl) or 54 Fe(PPIX)(Cl) at ph at 4 o C led to reconstitution of the holoprotein. The reconstituted proteins were purified by separating the extra hemes on an ion exchange gel column (CM C-50) at ph 7.0 (62). A more detailed description is written in the Appendix A at the end of this thesis. 48

49 2.5.2 Sample Preparation for Raman Measurements For cryogenic resonance Raman measurements, we suspend a thin film of frozen solution on a cryoloop (see Fig 2.4). Samples that are stable in the air, for example, myoglobin compound II, hydroxymetmyoglobin and metmyoglobin, can simply be loaded onto cryoloops by dipping the loop into the solution and then frozen in the cryostream. For samples that are sensitive to oxygen, for example, nitrosyl myoglobin (MbNO), carbonyl myoglobin (MbCO) and Cu B MbNO, we load the solution onto the cryoloop, freeze it under anaerobic conditions and store it in liquid nitrogen. To load the cryoloop (containing frozen sample) for Raman measurements, we quickly mount the magnetic base of the cryoloop onto a magnet using precolded cryotongs so that the sample is in the cryostream (see Fig 2.4). When Raman measurements are conducted at room temperature, protein solutions are contained in NMR tubes (outer diameter: 5 mm; wall thickness: 0.38 mm). For each measurement, the volume of sample can be 70µL to 120µL. To reduce photo damage to the sample, pressurized air is used to spin the tube, which is magnetically suspended on a spinning setup (Precision Sample Spinner (5mm), Princeton Photonics, Inc.). For samples which are sensitive to oxygen, for example, nitrosyl myoglobin (MbNO) and carbonyl myoglobin (MbCO), argon gas is used to flush the tube to remove oxygen inside. The samples are prepared under anaerobic conditions and transferred to the degassed NMR tube with air-tight precision syringe. The tubes are well sealed during measurement Sample preparation for NRVS measurements Several factors have to be considered when preparing samples for NRVS measurements. First, the sample must be isotopically enriched with 57 Fe or other Mössbauer nucleus of interest. Small molecule samples such as porphyrins enriched with up to 95% 57 Fe are prepared according to the small scale metallation procedure of Landergen and Baltzer (63). Proteins are usually enriched with 57 Fe through reconstitution. For many heme proteins, the Fe protoporphyrin 49

50 [Fe(PPIX)] can be extracted using Teale s method (60) and then replaced with commercially available [ 57 Fe(PPIX)] (24)(35). Harsher procedures are required to extract and replace the Fe from the covalently bonded heme in cytochrome c (64). Proteins can also be expressed, for example in E. coli, with 57 Fe supplied in the culture medium. In favorable cases, reconstitution may provide an opportunity to selectively label one of multiple distinct Fe sites, a feature often exploited in Mössbauer spectroscopy. Another important factor is the sample concentration or, more specifically, the 57 Fe concentration, which must be high enough to yield reasonable signal strength mm solutions of protein enriched with 57 Fe at single site yield interpretable NRVS data at 8 cm 1 resolution within hours of beam time at the APS (35). The small size of molecules designed to mimic protein active sites allows significantly higher concentrations, often reducing measurement times to a few hours. For porphyrin samples, using a mm 3 sample holder, a sample of up to 26 mg can be used, corresponding to Fe nuclei. Sample purity is a key concern. The NRVS experiment is a bulk technique sampling all 57 Fe nuclei, and impurities that also contain the probe nucleus may confound quantitative data interpretation. Impurities may be introduced during sample preparation or result from sample instability during measurement. Because of this, care must be taken to ensure purity and reproducibility as judged by Mössbauer, single crystal X-ray diffraction, electronic absorption spectroscopy, Raman spectroscopy or other qualitative techniques. To make full use of the incident beam, the sample volume should be large enough to fill the beam. Single crystals should ideally exceed the area of the beam ( mm 2 ) to maximize signal. Single crystals are aligned using a four-circle diffractometer, which adds the additional degree of freedom (χ) needed for single crystal alignments. Careful observation of crystal morphology along with molecular packing acquired on natural abundance iron samples may allow an approximate alignment. In the ideal crystalline case, the porphyrins are all coplanar. It is beneficial to place the porphyrin plane, or plane normal to the porphyrin plane, about the goniometer arcs. Use of an eucentric goniometer head for all alignments allows for fine 50

51 orientation adjustment without significant recentering. Sample holders for powders and solutions consist of a high density polyethylene (HDPE) block with a mm 3 milled well. The sample is placed into the well, a small Teflon seal is placed on the block, and a sapphire window is placed over the seal. Brass screws attach the HDPE block to a round copper block to facilitate heat transfer to the cold finger of a helium flow cryostat. Some practice may be needed to avoid creation of bubbles created when the Teflon seal or sapphire wicks concentrated protein solutions out of the well. If possible, it may be helpful to freeze the solution in the cell before placing the sapphire window. Isolated polycrystalline samples are mulled with a minimal amount of Apiezon M vacuum grease on a microscope slide using a non-metallic instrument and placed in the sample holder. In the experiment, the high resolution monochromator tunes the incident X-ray energy through the recoilless nuclear transition energy E 0. The energy range must include all vibrational signal for accurate normalization. A typical range around E 0 is [ 30, 80] mev for heme proteins or porphyrins at T< 30 K, but larger ranges may be required at higher temperature or for certain samples to enable data normalization, at the cost of increased measurement time. The energy sampling interval should be less than the resolution of the monochromator. A step size of 0.25 mev is typical for 1 mev energy resolution, with an accumulation interval of 5 seconds/point, allowing completion of one full energy scan within one hour. Typically, multiple scans are averaged to improve signal-to-noise ratios, and to identify possible scan-to-scan variations resulting from instrumental artifacts or from sample instability. For porphyrin model compound samples, either in the form of crystal or powder, 3 to 4 scans may be enough to obtain acceptable data quality. Satisfactory results on concentrated protein samples may require more than 20 scans (about 1 day). Unless there is specific interest in temperature dependence, data interpretation is simplest at the lowest temperatures that are conveniently achievable. Crystal samples can be placed in a cold nitrogen gas stream and powder or solution samples can be mounted on a helium-cooled cryostat. Fig. 2.6 shows NRVS data recorded for an Fe(TPP)(1-MeIm)(NO) crystal at two different 51

52 temperatures with the heme plane lying nearly parallel to the X-ray beam. Differences between the two spectra are apparent both for the central line (Fig. 2.6 inset) and for the higher frequency signals. Thermal excitation of low frequency vibrations with increasing temperature leads to the appearance of unresolved shoulders on all bands, including the recoilless line (inset), reducing the effective experimental resolution. Substantial anti-stokes signals resulting from vibrational deexcitation also appear at energies below E o as the temperature increases, necessitating measurement over a larger frequency range to ensure spectral normalization. However, the relative intensities of these anti-stokes signals provide a useful measure of sample temperature. energy (mev) excitation probability ( 10-4 cm) (119K) Fe(TPP)(1-MeIm)(NO) oriented in plane 287K excitation probability (cm) 287K 119K frequency (cm -1 ) excitation probability ( 10-4 cm) (287K) 0 119K frequency (cm -1 ) Figure 2.6: NRVS data recorded on a single crystal of Fe(TPP)(1-MeIm)(NO), oriented with the X-ray beam 13.8 from the planes of all porphyrin molecules, at two different temperatures, 119 K (blue) and 287 K (red). The two curves in the main panel are normalized according to Lipkin s first moment sum rule (Eqn. (2.5)) and scaled up by 200 times. It is apparent that increasing temperature leads to effective line broadening and to signals at negative energy resulting from vibrational deexcitations. The inset shows an expanded view of the recoilless line, with shoulders due to low frequency acoustic lattice vibrations. 52

53 2.6 Computational Methods All DFT calculations on the model compounds were done with Gaussian 03 program (65) using the B3LYP functional (66)(67). The basis set was Ahlrich s VTZ (68) for the Fe atom and 6-31G* for all other atoms. All reported frequencies are unscaled. All reported energy values are sum of electronic and zero-point energies. The predicted VDOS for the iron atom can be compared directly with the experimental VDOS. The partial VDOS for atom j along direction ˆk (for oriented samples) is a sum over all vibrational modes ν α (25): ) Dˆk j ( ν)= (ˆk e jα 2L( ν να ) (2.12) α Here,L( ν ν α ) is a normalized line shape function with width chosen to facilitate comparison with the experimental VDOS. Since the mode composition factor e 2 jα is the fraction of kinetic vibrational energy of the molecule on atom j for mode ν α (25), we calculate the vector e jα = m j r j Q α = m j r j m j r 2 j (2.13) and its squared value e 2 jα= m j r 2 j m j r 2 j (2.14) from the masses m j and predicted vibrational displacements r j of atom j (40). The VDOS D j ( ν)= e 2 jαl( ν ν α ) (2.15) α is summed over the three directions for comparison with experimental data recorded on randomly oriented samples. Six modes corresponding to molecular rotation and translation appear at zero frequency in the calculation on an isolated molecule are omitted from the summations in Eqn. (2.12) and (2.15). Predicted stiffness (k s ) can be calculated by inserting D j ( ν) into 53

54 Eqn. (2.11). 2.7 Relationship between Raman Isotope Shift and KED The KED of the Fe atom e 2 Fe in vibrational modeαcan be calculated according to the formula (25) e 2 jα= 2 d(ln ν α) d(ln m j ) 2 ν a/ ν a m j /m j (2.16) where ν α is the frequency shift of modeαdue to the mass change ( m j ) of atom j. 54

55 Chapter 3 Vibrational Dynamics of Monooxygenated Myoglobins Vibrational dynamics on myoglobin compound II (Mb(IV)=O), together with hydroxymetmyolgobin (Mb(III) OH) and aquometmyoglobin (Mb(III) OH 2 ) are investigated with NRVS, resonance Raman and DFT computation in this chapter. We compare vibrational features among the three myoglobin compounds to clarify Fe-ligand structures in compound II, an intermediate in oxygen activation. 3.1 Introduction Compound II: an Intermediate in Oxygen Activation The abundance of gaseous oxygen in Earth s atmosphere attests to its relative stability, yet higher organisms base their existence on the efficient metabolism of molecular oxygen. Molecular oxygen (O 2 ) is paramagnetic, and biological oxygen activation typically involves interaction with metal sites whose spin-orbit coupling facilitates otherwise spin-forbidden reactions. Heme proteins are important enzymes that catalyze oxygen activation (69)(70)(71). The protein starts 55

56 O 2 +2H + +2e - H 2 O Fe(III) ferric 2H 2 O O Fe(IV) Compound I + e - 2H + + e - O Fe(IV) Compound II Figure 3.1: Monooxygenated heme species relevant to activation of molecular oxygen by heme proteins. The compound I and II intermediates in the cycle contain an iron-oxo group (Fe(IV)=O). The extra positive charge in compound I is usually described as a cation radical on the porphyrin. The protein environment may alter the proton affinity of the oxygen ligand. Green bars in the figure represent the porphyrin portion of the heme. from a resting ferric (Fe(III)) state, and reacts with O 2 or H 2 O 2 under proper conditions. The iron will be oxidized to Fe(IV), and an iron-oxo group (Fe(IV)=O) is formed, together with a radical left on the porphyrin. This product is called compound I. The radical is very reactive and it will extract and pair with one electron from its surroundings, reducing the system to a state called compound II. The protein will return to the resting ferric state by oxidizing the substrate, fulfilling one catalysis reaction cycle. Compound II is common to many enzymatic biological activation processes (72)(73)(74). They are key intermediates in the reactive cycles of numerous enzymes including heme-copper oxidases, peroxidases, catalases, and cytochromes P-450 (75)(76)(10). The reaction cycle in oxygen activation is illustrated in Fig

57 Table 3.1: Survey of Fe ligand bond lengths reported for monooxygenated heme proteins. a iron b b EXAFS distances (pm) crystallographic distances (pm) spin protein L ex L ax state Fe O c Fe-L ax ref. Fe O c Fe-L ax ref., PDB code 1 Mb His (81) (79),1GJN 1 HRP His k (82) (77),1H55 Fe(IV) 1 CCP O 2 His (83) (80),1ZBZ 1 CAT Tyr 166 d 227 (84) (78),1GWF 1 CPO Cys e (82) - - 1/2 OH (85) f - - Fe(III) 5/2 Mb OH His (85) g - - 5/2 H 2 O 211 h 212 h (86) (13),1A6K Fe(II) 0 Mb H 2 O His 213 i 199 (87) j (88) l, - a need to notice that for protonated models, the L ex for Fe(IV) (O 2 ) is replaced by OH. b L ex = exogenous ligand; L ax = protein ligand (S cys for CPO, O Tyr for CAT and N His for all others). c Oxygen atom in the L ex. d 166 pm is for high ph (8.3) CAT-II; At low ph, this value is 180 pm. see Table 3 in ref. (84). e 240 pm for ph 5.5; 237 pm for ph 6.7. f ph=11.3,100 K, see Table 1 in the ref. (85) g ph=11.3,293 K, see Table 1 in the ref. (85) h from EXAFS (115 K). For XANES (70 K), d Fe O = 222pm, d Fe Lax = 214pm from (87). i value for solution sample; 215 pm for crystal sample. j XANES. 70 K. k average of the Fe-N pry and Fe-N His distances. l 115 K Controversial Pictures of Compound II Controversy has arisen surrounding the nature of the high valent intermediate compound II. In contrast with the traditional description of compound II as an oxo adduct of ferryl iron, Fe(IV)=O (see Fig.3.6(a)), structural models derived from recent X-ray diffraction studies have long Fe-O bonds more consistent with a lower Fe-O bond order (77)(78)(79)(80). These structural data have motivated the suggestion that the oxo group is in fact protonated, so that compound II would best be described as Fe(IV) OH (see Fig.3.6(b)). Table.3.1 lists a survey of experimental results on the Fe O bond length from both EXAFS and X-ray diffraction. It includes Mb, HRP, CCP, CAT and CPO. EXAFS measurements support a long bond for compound II of chloroperoxidase (CPO) (82), in which a thiolate ligand derived from cysteine binds trans to the oxo iron as for cytochrome P-450 (82). The basicity of the ferryl 57

58 oxo group is proposed to facilitate the oxygen insertion reaction catalyzed by cytochrome P-450 (82). However, analysis of EXAFS results on proteins with a histidine imidazole group bound trans to the oxo iron find a short bond consistent with the traditional unprotonated Fe(IV)=O description of compound II (81)(83)(85)(86) (87)(84)(82), and inconsistent with the X-ray diffraction studies Vibrational Investigation of Myoglobin Compound II The two controversial viewpoints suggest different chemistry in the catalytic reaction cycle. The physics between these unprotonated and protonated iron-oxo groups are also different. For example, their vibrational characteristics should be easily distinguished using vibrational spectroscopy. Vibrational studies find Fe O frequencies slightly lower than in model compounds with double bonds, and frequency shifts in D 2 O are smaller than expected for a protonated oxo group (10). Moreover, there are slight variations in the reported values for the Fe O frequencies. Interpretation is complicated by the relatively weak Raman signal for the Fe O stretch and by the possibility that deuterium substitution can influence the frequency or scattering intensity by altering the strength of hydrogen bonds to the oxo group (from distal histidine). Figure 3.2: Controversial pictures for myoglobin compound II: unprotonated (left) and protonated (right). Although myoglobin is designed by nature mainly to store O 2 in physiology, ferryl species 58

59 (Fe(IV)) of myoglobin are formed during reperfusion of muscle tissue following ischemia, and their role in oxidative tissue damage is under active discussion (89)(90). Myoglobin can react with H 2 O 2 to form compound II state. Being a relatively simple protein, it can be a model for more complicated systems. In this thesis project, we apply both NRVS and resonance Raman, in comparison with DFT computation, to investigate the vibrational characteristics of horse heart myoglobin compound II, hydroxymetmyoglobin and aquometmyoglobin, the three myoglobin compounds that have a single oxygen bound to the heme iron (monooxygenated myoglobin compounds). And try to clarify a correct picture for the iron-oxo group status (unprotonated or protonated). 3.2 Methods General methods in experiment are described in Chapter 2, it is useful to write down here specific details for this project. Materials: Native horse heart myoglobin and hydrogen peroxide (30 wt %) were purchased from Sigma-Aldrich (St. Louis, MO). 57 Fe-protoporphyrin IX chloride [ 57 Fe(PPIX)(Cl)] and 54 Fe(PPIX)(Cl) were purchased from Frontier Scientific (Logan, UT). Deuterium peroxide (98 atom% D, 30% in D 2 O) and H 18 2 O 2 (90 atom% 18 O, 2% in H 2 O) were purchased from Icon Isotopes (Summit, NJ). Sample Preparation for NRVS: Mb(IV)=O: To prepare Mb(IV)=O, the 57 Fe-labeled protein (obtained through reconstitution) was concentrated to 17 mm in 0.1 M potassium phosphate buffer, ph 8.0. Hydrogen peroxide solution was diluted to 1.0 M in the same buffer, and mixed rapidly with the protein to produce Mb(IV)=O. This reaction used 40µL of protein solution and ten equivalents (91) of hydrogen peroxide. About 20µL of the mixed solution was loaded into a 59

60 sample cell designed for NRVS measurements and frozen within 60 seconds. Dilution of the remaining sample for visible absorption measurements with a spectrophotometer(u-3410, Hitachi) confirmed formation of compound II (see Fig 3.3). Mb(III) OH: To prepare Mb(III) OH, the 57 Fe labeled protein was concentrated to about 10 mm. It was then diluted by 10 times in 0.1 M, ph 10.0 glycine-naoh buffer, followed by reconcentration to about 10 mm. The procedure was then repeated, leading to a final protein concentration of 11 mm. Visible absorption (see Fig 3.4) indicated the formation of Mb(III) OH. About 20µL of the sample was loaded into NRVS sample cell and frozen absorption spectrum 57 Fe-Mb(IV)=O absorbance Wavelength (nm) Figure 3.3: Absorption spectrum of the NRVS sample of Mb(IV)=O, measured on dilution of the sample in 0.1M ph 8 potassium phosphate buffer. Mb(III) OH 2 The 57 Fe-labeled protein was concentrated to above 10 mm in 0.1 M potassium phosphate buffer, ph 8.0. All samples were stored and transported under cryogenic conditions and were mounted on a helium flow cryostat (see Fig. 2.5) for NRVS data collection. Sample Preparation for Raman: Mb(IV)=O: Myoglobin was prepared at about 2 mm in 0.1 M, ph 8.0 potassium phosphate buffer. (The myoglobin used to react with D 2 O 2 was in 0.1 M, ph 8.0 potassium phosphate buffer prepared with D 2 O.) The hydrogen peroxide was diluted to 1 M or less in 0.1M, ph8.0 potassium 60

61 2.0 absorption spectrum 57 Fe-Mb(III)-OH absorbance (b) (a) 10 (a) wavelength (nm) Figure 3.4: Absorption spectrum of the NRVS sample of MbOH. The solid curve was obtained on the original sample without dilution. The dotted curve was measured on dilution of the sample in 0.1M ph10 glycine-naoh buffer. phosphate buffer before use. The deuterium peroxide was diluted to 0.2 M in 0.1 M, ph 8.0 potassium phosphate buffer prepared in D 2 O before use. The H 18 2 O 2 (about 0.5 M) was used without dilution. Myoglobin compound II samples were obtained through the reaction of myoglobin solution with a 10-fold excess of peroxide (91). Mb(III) OH: Mb(III)-OH, Mb(III) OD and Mb(III) 18 OH samples were prepared by dissolving lyophilized myoglobin in 0.1M, ph glycine-naoh buffer prepared with H 2 O, D 2 O and H 18 2 O, respectively. Sample concentrations were between 1.8mM and 2.0mM. The 57 Fe and 54 Fe labeled Mb(III) OH solutions were first obtained in the same way as for the sample in NRVS measurement, and then diluted to about 2 mm. Mb(III) OH 2 : Mb(III) OH 2, Mb(III) OD 2 and Mb(III) 18 OH 2 samples were prepared by dissolving lyophilized myoglobin in 0.1M potassium phosphate buffer prepared with H 2 O, D 2 O and H 18 2 O, respectively. The 57 Fe and 54 Fe labeled Mb(III)-OH 2 were obtained through heme reconstitution. Sample concentrations were between 1.8mM and 2.0mM and buffers were at ph 8. Crystal sample: Crystal Mb(III) OH 2 was obtained in (NH 4 ) 2 SO 4 solution(3 M, ph 7.3). Crystal form of Mb(IV)=O was obtained by incubation of a piece of crystal Mb(III) OH 2 in the mother liquid solution containing 22 mm H 2 O 2 for 45 seconds, followed by flash freezing in

62 K N 2 stream on a cryoloop. The crystal sample was used mainly in photoreduction measurement. A picture of this crystal seen from the Raman microscope is shown in Fig Figure 3.5: The picture of the crystal myoglobin compound II seen from the Raman microscope frozen in the 100 K N 2 stream. NRVS Measurement: Nuclear resonance vibrational spectroscopy (NRVS) data were collected at sector 3-ID-D of the Advanced Photon Source at Argonne National Laboratory, as described in Chapter 2 (see also (17) and (92)). Briefly, extremely relativistic electron bunches passed through an undulator inserted in the storage ring and generated broad band X-ray pulses. A high heat-load monochromator reduced the X-ray bandwidth to about 1 ev, centered at the kev nuclear resonance energy of the Mössbauer isotope 57 Fe, and was followed by a high resolution monochromator(93) that further reduced the bandwidth to 1.2 mev ( 10 cm 1 ). The X-ray beam was highly collimated, with a cross section of mm 2 at the sample position. The high resolution monochromator scanned the energy of the X-ray beam incident on the sample in the vicinity of kev with a step size of 0.25 mev with 5 seconds on each point. Measured energy ranges were 30 to 120 mev for Mb(IV)=O (totally 52 scans), 30 to 100 mev for Mb(III) OH (12 scans at both higher and lower temperatures) and 20 to 80 mev for metmb (32 scans). An avalanche photodiode detector (APD) detected X-rays emitted from the sample. Timing 62

63 circuitry excluded prompt events coincident with the X-ray pulse, due to scattered photons, and counted events delayed in time with respect to the incident X-ray pulse, which are emitted by excited 57 Fe atoms. The resulting delayed count rate monitors 57 Fe absorption as a function of incident X-ray energy. The incident kev X-ray flux was approximately 10 9 Hz. Multiple energy scans were collected and averaged for each sample, and comparison of initial and final scans confirmed the absence of spectroscopic changes due to radiation damage. Raman Measurement: Cryogenic resonance Raman spectra were obtained through a confocal Raman microscope (LabRam HR800, Horiba JY) on free standing films frozen on nylon cryoloops(hampton Research) and cooled by 100 K nitrogen stream from a cryostream cooler (700 Series, Oxford Cryosystems). Scattering was excited using nm line of a Krypton laser (Innova 302C, Coherent). The laser spot ( 20µm in diameter for a 10 objective) was continuously scanned along a line during data collection, in order to reduce the average power density. Mb(IV)=O: The laser power on cryogenic Mb(IV)=O samples was 1 mw. Spectral contributions from irreversible photo chemistry were minimized by adding 6 to 8 spectra measured on different spots of the sample, with 4 minutes on each spot. Photoreduction measurements on Mb(IV)=O was done by focusing the laser on a fixed spot on the frozen sample at 100 K with different power levels. Mb(III) OH: The laser power on the cryogenic MbOH samples were 2 mw for the Mb 18 OH and 0.55 mw for the rest. The accumulation time was 16 minutes for the 57 Fe and 54 Fe labeled sample, 6 minutes for the Mb 18 OH and 8 minutes for the rest. Mb(III) OH 2 : The laser power on the cryogenic MbOH 2 samples were mw, accumulation time was 4 minutes for the native sample and 8 minutes for the rest. Raman spectra of all 57 Fe and 54 Fe labeled samples were also measured at room temperature in spinning NMR tube with the same optical setup mentioned above. The laser power at the samples were 5.5 mw (Mb(IV)=O), 8 mw (Mb(III) OH) and 3.5 mw (Mb(III) OH 2 ). 63

64 In photoreduction measurements on Mb(IV)=O, low power with line scanning was used to obtain an intact (i.e., with minimal photoreduction) spectrum while high power with point focusing was applied to maximize the photoreduction. All Raman spectra were calibrated using fenchone (94). The resolution of the Raman spectra is about 2 cm 1. Relation between Raman Isotope Shift and KED: The kinetic energy distribution (KED) can be calculated using isotope shift observed in Raman measurement. The relationship between the Raman isotope shift ( ν a ) and KED of atom j in vibrational modeα(e 2 jα ) is described in Chapter 2 (see Eqn. 2.16). NRVS Data Analysis: The measured NRVS data were processed with the program PHOENIX (55). In general, individual scans were summed and then normalized to the recoil energy E R = 1.96 mev of a free 57 Fe nucleus, according to Lipkin s sum rule(95) ES (E) de=e R, to yield the excitation probability S (E). PHOENIX extracted the Fe-weighted vibrational density of states (Fe VDOS) D(E) from S (E) by removing the elastic central peak, multiphonon contributions and temperature dependence (96)(55). The input sample temperature is adjusted to be consistent with the ratio of Stokes and anti-stokes contributions to S (E). For convenient comparison with Raman spectra, the VDOS is presented as a function of the wavenumber ν=(e E o )/hc, with D( ν) rescaled to maintain the normalization D( ν) d ν = 3. (3.1) The stiffness (36, 58, 59) k s = m Fe ω 2 =m Fe (2πc) D( ν) ν 2 d ν (3.2) determined from the VDOS measures the average strength of the iron-ligand bonds. 64

65 In a normalized spectrum of Fe VDOS, the area of a single mode is equal to the mode kinetic energy distribution (KED) to the atom Fe (25). We also denote it as e 2 Fe. Thus fitting of an Fe VDOS spectrum will help to resolve vibrational modes (center ( ν) and width of fitted peak), as well as associated e 2 Fe (area of fitted peak). Computational Methods: DFT computational methods are described in Chapter 2. Models containing full Fe-protoporphyrin IX, monooxygen ligands (O 2, OH or H 2 O) and amino acid residues His93 and Ser92) are used in the computation. Optimized models of Mb(IV)=O and Mb(IV) OH are shown in Fig Selected optimized geometry parameters are listed in Table

66 Mb(IV)=O Mb(IV) OH Figure 3.6: Optimized structures of the Mb(IV)=O and Mb(IV) OH models rendered using MOLEKEL (97). Protonation of the oxo group in the latter model results in significant lengthening of the Fe O bond as well as tilting of the imidazole plane from being perpendicular to the heme plane. The Fe-ligand geometry is listed in Table 3.3. The color scheme is: cyan iron, green carbon, blue nitrogen, red oxygen, grey hydrogen. 66

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90 3.6 Supplemental Data Spin density map obtained in DFT computation. Figure 3.18: Predicted electronic spin density surface (isovalue=0.005) for: Mb(IV)=O (S=1), Mb(IV) OH (S=1; q=0,+1), Mb(III) OH(S=1/2, 5/2), Mb(III) OH2(S =1/2, 5/2). The model labeled here as Mb(IV) OH was the one published in (1), also listed in Tab. 3.3 with S= 1, q=0. The Mb(IV) OH+H + model is the same as the Mb(IV) OH depicted in Fig. 3.6 and also listed in Tab. 3.3 with S= 1, q=+1. 90