The Intrinsic Dynamics of Arginine Kinase Omar Davulcu

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FLORIDA STATE UNIVERSITY

COLLEGE OF ARTS AND SCIENCES

THE INTRINSIC DYNAMICS OF ARGININE KINASE

OMAR DAVULCU

A Dissertation submitted to the Department of Chemistry and Biochemistry in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Degree Awarded: Spring Semester, 2008 The members of the Committee approve the Dissertation of Omar Davulcu defended on December 13, 2007.

Michael S. Chapman Professor Co-Directing Dissertation

Timothy M. Logan Professor Co-Directing Dissertation

W. Ross Ellington Outside Committee Member

John G. Dorsey Committee Member

Approved:

Joseph B. Schlenoff, Chair, Department of Chemistry and Biochemistry

The Office of Graduate Studies has verified and approved the above named committee members.

ii This work is dedicated to my parents, Umit and Sengul Davulcu, whose unending love and support has provided me the courage to pursue my dreams.

iii ACKNOWLEDGEMENTS

Countless people have played integral parts in the realization of the work described in this dissertation. I would first like to thank my mentor, Dr. Michael Chapman, for his encouragement, unending patience, and willingness to take a chance on a student who knew nothing about NMR spectroscopy.

My thanks also go to our collaborator, Dr. Jack Skalicky, who has been more like a co-mentor to me than anything else. I am deeply indebted to Jack for what I have learned of both NMR spectroscopy and bird watching.

To the members of my committee, Drs. Tim Logan, Ross Ellington, and John Dorsey, I also extend my thanks. Their willingness to answer questions and give suggestions – work related and not – has proven to be invaluable.

I would also like to thank the current and former members of both the Chapman and Ellington laboratories for advice and assistance. My heartfelt thanks especially go out to Drs. Jim Gattis, Gregg Hoffman, and Eliza Ruben for being the best colleagues and friends a person could hope to have.

A very special thanks goes to Nancy Meyer for sticking with me in times both easy and rough.

This work was funded by the National Institutes of Health grant GM77643 to Michael Chapman, the National Science Foundation through the National High Magnetic Field Laboratory’s in-house research project grant 5024-641-22 to Michael Chapman and Jack Skalicky, and the American Heart Association grant 0415115B to Omar Davulcu.

iv TABLE OF CONTENTS

List of Tables ...... vi List of Figures ...... vii Abstract ...... viii

1. Introduction ...... 1

2. Sample preparation and resonance assignment ...... 17

3. Slow, main-chain dynamics of substrate-free arginine kinase ...... 31

4. Substrate induced changes in arginine kinase...... 46

5. Conclusions and future directions ...... 61

APPENDICES ...... 65

A. Expression and purification of isotope enriched arginine kinase ...... 65 B. Additional spectra and chemical shift tables ...... 69

REFERENCES ...... 82

BIOGRAPHICAL SKETCH ...... 95

v LIST OF TABLES

Table 1: Summary of triple resonance experiments for assignment ...... 21

Table 2: Summary of individual exchange parameters...... 35

Table 3: Summary of collective exchange parameters ...... 37

Table 4: Summary of KD values obtained from substrate titrations ...... 51

vi LIST OF FIGURES

Figure 1: Kinetic mechanism of arginine kinase ...... 2

Figure 2: Comparison of arginine kinase crystal structures ...... 4

Figure 3: 2D [15N, 1H]-TROSY of arginine kinase with assignments ...... 20

Figure 4: Summary of triple resonance arginine kinase data ...... 22

Figure 5: 2D [15N, 1H]-TROSY of 15N-arginine arginine kinase ...... 23

Figure 6: Connectivities in the 3D [13C, 15N, 1H]-HNCACB experiment ...... 25

13 15 1 Figure 7: Cβ chemical shifts in the 3D [ C, N, H]-HNCACB experiment .....26

Figure 8: Impact of arginine kinase refolding upon deuterium back-exchange .29

Figure 9: Relaxation dispersion profiles obtained from individual fits ...... 38

Figure 10: Relaxation dispersion profiles obtained from collective fits ...... 39

Figure 11: Amino acid composition of collectively fit regions ...... 40

Figure 12: Conformational exchange in substrate-free arginine kinase ...... 42

Figure 13: Summary of titration data ...... 49

Figure 14: Chemical shift perturbations for ATP and arginine titrations ...... 52

Figure 15: Details of substrate titrations ...... 54

vii ABSTRACT

Arginine kinase reversibly catalyzes phosphoryl transfer between ATP and arginine, thus providing a mechanism for buffering ATP levels in cells with high or variable energy requirements. X-ray crystal structures of a substrate-free and transition state analog form of arginine kinase suggest large conformational changes upon substrate binding. Steady state enzyme kinetics show that arginine kinase follows a random, bimolecular bimolecular kinetic mechanism with a turnover rate of ~135 sec-1. While the crystal structures have provided a wealth of information about the conformational changes of arginine kinase, they provide little to no data on dynamics. Crystal structures provide static snapshots at endpoints of rather complex equilibria. The link between enzyme dynamics and function is increasingly apparent but still remains relatively unexplored. Recently developed NMR techniques which probe dynamics on the micro- to millisecond timescale have provided insight into connection between dynamics and catalysis in a number of systems. The work presented in this dissertation is an NMR-based investigation into the dynamics or arginine kinase. Expression and purification of arginine kinase enriched with 15N, 13C, and 2H, a requirement for the NMR experiments, was achieved. Another prerequisite, resonance assignment, was accomplished using a standard suite of triple resonance NMR experiments and urea-induced unfolding and refolding to allow for back-exchange of amide deuterons in the core with solvent protons. Backbone amide resonances were assigned for 329 of 344 assignable residues. At the time, arginine kinase was one of the five largest monomeric units to be assigned. Using 15N transverse relaxation dispersion experiments, the dynamics of substrate-free arginine kinase were probed. These experiments implicate a number of residues, which cluster in four regions of the enzyme, in slow micro- to millisecond timescale dynamics. Most interesting is the loop spanning residues I182-G209, which the crystal structures show undergoes a large conformational change to interact with substrate nucleotide. The rate of exchange for this

viii loop was found to be approximately 800 sec-1, on the same order as turnover, indicating that the motion associated with this loop may be a rate-limiting step upon catalysis. Furthermore, the changes associated with binding of substrates have been probed by substrate titrations in conjunction with 2D [15N, 1H]-TROSY spectroscopy. These experiments, which segregate the conformational changes seen in the crystal structures into those induced by binding of individual substrates, show that phosphagen and nucleotide binding elicits relatively independent changes in the N-terminal and C-terminal domains, respectively. The loop spanning residues I182-C201, however, appears to be affected by both substrates. Interestingly, this is the same loop relaxation dispersion experiments implicate in slow dynamics. As a bimolecular enzyme representative of a large enzyme class, the transferases, the amenability of arginine kinase to both x-ray crystallography and NMR make it a unique model system for understanding the connections between dynamics and function. The work described here outlines the potentially rate limiting intrinsic dynamics of arginine kinase and changes induced by substrate binding. These results highlight the importance of dynamics and reflect the growing view that enzymes have evolved both structure and dynamics simultaneously.

ix 1. INTRODUCTION

Phosphagen kinase physiology and catalysis Tissues and cells with high and/or variable energy demands, such as cardiac muscle and sperm cells, require a system for maintaining cellular ATP levels. ATP is the cellular energy “currency” – its hydrolysis linked to and provides the energy for otherwise endergonic chemical reactions, molecular motions and transport [1]. It has been reported that vertebrate cardiac cells consume 2% of the total available ATP in a single heartbeat [2]. The necessity of a system to maintain near constant levels of ATP is made clear when the thermodynamics of its hydrolysis are considered:

0 ΔGATP = ΔG ATP + RT ln([ADP][Pi /[] ATP])

0 where ΔGATP is the effective free energy of ATP hydrolysis and ΔG ATP is the standard free energy of ATP hydrolysis, -30.5 kJ/mol. This relationship demonstrates the link between ΔGATP and cellular concentrations of ATP, ADP, and Pi. As ATP is consumed and ADP and Pi are generated, the free energy yield of ATP hydrolysis would decline unless ATP is replenished and the non-equilibrium state is maintained. A declining energy yield could not be tolerated, because ATP would cease to provide sufficient energy to drive essential cellular processes.

Maintenance of a ΔGATP of approximately -60 kJ/mol, which is typical in many tissues [3], requires maintenance of the [ADP]/[ATP] ratio by rapid rephosphorylation of ADP to regenerate ATP. It has been shown that cells function within a relatively narrow

ΔGATP range [4, 5]. In tissues and cells without high and/or variable energy requirements, metabolic pathways such as oxidative phosphorylation provide an adequate means of ATP regeneration [3, 6]. In those tissues and cells with highly fluctuating energy demands, however, ATP regeneration through metabolic pathways alone can not keep up with bursts of ATP usage [3, 6]. These cells achieve rapid cellular buffering of ATP levels through reactions catalyzed by the phosphagen kinase family of enzymes. These enzymes catalyze reversible phosphoryl transfer between ATP and a phosphagen – a guanidinium containing compound, thus providing a means of regenerating ATP [7]. It has also been

1 proposed that the use of a phosphagen as an energy-storing molecule may provide efficient shuttling of energy between cellular compartments [7-9]. The phosphagen kinase family of enzymes consists of eight known and highly conserved enzymes, representatives of which are found in nearly all animals [10, 11]. Each of the enzymes within this family uses a different phosphagen substrate. These substrates, while varying largely in size and electrostatic properties, all share the same functional guanidinium group [10]. Enzyme kinetics has shown that two members of this family, arginine kinase and creatine kinase, share a rapid equilibrium, random order bimolecular-bimolecular mechanism which is likely common to all of the phosphagen kinases [12].

Arginine kinase structure and function Arginine kinase (E.C. 2.7.3.3), the focus of this work, catalyzes reversible phosphoryl transfer between ATP and arginine and is found in invertebrates and protozoans. Enzyme kinetics has elucidated not only the kinetic mechanism (Figure 1), but also a turnover rate of approximately 135 sec-1 [12] and the presence of positive substrate binding synergy, in which binding of one substrate enhances binding of a second substrate [12, 13]. Substrate binding in arginine kinase is accompanied by large, and potentially rate limiting, conformational changes, as first implicated by x-ray solution scattering experiments [14]. The conformational changes are of a magnitude that in other

Figure 1: Kinetic mechanism of arginine kinase with binary complexes colored blue and ternary complexes colored red. Equilibrium dissociation constants are denoted as KS for binary complexes and KM for ternary complexes, and the catalytic step is denoted as kcat. Arg and parg represent arginine and phosphoarginine, respectively.

2 enzyme systems might be considered potentially rate-limiting [15]. Indeed, in the phosphagen kinases, relatively low turnover number suggests that the rate limiting steps are not chemical [16]. X-ray crystal structures have provided the clearest view of the extent of substrate induced conformational changes in arginine kinase. Two, high resolution crystal structures of arginine kinase are available: one in a substrate-free, or ‘open’, form, solved by Yousef et al [17] and one in a transition state analog complex, or ‘closed’, form, determined by Zhou et al [18]. The latter structure crystallized with arginine, MgADP, and nitrate, which mimics the planar transition state of the transferred phosphoryl group. These structures show arginine kinase to be a two-domain enzyme with a small, α-helical N-terminal domain linked to a larger, primarily β-sheet C-terminal domain, with substrates binding in the cleft between these two domains [17, 18]. Analysis of B-factors of backbone N atoms in the substrate-free crystal structure implicates a number of regions as dynamic. As this structure lacks any bound substrates, these dynamics are inherent to arginine kinase. Elevated B-factors can be seen in residues G172-Q179, K189-L195, and A291-E298, all of which are primarily loops. Residues R309-G320 are disordered and not modeled in the substrate-free structure [17]. B-factors for all of these regions are reduced in the transition state structure, residues R309-G320 can be seen, but B-factors for A291-E298 still remain well above the mean [18]. Comparison of the open and closed crystal structures of arginine kinase provides a detailed picture of substrate induced conformational changes (Figure 2). Simply put, both N-terminal and C-terminal domains fold over the active site, along with a number of loops. These large scale motions may, among other things, serve to prevent wasteful hydrolysis through substitution of solvent water for substrate as the nucleophile. Analysis of the paired open and closed structures with DynDom yields three ‘dynamic domains’ which undergo a hinged rotation relative to a fourth, fixed domain [17-20]. Within these domain motions are also loop reconfigurations. The site of largest conformational change upon substrate binding is the loop containing H185, which closes a ~10 Å gap to interact with the ribose of substrate nucleotide. The substrate specificity loop, residues L61-Y68, moves closer to the arginine binding site to interact with the

3 amino acid end of substrate arginine [17, 18]. It is thought that this loop plays a role in mediation of specificity through steric interactions that distinguish arginine from other phosphagens that are substrates for arginine kinase homologues [21-23]. Similar conformational changes are seen in an x-ray crystal structure of creatine kinase bound to a transition state analog, suggesting that the entire family of phosphagen kinases undergoes a common set of fundamental structural changes possibly involved in mediating substrate specificity, preventing wasteful hydrolysis of ATP, and perhaps also precisely aligning substrates for phosphoryl transfer [24-27]. Even with the wealth of structural and kinetic data available today, the link between dynamics and catalysis still remains elusive. Recent publications point to a growing appreciation of the critical role of dynamics in enzyme catalysis [28, 29]. Authors Benkovic and Hammes-Schiffer note that we remain largely ignorant of the mechanics of how dynamics are used to achieve catalytic effects, because techniques for mapping protein motion have lagged far behind those for analyzing static structures [28].

Figure 2: Comparison of crystal structures of arginine kinase. The substrate-free structure is shown in red and the aligned transition state structure in blue [17, 18].

Computation and experimentation have indicated that motion can be used: (a) in reducing the free-energy activation barrier through the harnessing of an atom’s kinetic energy; (b) in the dynamics alignment of substrates in near transition state geometries; (c) in configuring active sites for catalysis; and (d) in product release [30-40].

4 Conformational dynamics in enzyme catalysis The importance of motion and dynamics were initially proposed by Daniel Koshland. Emil Fischer’s work with maltase and emulsin had led to the ‘lock and key’ theory which describes substrates as keys and enzymes as locks to which these keys fit [41]. Koshland, in noticing that the lock and key theory failed to explain, among other things, binding of analogues to enzymes, augmented Fischer’s theory. Koshland’s theory of induced fit describes enzymes not as rigid locks but as flexible entities. Binding of substrate or analog induces changes in the enzyme and only those induced by the correct substrate achieve an active enzyme configuration [42]. Today, with increasing numbers of structures of enzymes in substrate-free and various bound states available, the ubiquity of conformational change is now apparent and some examples are described below. Structurally and mechanistically, dihydrofolate reductase is likely one of the most well characterized enzymes to date [43]. This enzyme catalyzes hydride transfer from NADPH to dihydrofolate (DHF) to form tetrahydrofolate (THF) [44]. Over 40 crystal structures of the enzyme exist, including those of intermediates or models of intermediates, which define the conformational changes that occur during the catalytic cycle [45, 46] The kinetic mechanism, in which the enzyme cycles through five observable intermediates, has also been elucidated and it has been shown that NADPH rebinds the enzyme before THF is released and that product release is likely the rate- limiting step [47-50]. Crystal structures suggest that three loops adopt different conformations – open, closed, or occluded – depending upon which ligands are bound [51]. The conformations of these loops are intimately connected with catalysis, as hydride transfer occurs concurrently with a millisecond-timescale transition from the closed form to the occluded form in one of these loops [44, 51] These conformational changes are suggested as having a role in catalysis by aligning substrates. The occluded conformation forces the nicotinamide ring into the solvent and blocks its entry to the active site, making the closed conformation the only one favorable to catalysis [44, 46]. Additionally, mutations in these loops reduce both the turnover rate and the rate of conformational exchange, establishing a clear link between these conformational changes and catalysis [51].

5 Fluctuations on the pico- to nanosecond timescale have also been shown to play a role. A number of residues in the loops mentioned above have been shown to possess dynamics on this timescale in the occluded conformation [52]. Upon formation of the closed conformation, however, these motions are dampened [43, 53]. It is suggested that this decrease in fast motions may play a role in limiting diffusion to and from the active site and for proper alignment of substrates [44]. Dynamics across the femto- to millisecond timescale in dihydrofolate reductase have been unified in what has been termed a network of coupled motions [54]. It is common knowledge that engineered mutations in proteins can be expected to impact the entire structure of the protein. The work of Stephen Benkovic and Sharon Hammes- Schiffer has exquisitely described a network of amino acid interactions in dihydrofolate reductase which link dynamics on the femtosecond to millisecond timescales with catalysis [54]. This work has rationalized the impact of mutations at sites distal to the active site of dihydrofolate reductase (disruption of the network), the nonadditivity of the effects of multiple mutations (different amounts of disruption of the network), and has provided a new perspective on allosteric regulation (modulation of the network) [51, 54, 55]. Triosephosphate isomerase, another well studied system, reversibly catalyzes isomerization of dihydroxyacetone phosphate to D-glyceraldehyde 3-phosphate [56]. Crystal structures of the substrate-free enzyme [56, 57], a near atomic resolution Michaelis complex [58], and a complex with an inhibitor [59] have been determined. These structures implicate one loop, termed the flexible loop, as being involved in substrate induced conformational change. It was suggested that this loop acts as a ‘lid’ to seal off the active site of the enzyme following substrate binding to exclude bulk solvent and even modify the dielectric near the active site [57, 59, 60]. The dynamics of the flexible loop of triosephosphate isomerase have also been shown to play a role in alignment of substrates for catalysis. The crystal structure of the Michaelis complex shows residues in this loop interacting with bound substrate and preventing elimination of inorganic phosphate [55, 58]. In fact, deletions of residues in this loop have been shown to cause substantial increases in inorganic phosphate production [61].

6 Interestingly, later experiments have shown that the motion of this flexible loop is not ligand induced and is actually intrinsic to the enzyme [60]. Furthermore, the rate of motion for this loop, ~104 sec-1, was shown to be on the same order as turnover [60]. Measurement of the rates of loop motion and catalysis as a function of temperature have shown that the motion of the flexible loop may be partially rate limiting upon catalysis [15]. Further investigations show that it is in fact opening of this loop and subsequent product release which is the rate limiting step [62]. Briefly, as mentioned above, recent developments have provided a new view of allostery. Allostery, defined as events in one part of a protein affecting a different part of a protein, is typically associated with conformational changes associated with ligand binding being propagated between the regulatory and active sites of a protein and is a powerful means of regulation [63]. One system in which the interplay between dynamics and allostery has been investigated is the transcriptional enhancer nitrogen regulatory protein C, which is a two- component signal transducer involved in nitrogen regulation [64]. Phosphorylation of a ‘receiver domain’ in the protein is required for activation of an ATPase in a ‘central domain’ [64]. This activation impacts downstream transcription of genes involved in nitrogen metabolism. Solution structures of the inactive (dephosphorylated) and active (phosphorylated) forms of the receiver domain have been determined [64, 65]. These structures show that activation of the receiver domain is followed by a suite of conformational changes that are propagated to the central domain [64, 65]. Investigations into the dynamics of the inactive and active forms of nitrogen regulatory protein C, however, provide a much more interesting picture. Dynamics on the pico- to nanosecond timescale did not change as a result of phosphorylation, implying that this timescale does not play a role in activation [66]. There are changes in the micro- to millisecond timescale, however, indicating that slow dynamics play a role in conveying the allosteric signal between domains [66]. Furthermore, it was found that a preexisting equilibrium exists between the inactive and active forms in the absence of phosphorylation and that the phosphorylation event acts to shift this equilibrium towards the active form [66].

7 Methods for characterizing dynamics As demonstrated by the examples described above, enzyme motions important to function span a wide range of timescales and a number of biophysical methods have been developed to probe these different timescales. These methods are as varied as the energies of interactions (and frequencies) and the amplitudes of motions involved. Relatively fast motions on the order of femto- to picoseconds with magnitudes of 0.01 to 0.1 Å, which may be associated with covalent bond breaking and formation, proton and hydride transfer, and methyl group rotation, can be probed with optical methods [28]. Raman spectroscopy has been used to investigate rhodopsin and a rhodopsin-specific cofactor, in which structural changes were observed to occur in the first 20 picoseconds of vision. These motions were implicated in both substrate alignment and transition state stabilization [67]. While development of Raman spectroscopy has advanced vibrational studies of enzymes, these studies typically revolve around scattering observed from aromatic amino acids [67], which limits studies to specific sites of native proteins. Fluorescence resonance energy transfer (FRET) has been a popular method for probing motions on the order of nano- to picoseconds with magnitudes of 0.1 to 5 Å. FRET experiments are gaining in use due to the ability to make single molecule measurements in real time under near physiological conditions [68]. An investigation into the dynamics involved in the product release steps of the enzyme protochlorophyllide oxidoreductase identified two new product release pathways which are dependant upon temperature. Enzyme dynamics were implicated in product release in thermophillic versions of the enzyme due to inability of product chlorophyllide to dissociate from enzyme at low temperatures [69]. While extremely useful in probing conformational dynamics, these techniques are typically site-specific, involving incorporation of fluorescent labels at different locations in an enzyme. This approach quickly becomes impractical when an entire enzyme is to be surveyed. Substrate-triggered dynamics on the nano- to microsecond timescale and slower, with magnitudes of intermediate size, large enough (> ~0.5 Å) to be seen, but small enough to have little impact upon crystal packing, can be probed with time resolved crystallography. These dynamics can include hinge bending, domain motions and local unfolding. Time resolved crystallography can be used to produce a sequence of structural

8 ‘snapshots’ separated by microseconds via the use of caged substrates. This technique requires that the motions involved do not disrupt the crystal lattice and that caged substrates exist and can be released by photolysis [70-75]. These requirements severely limit the systems which can be explored with time resolved crystallography; in nearly two decades, this approach has been applied to only a select few enzymes [70, 71]. This technique has been used to describe the kinetic mechanism and conformational change associated with photoreceptor photoactive yellow protein, some of which occurred over 20 Å away from the active site and are required for catalysis [72]. Hydrogen/deuterium exchange experiments, which probe very slow, sub-second dynamics with magnitudes typically greater than 1 Å, have been of growing interest in recent literature. These experiments measure changes in solvent exposure of residues which is a reflection of local folding/unfolding transitions and provide an alternative route for investigations of dynamics for proteins which are not amenable to NMR studies due to, for example, size or solubility constraints [76]. Coupled to mass spectrometry, hydrogen/deuterium exchange has been used to probe dynamics in substrate-free and transition state analog bound creatine kinase, along with guanidinium chloride induced creatine kinase unfolding [77-80]. In substrate-free creatine kinase, high rates of deuteration, which reflect local dynamics on the timescale of tenths of seconds and slower, were detected in a number of peptides, including the N-terminus, residues 51-72 which is the substrate specificity loop, 193-201, and 312-330 [80]. Upon formation of the transition state analog complex, rates of deuteration were reduced in all of these peptides except the N-terminus, indicating that binding of substrates impacts the dynamics of these regions, likely though direct interactions with either the substrates themselves or newly formed hydrogen bonds, as is the case between residues D325 and H65 [27, 79]. Nuclear magnetic resonance (NMR) can probe dynamics across a range of timescales, including those most likely relevant to enzymatic turnover. Order parameters characterizing amplitudes of intramolecular motions and correlation times for these motions can be derived from the Lipari-Szabo formalism and its treatment of the spectral density function, providing a robust technique for investigating motions of ~20 nanoseconds and faster [81-85]. Experiments have been developed to probe a wide range

9 of bond vectors describing covalently connected nuclei pairs. These experiments have been applied to a vast array of proteins and enzymes, including adenylate kinase, lysozyme, and RNase A [44]. These, and in fact all, NMR experiments on proteins, require enrichment in spin-½ nuclei (15N, 13C) and can simultaneously probe all instances of a given bond vector (backbone NH vector, for example). Another NMR measurement, the residual dipolar coupling, provides access to sub-millisecond timescale dynamics on a per-residue basis [86]. Residual dipolar couplings are a result of the magnetic dipole-dipole coupling between nuclei pairs [87] and are typically represented as vectors between these nuclei – a vector connecting the 15N and 1H nuclei which comprise an amide group in a protein, for example. Under typical, isotropic solution conditions, this vector maps out all space and the coupling averages to zero as the molecule tumbles in solution [86]. Therefore, molecular alignment is necessary and typically achieved by addition of an alignment medium, such as phospholipid bicelles, polyacrylamide gels, and even bacteriophages [86, 87]. Residual dipolar couplings have been used to describe the dynamics associated with ligand binding in maltose binding protein, including reorientations of domains which prove to be critical to interaction with cellular receptors [88]. Technically, measuring residual dipolar couplings can be difficult for large proteins without special labeling procedures [89]. Selection of alignment media can be problematic due to incompatibilities between various proteins and media, instability of various alignment media, and differences in the nature of alignment [86, 87]. Additionally, multiple different media must be used as a single dipolar coupling leads to an ambiguous set of vector orientations [87]. This degeneracy can be resolved by use of multiple media [87]. Most intriguing is the use of NMR to explore slower motions, those on the order of milli- to microseconds, using relaxation dispersion experiments. These methods, which exploit the dependence of R2 upon slow motions and effective magnetic fields, allow one to survey all sites of a protein for dynamics simultaneously. R2, the transverse relaxation rate constant, describes loss of coherence of transverse magnetization and can encode information about slower dynamics. Capable of measuring exchange rates down to 50 sec-1, relaxation-based experiments can provide unique insight into dynamics that are either intrinsic to a protein or associated with catalysis [90]. As with virtually any

10 NMR investigation, there are a number of prerequisites, such as isotope enrichment and resonance assignment. NMR-based protein investigations are also limited by molecular mass of the protein, but recently developed pulse sequences and labeling schemes continue to push this limit higher [89]. Transverse relaxation dispersion experiments have been used to describe conformational transitions throughout the catalytic cycle for cyclophillin A, pin1, and RNase A [91-95]. In RNase A, millisecond timescale dynamics of regions distal to the active site were found to be critical to enzymatic activity [91]. A single histidine residue was found to be at the core of the coupling between dynamics and catalysis, despite being 18 Å from the active site [91]. It is important to note that computational methods have also provided tremendous insight into the dynamics of biomolecules. These methods, examples of which are presented below, typically share a set of advantages and disadvantages. Computational approaches provide details of the motions of particles as a function of time [96, 97] which are typically inaccessible via experimental approaches. Another advantage to simulations is that the potentials used in the calculations are under user control. One has the ability to alter or completely remove specific components of a physical property, therefore determining the impact that component has on the given property [96]. For example, free energy simulations of asparagine and aspartate binding to aspartyl-tRNA synthetase used ‘computational alchemy’ – modulation of protein and solvent dielectrics – to probe the molecular mechanisms of this enzyme’s specificity [98]. One major limitation of computational methods is the requirement of experimental data to validate results obtained from simulation. Theoretical estimates of errors associated with simulations are often difficult, if not impossible, to quantify in the absence of comparable experimental data [96]. In practice, simulations are compared to experimental data to gauge accuracy of not only a given simulation but the methodology itself, thus providing an opportunity for both methodological improvement [96] extrapolation to systems where less experimental data might be available. Atomic level simulations typically probe motions on the order of nanoseconds and faster, limited by computational tractability [96]. Extension of these methods to larger complexes and slower timescales involves a number of approximations [96, 97, 99]. It should be noted that millisecond timescales, often of interest in conformationally limited enzyme turnover

11 rates, are beyond most computational methods and have only been probed in the unfolding reactions of very small proteins [161]. Classical molecular dynamics simulations have uncovered dynamics on the order of nanoseconds in acetylcholinesterase that are functionally critical to the enzyme [96, 100]. These dynamics – reorientations of aromatic side-chains – mediate the opening and closing of a channel through which substrate acetylcholine travels to reach a buried active site [100]. Normal mode analysis, which decomposes the dynamics of a molecule into a series of atomic vibrations, was used to probe the intrinsic dynamics of adenylate kinase [101]. Quite interestingly, the dominant modes in this analysis correlate very well with changes seen in crystal structures of adenylate kinase upon substrate binding, suggesting that large scale, substrate induced conformational changes in proteins may exploit smaller amplitude, higher frequency, intrinsic dynamics [102]. The elastic network model, a ‘course-grained’ approach which reduces groups of atoms, such as amino acid residues in a protein, to single objects allows for extension of the methodology into macromolecular complexes at the cost of losing atomic detail [99]. This approach has been used to simulate the ‘ratchet-like’ motion of the ribosome, which corresponds very well with electron microscopy data [103-105] in spite of the simplifications made. This ratchet-like motion was found to be critical to translocation of the ribosome during protein synthesis [106, 107]. These techniques all point to inexorable connections between dynamics and catalysis, even though the majority of information obtained from structural biology is static. Enzyme fluctuations, in the examples mentioned above, have been shown to be involved substrate binding, turnover, and product release. These studies, particularly the NMR-based investigations, provide interesting ‘twists’ to the idea of induced-fit turnover. Static structures, such as those obtained from NMR and x-ray crystallography, show only the lowest energy conformations of an enzyme. Studies of slow timescale dynamics, however, show that excursions to higher energy states are critical to enzyme function and some of these dynamic modes may actually be intrinsic to the enzyme in question and not induced by substrate [44]. Dynamics associated with arginine kinase catalysis are likely on the millisecond timescale and this expectation eliminates a number of these potential techniques.

12 Transverse relaxation dispersion methods, detailed below, are chosen due to their ability to probe this timescale, to survey multiple protein sites simultaneously, and to be applied to both substrate-free and various complexed forms of arginine kinase. Due to the relatively large size of arginine kinase (~42 kDa), a number of initial hurdles must be overcome, such as high levels of 2H incorporation and resonance assignment. In this dissertation, these issues are addressed and intrinsic dynamics are probed using transverse relaxation dispersion.

Relaxation dispersion and conformational exchange One of the earliest applications of NMR was the measurement of dynamics in biological molecules. Fast, pico- to nano-second timescale dynamics have typically been studied by measuring the longitudinal relaxation rate (R1), the transverse relaxation rate

(R2), and the heteronuclear NOE enhancement [44]. Relaxation rates and dynamics are linked by the fact that molecular motion leads to local magnetic field fluctuations which then cause relaxation. Analysis of these data via the Lipari-Szabo formalism ultimately results in a description of the magnitude of internal motions, modeled isotropically through S2, the order parameter. Values approaching 1 imply restricted internal motions and values approaching 0 imply unrestricted motions [44, 84, 85]. Protein conformational changes linked to substrate binding and product release, and sometimes instrinsic protein motions, typically occur on timescales slower than those accessed through Lipari-Szabo analysis of relaxation rates [44]. The timescales involved in these processes typically span micro- to milli-seconds. Furthermore, no general relationship between these slower timescale motions and those probed through S2 obtained from Lipari-Szabo analysis has been reported [44].

There is a relationship, however, between the R2 used in Lipari-Szabo analysis and slower, micro- to milli-second timescale dynamics. When a nucleus is undergoing conformational exchange on this timescale, then the pico- to nano-second timescale motions probed with Lipari-Szabo analysis do not fully account for observed R2 relaxation rates [44]. These cases require invocation of an additional term, Rex, which is related to R2 as follows:

0 R2 = R2 + Rex (1)

13 0 where R2 is the observed transverse relaxation rate, R2 is the transverse relaxation rate in the absence of conformational exchange, and Rex is the contribution to transverse relaxation due to conformational exchange which arises from different magnetic environments explored by a nucleus undergoing conformational exchange [44].

Rex can be measured by two NMR methods: R1ρ or R2 transverse relaxation dispersion experiments [44], with the focus here being placed upon R2 relaxation dispersion methods. Transverse relaxation dispersion experiments are chosen in this work due to the ability of these methods to measure exchange rates in the range of 50- 1500 sec-1 – within which the rate of functional dynamics in arginine kinase are expected, based on kcat [12, 90]. R1ρ methods, on the other hand, are typically used to probe a slightly faster range of 2500-10000 sec-1 [90]. Transverse relaxation dispersion methods provide a means of measuring Rex by exploiting the dependence of Rex upon an applied

B1, or effective, field strength. In relaxation dispersion experiments, the effective field strength, νCPMG, is modulated by changing τCPMG, the time between successive inversion pulses, in a constant-time Carr-Purcell-Meiboom-Gill (CPMG) pulse block and is defined as [44]:

−1 υCPMG = 4( τ CPMG ) (2)

As effective field strength increases, Rex decreases, resulting in a decrease in R2 until the

Rex contribution is minimized. Plots of R2 as a function of νCPMG result in relaxation dispersion profiles (see Figures 9 and 10 for examples). Assuming a two-state model and fast exchange on the chemical shift timescale, these relaxation dispersion profiles can be fit to the following equation to obtain relevant exchange parameters:

2 Rex /1( τ CPMG ) = ( p A pB Δω / kex 1)[ − tanh(kex 8/ υCPMG /() kex 8/ υCPMG )] (3) where pA and pB are populations of the two states, Δω is the chemical shift difference between the two states, and kex is the sum of forward and reverse rate constants describing exchange between the two states [108, 109]. As mentioned above, relaxation dispersion experiments have been used to describe motions associated with substrate binding, product release and enzymatic catalysis in cyclophillin A, RNase A, and dihydrofolate reductase [91, 93, 94, 110].

Arginine kinase dynamics With two, high resolution crystal structures [17, 18], a turnover number of approximately 135 sec-1 [12] and evidence suggesting that catalysis may be limited by conformational change [14], arginine kinase, a bimolecular enzyme catalyzing the common, biologically relevant reaction of phosphoryl transfer, presents itself as an exceptional model for understanding the roles dynamics may play in catalysis. As catalytically relevant dynamics are likely on the millisecond timescale, relaxation dispersion experiments provide a truly unique opportunity to investigate the connections between these dynamics and catalysis in a relatively large and representative model system. The work described here is an NMR-based investigation into the conformational dynamics associated with substrate-free and various bound forms of arginine kinase. As detailed in Chapter 2, resonance assignment, a foundation of NMR studies on proteins, followed a systematic optimization of the over-expression and purification of various isotope enriched forms of arginine kinase. Using 15N transverse relaxation dispersion experiments, Chapter 3 builds upon these assignments and describes the intrinsic dynamics of arginine kinase. Finally, Chapter 4, through 2D [15N, 1H]-TROSY experiments and substrate titrations, dissects the conformational changes seen in the crystal structures of arginine kinase into those associated with binding of individual substrates [17, 18]. Resonance assignment was achieved for over 95% of the assignable backbone amide resonances in arginine kinase. 15N transverse relaxation dispersion experiments conducted on substrate-free arginine kinase implicate, among other regions of the enzyme, the loop spanning residues I182-G209 undergoing conformational exchange on the time scale of substrate turnover, indicating that conformational changes in this loop may be intrinsic to the enzyme and not induced by substrate binding. Substrate titrations reveal that changes associated with phosphagen and nucleotide binding are, for the most part, independent. Various loops are implicated in folding over the active site as a result of phosphagen or nucleotide binding, and the loop I182-C201 appears to be influenced by binding of both substrates. These titrations also provide KD values for each substrate in

15 conditions necessary for NMR, which will be vital in relaxation dispersion-based investigations of various arginine kinase complexes.

16 2. SAMPLE PREPARATION AND RESONANCE ASSIGNMENT

This chapter describes work that was summarized in Davulcu, O., Clark, S.A., Chapman, M.S. & Skalicky, J.J., Main chain (1)H, (13)C, and (15)N resonance assignments of the 42-kDa enzyme arginine kinase. J Biomol NMR, 2005. 32(2): p. 178.

Prerequisite to all of the NMR work described in this dissertation are preparation of appropriate samples and optimization of sample conditions. Isotopic enrichment of over-expressed arginine kinase with various combinations of 15N, 13C, and 2H is required based on the NMR experiment being conducted. Deuteration - high levels of 2H enrichment - is a requirement for proteins as large as arginine kinase (357 residues, 42 kDa) due to extremely efficient 13C transverse relaxation [83, 111-114]. Sample conditions must allow for high concentrations of arginine kinase, 1 mM and higher, to remain stable and soluble for the time required to perform NMR experiments, typically days to weeks. Resonance assignment was accomplished using a combination of triple resonance NMR experiments conducted on arginine kinase enriched with isotopes 15N, 13C, and 2H and 2D [15N, 1H]-TROSYs of arginine kinase enriched with specific 15N- labeled amino acids. The latter experiments greatly assisted in assignment of overlapping resonances. Resonance assignment was completed only after unfolding and refolding of the enzyme, thus allowing for back-exchange of initially deuterated amides in the core of arginine kinase with protons in solvent.

Materials and Methods Sample preparation Limulus polyphemus arginine kinase was expressed and purified in soluble form using previously published protocols [115], detailed in appendix A, which utilize DEAE anion exchange chromatography, unfolding and refolding in urea/H2O, and size exclusion chromatography. The protein was uniformly isotope enriched in 13C and 15N and ~85% 2 13 enriched in H by growth in M9 minimal media containing 0.2% C6-D-glucose, 0.1% 15 2 ( NH4)2SO4, and 100% H2O, supplemented with 0.001% thiamine and 0.001% FeCl3 [116, 117]. Purified enzyme was pooled and concentrated in NMR buffer (10 mM citric

17 2 o acid, 0.5 mM DTT, 50 mM KCl, 50 μM NaN3, 10% H2O, pH=6.5, 4 C). The unfolding/refolding protocol yielded enzyme with full activity relative to enzyme prepared without unfolding/refolding steps. Except for newly detectable resonances from amides in the core of arginine kinase (see Discussion), the 2D [15N,1H]-TROSY spectra of enzyme obtained from preparations including and omitting the unfolding/refolding step are identical. This indicates that unfolding/refolding has not changed the structure of arginine kinase or its ability to function. The unfolding-refolding step was introduced to fully replace all exchangeable deuterons with protium Expression of arginine kinase enriched in a specific 15N-labeled amino acid was accomplished with minor modifications to the standard protocol (see Appendix A). In essence, all amino acids are included in the media, and are of the 14N form, except a single amino acid type which is highly enriched in 15N. Individual unlabeled amino acids were added to the media to final concentrations of 0.01%, except for histidine, phenylalanine, proline, tyrosine, and tryptophan, which were added to final concentrations of 0.02%. Note that the labeled amino acid was not added at this point and this media should not be autoclaved. Cultures were grown at 37 oC and 250 rpm to an OD of 0.3 AU at 600 nm. At this point, labeled amino acid was added to the media and the culture is grown at 37 oC and 250 rpm to an OD of 0.6 AU at 600 nm and induced with IPTG for 2 hours. Subsequent purification follows as per the above protocol. NMR spectroscopy All NMR experiments were recorded at 25 oC on Varian INOVA600 (University of Utah, Salt Lake City, UT) and INOVA720 (National High Magnetic Field Laboratory, Tallahassee, FL) spectrometers, operating at proton frequencies of 600 and 720 MHz, respectively, and equipped with triple resonance pulsed field gradient probes. In all cases, 1H chemical shifts were referenced to the DSS methyl proton at 0 ppm and 15N and 13C chemical shifts were referenced indirectly [118]. All NMR data were processed with Felix [119] and analyzed with Sparky [120]. The 2D [15N, 1H]-TROSY of arginine kinase used in resonance assignment was 15 collected at 720 MHz using following parameters: N; t1max = 58 ms, sweep width = 82.3 ppm – recorded unaliased to avoid overlap with amide signals, 1H; acquisition time = 79 ms, spectral width = 18.1 ppm. A total of 64 transients were collected for each t1 point

18 with a recycle delay of 1.2 seconds, resulting in a measurement time of 4.5 hours. The final data matrix was processed to 1024 (15N) x 2048 (1H) points. Main chain assignments were obtained from TROSY versions of 3D [13C,15N,1H] HNCA, HNCACB, HN(CA)CB, HN(CO)CA, HN(CO)CACB, and HN(COCA)CB experiments, collected at 720 MHz [121]. The following parameters were implemented 13 15 in these experiments: C; t1max = 8 ms, sweep width = 60 ppm, N; t2max = 20 ms in all experiments except the HN(COCA)CB where t2max = 24.8 ms, sweep width = 34.3 ppm, 1H; acquisition time = 43 ms, spectral width = 16.7 ppm. A total of 4 transients were collected for each experiment except the HNCACB, in which 8 transients were collected. A recycle delay of 1.8 seconds was used in all experiments except the HN(CO)CA, where a recycle delay of 2.0 seconds was used. In all cases, final data matrices were processed to 256 (13C) x 128 (15N) x 256 (1H) points. A 3D [1H,15N,1H] NOESY was collected at 600 MHz with a 100 ms mixing time and used to identify 1HN-1HN NOEs in regular secondary structure. Brackets denote the order of frequency labeling. 2D [15N, 1H]-TROSYs of amino acid type specific labels were collected at 720 15 1 MHz using the following parameters: N; t1max = 64 ms, sweep width = 75.4 ppm, H; acquisition time = 43 ms, spectral width = 16.7 ppm. A total of 64 transients were collected for each t1 point with a recycle delay of 1.2 seconds. The final data matrices were processed to 1024 (15N) x 1024 (1H) points.

Results Using previously published expression and purification protocols [115, 122], yields of approximately 65 mg of 15N- and/or 13C-arginine kinase per liter of culture were obtained. Deuteration, in addition to incorporation of 15N and/or 13C reduced purified yields to approximately 35 mg per liter of culture. Supplementation of M9 media with both FeCl3 and thiamine is required to achieve these yields [117]. Without addition of these additives, yields for any isotopically labeled form of arginine kinase are at most 2 mg per liter of culture – insufficient to support the NMR investigations described below. Systematic screening of buffer conditions by a previous lab member, Dr. Shawn Clark, determined that arginine kinase was stable for long periods in a citrate buffer, pH=6.5, with 50 mM KCl [123]. In this buffer, arginine kinase can be maintained at

Figure 3: 2D [15N, 1H]-TROSY of triple labeled arginine kinase with resonance assignments shown.

20 Table 1: Summary of triple resonance experiments performed on triple labeled arginine kinase. These experiments are conducted with specific pulse sequences which selectively probe nuclei in the immediate covalent environment of amide groups. Experiment Observed chemical shifts N Residue i: H , N, Cα, Cβ HNCACB Residue i-1: Cα, Cβ Residue i: HN, N HNcoCACB Residue i-1: Cα, Cβ N Residue i: H , N, Cα HNCA Residue i-1: Cα Residue i: HN, N HNcoCA Residue i-1: Cα N Residue i: H , N, Cβ HNcaCB Residue i-1: Cβ Residue i: HN, N HNcocaCB Residue i-1: Cβ

concentrations upwards of 2 mM (~84 mg/ml) for months at 25 oC without major aggregation. Arginine kinase in this buffer may also be stored long-term by freezing at - 80 oC. At the core of all the NMR work described herein is one experiment: the 2D [15N, 1H]-TROSY [124]. The 2D [15N, 1H]-TROSY (Transverse Relaxation Optimized SpectroscopY) of triple labeled (15N, 13C, and 2H) arginine kinase is shown in Figure 3. This experiment provides correlations between 15N and 1H; in other words, the spectrum ideally contains a resonance for every NH group in arginine kinase. Resonances are positioned in the spectrum based on the chemical shifts of the nuclei being observed; in the case of the 2D [15N, 1H]-TROSY shown in Figure 3, 15N and 1H chemical shifts are on the y and x axes, respectively. The chemical shift provides a description of the local magnetic environment of a given nucleus and arises from the local magnetic fields caused by motions of electrons [121]. In highly structured molecules, such as proteins, nuclei of the same type, and even the same chemical bonding, but in different 3-D structural

Figure 4: Summary of triple resonance data acquired for triple labeled arginine kinase.

Resonances corresponding to Cα are colored red and Cβ are colored blue. (A) Strip contour plots for a well resolved NH signal in the 2D [15N, 1H]-TROSY (E335; 10.3 ppm 1H; 123.2 ppm 15N).

Strips are labeled according to experiment. All expected Cα and Cβ correlations are observed and are shown with horizontal lines. (B) A single 15N plane (123.2 ppm 15N) of the 3D [13C, 15N, 1H]-

HNCACB experiment. Cα and Cβ correlations for individual residues are denoted with vertical lines and labeled according to residue number. contexts will likely have different local magnetic environments, thus leading to a difference in chemical shifts. While the 2D [15N, 1H]-TROSY provides a resonance for each NH group in arginine kinase, there is little to no information as to which resonances arise from which residues in the enzyme. The process of determining which resonances in the 2D [15N, 1H]-TROSY correspond to which NH groups in the protein is termed resonance assignment and is the foundation of any NMR-based investigation of proteins. Interpretation of the relaxation or titration data discussed later would be impossible without this initial step of resonance assignment. As mentioned above, there is not enough information in the backbone amide group chemical shifts to unambiguously assign them. To resolve this, additional

Figure 5: 2D [15N, 1H]-TROSY of 15N-arginine arginine kinase. This molecule has 15N incorporated only at arginine sites. All 17 expected arginines are shown with assignments. Boxed resonances indicate those which are absent in the initial triple labeled enzyme. These resonances are recovered upon urea induced unfolding and refolding of enzyme (see Discussion). information is added in the form of 13C chemical shifts. The NMR experiments which correlate 13C, 15N, and 1H, termed triple resonance experiments, are recorded as 3- dimensional experiments. Table 1 summarizes the triple resonance experiments performed on arginine kinase and the information ideally obtained from each [121]. Examples of triple resonance data collected on arginine kinase are shown in Figure 4A for a well resolved NH signal in the 2D [15N, 1H]-TROSY and Figure 4B which depicts a single 15N plane of the 3D [13C, 15N, 1H]-HNCACB experiment. Peak picking of 13C resonances was accomplished using a combination of the automated routines built into Sparky [120] and manual inspection. The automated approach generally succeeds in recognizing resolved resonances but sometimes fails to resolve resonances in more crowded regions of spectra. In these cases, it is necessary to manually identify peaks (resonances).

23 Even with extension of spectra into a third dimension, resonance overlap still remains a problem with large proteins. To address this, 2D [15N, 1H]-TROSYs were collected for eight different arginine kinase samples, each expressed with a different isotopically-labeled amino acid type: 15N-cysteine, aspartate, glutamate, lysine, leucine, asparagine, arginine, and valine. Each of these samples is 15N labeled at only one of the amino acid types listed, which ideally results in a 2D [15N, 1H]-TROSY containing resonances only from those residue types. This is a big help in resolving regions of high resonance degeneracy by reducing the complexity (Figure 5, additional examples in Appendix B). In spite of the precautions taken, such as short over-expression times, the aspartate, glutamate, and asparagine specific labels yielded resonances from many other amino acid types, albeit with reduced intensities, due to metabolic conversion of one amino acid type to another in the expression bacterium [116].

Discussion The first step in resonance assignment is the building of connectivities in the resonances of adjacent amino acids, an example of which is shown in Figure 6. Simplistically, the triple resonance experiments generate resonances for different subsets of carbon atoms in the bonding neighborhood of amide groups. If non-overlapped, differences between the triple resonance experiments can be used to assign resonances to specific residues in the primary sequence of arginine kinase. Triple resonance experiments yield resonances for adjacent residues, or searches can be made for pairs sharing some of their resonances, indicating that they might be adjacent. There may be many ambiguities, confounded by overlapped or missing peaks, but searches can be made for sets corresponding to stretches of consecutive amino acids. Through the combination of type-distinctive resonances and connectivities, a start can be made on assigning resonances to stretches of the primary sequence. Computer programs can search for consistent combinations, though full automation for a protein of this size is generally not possible. The process is computer-assisted with “manual” interventions. For arginine kinase, extensive use was made of the Sparky and AutoAssign [120, 125]. The following paragraphs describe the process in greater detail.

24 While, in theory, sufficient data for resonance assignment would be provided by the 3D [13C, 15N, 1H]-HNCACB and 3D [13C, 15N, 1H]-HNcoCACB pair of experiments alone, the other triple resonance experiments help greatly in resolving degenerate 13C resonances. Taking the 3D [13C, 15N, 1H]-HNCACB and 3D [13C, 15N, 1H]-HNcoCACB data together for any given NH spin system, the 13C resonances belonging to an arbitrary residue number i can be resolved from the 13C resonances belonging to residue number i- 13 15 1 13 1, as the 3D [ C, N, H]-HNcoCACB only contains C resonances arising from Cα and

Cβ of residue number i-1. One can then use this information to extend the chain in either direction: to find residue number i+1, the 3D [13C, 15N, 1H]-HNcoCACB can be searched 13 15 1 for the Cα and Cβ resonances of residue i; to find residue i-2, the 3D [ C, N, H]-

HNCACB can be searched for the Cα and Cβ resonances of residue i-1. These chains, or connectivities, end at prolines, as prolines do not have a backbone amide and thus no resonance in the 2D [15N, 1H]-TROSY.

Figure 6: Strips of the 3D [13C, 15N, 1H]-HNCACB experiment showing 13C connectivities for

residues T32-T49 with lines. Cα resonances are colored black and Cβ resonances are colored red.

25 These connectivities link resonances in the 2D [15N, 1H]-TROSY based on the order in which the corresponding backbone amides appear in the primary structure of arginine kinase, but do not necessarily unambiguously assign residue numbers to the NH spin systems. This is done by recognizing patters in the 13C

chemical shift of Cβ of some amino acid types. Shown in Figure 7, alanines can be recognized by the

large upfield shift of Cβ, typically around 20 ppm. Conversely, serines and threonines are recognized by the

large downfield shift of Cβ, usually around 70 ppm. This feature can also occasionally be troublesome as this

shift of Cβ puts it, in terms of

chemical shift, in the vicinity of Cα and overlap of resonances arising from these two nuclei, which have intensities of opposite sign, results in cancellation in experiments detecting

both Cα and Cβ. Finally, glycines can

be easily recognized as they lack Cβ. 2D [15N, 1H]-TROSYs of amino acid type specific labels also assist in providing information about the type of amino acid a given NH spin

system may belong to, but not residue Figure 7: Strips of the 3D [13C, 15N, 1H]- number. HNCACB experiment depicting Cβ chemical shift patterns (blue) for an example glycine,

Initial connectivities were alanine, and threonine. Cβ resonances are for these residue types are boxed. Note the built and assignments made using absence of a Cβ resonance for glycine.

26 AutoAssign [125], which yielded assignments for approximately 15% of all assignable residues. High resonance degeneracy ultimately defeated automated assignment routines and it became necessary to manually build connectivities. Combining all of the triple resonance experiments, the amino acid type specific experiments, and the initial assignments generated by AutoAssign [125] allowed for manual extension of backbone amide resonance assignments to approximately 290 of 344 assignable, non-proline residues. In terms of software, both AutoAssign [125] and SmartNotebook [126] were explored, but the former was chosen due to its ease of use and its interface with Sparky [120]. An explanation of why approximately 50 residues remained unassigned was not evident at this point. Compounding the issue was the presence of ‘additional’ resonances in 2D [15N, 1H]-TROSYs of amino acid type specific labeled arginine kinase. These resonances, outlined with boxes in Figure 5, were not present in the 2D [15N, 1H]-TROSY of triple labeled arginine kinase. These enigmas remained unexplained until the then partial resonance assignment was mapped onto the substrate-free crystal structure of arginine kinase. Most of the surface of the enzyme had been assigned, but the interior core, which is composed primarily of a β-sheet, and a C-terminal α-helix (residues E335-E353) were largely unassigned. We hypothesized that the back-exchange of amide deuterons with solvent protons during purification had been incomplete for these ~50 residues, due to these deuterons being ‘locked’ within hydrogen bonds. Deuteration of non-labile proton sites 2 was achieved by expression of arginine kinase in 100% H2O, which also initially results in all labile proton sites being deuterated. It was expected that back-exchange of these labile deuterons with protons would occur during purification of the enzyme, which occurs in 100% H2O. This back-exchange is critical, as all of the NMR experiments presented here are detected via the amide proton and substitution of this proton with 2H produces no NMR signal at the sampled 1H frequency. This hypothesis of incomplete back-exchange of amide deuterons with protons would explain both the absence of signals arising from amide groups in the core of arginine kinase in the 2D [15N, 1H]-TROSY of triple labeled enzyme and the presence of seemingly additional resonances in the 2D [15N, 1H]-TROSYs of amino acid type specific

27 labeled enzyme. In the triple labeled enzyme, amide groups of the non-exchanging core region were deuterated and thus yielded no signal in any of the NMR experiments, which were 1H detected. These same amides, however, are not deuterated in experiments with amino acid type specific labels, as deuteration is only necessary when 13C chemical shifts are measured. Thus, resonances were seen with amino acid type specific labels that had not been present in the spectra of triple labeled enzyme. Detection of the core resonances in the triple labeled experiments was required to complete the resonance assignment. To allow this, solvent back-exchange was performed in the unfolded state, with refolding prior to NMR spectroscopy. A second triple labeled arginine kinase sample was expressed in the same manner as the first. After the first purification step, DEAE anion exchange chromatography, fractions containing arginine kinase were pooled and denatured in 6M urea. Fortunately, a protocol for a urea-based refolding of a slightly different arginine kinase expression construct had been developed and optimized by a former lab member, Dr. Genfa Zhou, for expression and purification of arginine kinase for x-ray crystallography [122]. This protocol, which involves sequential dialysis of the unfolded enzyme into decreasing concentrations of urea, typically results in an approximately 25% reduction in yield of purified enzyme. In spite of this, the new triple labeled sample was nearly 1 mM. A similar suite of triple resonance experiments was performed on the new triple labeled arginine kinase. A comparison of both the 2D [15N, 1H]-TROSY and 3D [13C, 15N, 1H]-HNCACB for both the non-refolded and refolded arginine kinase is shown in Figure 8. The appearance of new resonances in both the two- and three-dimensional experiments confirmed the hypothesis that incomplete back-exchange of amide deuterons was indeed frustrating resonance assignment. No major chemical shift changes were detected in other resonances, implying that the refolding process does not have an impact upon the structure of arginine kinase. Interestingly, a 2D [15N, 1H]-TROSY collected on an earlier labeled sample (that had not been refolded), approximately a year after purification, does not show appearance of resonances from the core β-sheet and C- terminal α-helix, implying an extremely low rate of exchange of these amide deuterons. With resonances for the core residues available, backbone amide resonance assignment was extended to 329 of 344 total assignable residues. Assignments for V2,

Figure 8: Impact of arginine kinase refolding upon deuterium back-exchange. (Left) A comparison of the 2D [15N, 1H]-TROSY obtained without refolding (left panel) and after refolding (right panel). Boxes indicate the clear appearance of additional residues V125, C127, V220, and N223, all of which are located in the β-sheet core of arginine kinase. Additional examples are shown in Appendix B. (Right) Side-by-side comparison of 3D [13C, 15N, 1H]-HNCACB strips of the R124-V125 dipeptide obtained with and without refolding. The near complete absence of resonances in the non-refolded sample prevented assignment of these and other residues in the core of arginine kinase. L61, Y203, W204, E225, D226, T273, L275, T278, E341-D344, E348, and M349 were not determined. A number of these lie within the C-terminal α-helix described above (residues E335-E353), possibly indicating that unfolding is inadequate to allow for back- exchange in an α-helix that might be stable even in 6M urea. Of 357 total residues, 348 have Cα and Cβ resonance assignments with P100, Y203, W204, E225, P272, E341-

Q343, and E348 undetermined. Secondary structure was predicted from Cα and Cβ chemical shifts using the chemical shift index [127, 128] and the results, along with short range 1HN-1HN NOE patterns, are consistent with the substrate-free crystal structure of arginine kinase [17]. Thus we were able to take advantage of a pre-existing structure to validate the resonance assignment. It may seem ironic that so much effort has gone into the resonance assignment which is often one of the limiting steps in NMR structure

29 determination, but here the structure was already known. It is emphasized that this NMR study is not directed towards structure determination, but towards elucidation of the dynamics (covered in the following chapters) – for which the resonance assignment is equally critical. Chemical shift assignments were deposited in the BioMagResBank under accession number BMRB-6542 and are listed in Appendix B. Completion of the assignment provided some unique opportunities that there was no right to expect. On submission, arginine kinase was the 5th largest protein chain to have been near fully assigned. Combined with the availability of high resolution crystal structures of substrate-free and transition state forms, the stage was set for dynamics characterization of an enzyme of size and characteristics more typical of metabolic enzymes than the model systems previously amenable to such studies.

30 3. SLOW, MAIN-CHAIN DYNAMICS OF ARGININE KINASE

The dynamics associated with proteins can span a wide range of timescales, from femtoseconds to seconds, and beyond. A diverse set of experimental and computational techniques have been developed to probe different regions of this spectrum of timescales. Dynamics associated with enzyme catalysis are typically on the milli- to microsecond timescale. NMR provides a powerful approach, transverse relaxation dispersion experiments, to measure these dynamics for, in ideal cases, every residue in a protein. The crystal structures of substrate-free and transition state analog bound arginine kinase clearly imply large conformational changes associated with substrate binding [17, 18] which may be rate-limiting upon catalysis. The crystal structures, however, are static ‘snapshots’ and provide no information about the timescales of these motions. Presented here are 15N transverse relaxation dispersion experiments which probe individual residues for micro- to millisecond timescale dynamics and compliment the information obtained from crystallography. These experiments pinpoint residues undergoing exchange on this timescale and can provide rates of exchange and relative populations of conformers [44]. Relaxation dispersion experiments exploit the dependence of transverse relaxation 15 (R2) on the effective B1 field strength of the CPMG refocusing delays. For those N 0 spins that experience conformational exchange broadening, the measured R2 = R2 + Rex, 0 where R2 is the relaxation rate constant in the absence of exchange and Rex is the exchange contribution. It is this Rex term which is directly related to the rate of exchange and relative conformer populations [44]. 15 In the work presented here, individual N R2 values are measured as a function of effective CPMG field strength at three static magnetic field strengths and 25 oC. These experiments necessitate expression and purification of double-labeled (15N and 2H) arginine kinase. Due to incorporation of deuterium, unfolding and refolding of the enzyme is required to allow for back-exchange of initially deuterated amides in the core of arginine kinase with protons in solvent. Use of multiple static fields has been shown to be a requirement for accurate determination and interpretation of relaxation dispersion measurements due to the colinearity of fitted parameters [129, 130]. Of amino acid residues with assigned and non-overlapped backbone amide resonances, 37 show

31 significant exchange (Rex) contributions to transverse relaxation (R2) which cluster in regions of primary structure – mainly at hinge regions of domain motion and within loops. Of special interesting is a cluster of residues, I182-G209, undergoing -1 conformational exchange with a total rate constant (kex) of approximately 800 sec – commensurate with the turnover rate of arginine kinase and possibly a rate limiting motion.

thiamine and 0.001% FeCl3 [116, 117]. Refolding also followed published protocols detailed in appendix A. Purified enzyme was pooled and concentrated in NMR buffer 2 o (10 mM citric acid, 0.5 mM DTT, 50 mM KCl, 50 μM NaN3, 10% H2O, pH=6.5, 4 C). NMR spectroscopy Relaxation dispersion experiments were recorded at 25 oC on Varian INOVA600 (National High Magnetic Field Laboratory, Tallahassee, FL; University of Utah, Salt Lake City, UT), INOVA720 (National High Magnetic Field Laboratory, Tallahassee, FL), and INOVA800 (University of Colorado, Boulder, CO) spectrometers, operating at proton frequencies of 600, 720, and 800 MHz, respectively, and equipped with triple resonance pulsed field gradient probes. In all cases, 1H chemical shifts were referenced to the DSS methyl proton at 0 ppm and 15N and 13C chemical shifts were referenced indirectly [118]. All NMR data were processed with Felix [119] and analyzed with Sparky [120] and in-house software programs. 15 eff Effective N transverse relaxation rates (R2 ) were measured via a TROSY optimized CPMG pulse sequence [131] at three static field strengths (600, 720, and 800 15 MHz). Experimental parameters were as follows: at 600 MHz, N; t1max = 70 ms, sweep width = 46 ppm, 1H; acquisition time = 85 ms, spectral width = 20 ppm. A total of 8

transients were collected for each t1 point with a recycle delay of 3 seconds. At 720

32 15 1 MHz, N; t1max = 54 ms, sweep width = 46 ppm, H; acquisition time = 75 ms, spectral

width = 19 ppm. A total of 16 transients were collected for each t1 point with a recycle 15 1 delay of 1.9 seconds. At 800 MHz, N; t1max = 48 ms, sweep width = 46 ppm, H; acquisition time = 68 ms, spectral width = 19 ppm. A total of 16 transients were

collected for each t1 point with a recycle delay of 1.9 seconds. In all cases, the final data matrices were processed to 1024 (15N) x 1024 (1H) points. eff R2 was measured as a function of effective field generated through a series of eff inversion pulses during the CPMG block. At 600 MHz, R2 was measured with effective field strengths of 0, 25, 50*, 100, 200, 250, 300, 400, 500, 625, 750, 875, and eff 1000 Hz during a total relaxation period of 40 ms. At 720 and 800 MHz, R2 was measured with effective field strengths of 0*, 31.25, 62.5, 93.75, 125*, 156.25, 187.5, 250, 375, 500*, 625*, 750, 875, and 1000* Hz during a total relaxation period of 32 ms. Effective fields marked with asterisks denote those which were measured in duplicate. Data analysis eff For each assigned residue, transverse relaxation rate constants (R2 ) were determined from two-point exponential fits:

eff R2 = (− /1 τ relax )ln(I / I 0 ) (4)

where τrelax is the total relaxation period in seconds, I is the intensity of the corresponding

resonance at any given effective field strength, and I0 is the intensity of the resonance in the absence of the CPMG block. Dispersion profiles were fit via non-linear least squares fitting to the generalized Carver-Richards equation, assuming a two state model and fast exchange [90, 132]:

eff 0 R2 /1( τ CPMG ) = R2 + Rex (1)

2 Rex /1( τ CPMG ) = ( p A pB Δω / kex 1)[ − tanh(kex 8/ υCPMG /() kex 8/ υCPMG )] (3) eff 15 0 where R2 is the effective N transverse relaxation rate, R2 is the relaxation rate in the

absence of conformational exchange, Rex is the contribution to transverse relaxation due to conformational exchange, νCPMG is the effective field strength, τCPMG is the time

between successive inversion pulses in the CPMG pulse block, pA and pB are the populations of the two states, Δω is the chemical shift difference between the two states,

and kex is the sum of forward and reverse rate constants describing exchange between the

33 two states [108, 109]. Fitting was performed using software generously provided by Dr. Lewis Kay [133, 134].

Results 15 eff N transverse relaxation dispersion profiles, or plots of R2 as a function of

νCPMG, were generated for all non-overlapping NH resonances. A subset of these is shown in Figure 9, including residues both with and without Rex contributions to R2. eff Analysis of measured R2 values as a function of νCPMG reveals 37 non-degenerate residues with Rex contributions of 2 Hz or greater to R2, a commonly used cutoff in the literature [110], indicating at least 10% of the residues in arginine kinase experience milli- to micro-second timescale dynamics. Degenerate residues (those with overlapping resonances in the TROSY spectrum) are not included in the analysis due to the large errors associated with extracting the associated resonance intensities. Assuming a two-state model of conformational exchange and fast exchange on the chemical shift timescale (kex > Δω), the exchange contribution (Rex) to transverse relaxation, as a function of the CPMG pulse sequence time constant (τCPMG) is given by Equation 3. This equation was fit to the dispersion profiles measured for each of these residues to obtain relative populations of each state – pA and pB; the rate of exchange between the two states – kex; and the chemical shift difference between the two states – -1 Δω, where τCPMG = (4νCPMG) [131, 135-140]. Table 2 summarizes fitted parameters obtained for each of these residues and relaxation curves derived from fitted parameters are shown in Figure 9 for selected residues. The amino acid sequence of these segments is shown in Figure 11. A number of the residues fit individually exhibit quite large errors in fitted parameters. While these amide signals qualitatively show Rex contributions to R2, large 0 errors are likely a result of small Rex values relative to R2 and/or an ill-conditioning of the fit itself. The latter may result from co-linearity of parameters which remains unresolved even with three static magnetic field measurements. This can potentially be addressed by fitting multiple residues simultaneously, described below [90].

34 Table 2: Summary of exchange parameters obtained from fitting of equation 1 to 15N transverse relaxation dispersion profiles of individual residues. DynDom location refers to the dynamic domain to which a residue belongs. Residues for which fitting did not converge are marked with asterisks.

DynDom -1 Residue kex (sec ) pB (%) |Δω| (ppm) Location

D71 Domain 1 * * * D88 Domain 1 3182.7 ± 238.3 0.3 ± 0.1 1.9 ± 0.3 H90 Domain 1 1022.9 ± 477.5 0.4 ± 0.1 4.5 ± 0.5 G92 Domain 1 1564.3 ± 763.8 0.3 ± 0.1 5.1 ± 0.6

R126 Fixed-Domain 1 Hinge 692.2 ± 219.0 0.3 ± 0.1 2.9 ± 0.3 C127 Fixed-Domain 1 Hinge 943.2 ± 548.3 0.2 ± 0.1 3.7 ± 0.6 R129 Fixed-Domain 1 Hinge 945.5 ± 449.4 0.3 ± 0.1 5.6 ± 0.4 N137 Fixed-Domain 1 Hinge 1153.9 ± 158.6 1.9 ± 0.7 0.9 ± 0.6

S174 Domain 2 3119.1 ± 643.6 0.2 ± 0.1 4.7 ± 0.7 I182 Domain 2 704.1 ± 422.9 0.5 ± 0.2 4.5 ± 0.4 D183 Domain 2 * * * D184 Domain 2 2725.9 ± 1762.9 0.5 ± 1.3 3.1 ± 4.5 H185 Domain 2 1811.0 ± 649.3 0.3 ± 0.1 5.1 ± 0.6 E190 Domain 2 987.6 ± 73.1 4.5 ± 0.6 1.6 ± 0.1 G191 Domain 2 * * *

D192 Domain 2 761.4 ± 87.7 1.7 ± 0.4 1.3 ± 0.2 R193 Domain 2 1471.7 ± 390.5 0.5 ± 0.1 4.4 ± 0.4 T197 Domain 2 3664.3 ± 1360.0 0.5 ± 0.1 6.8 ± 1.3 A198 Domain 2 4194.7 ± 1158.6 100.0 ± 1.2 2.6 ± 1.6 A200 Domain 2 1609.9 ± 436.6 0.7 ± 0.1 4.6 ± 0.5 C201 Domain 2 507.7 ± 230.0 1.3 ± 0.1 1.9 ± 0.3 R202 Domain 2 1296.3 ± 216.9 0.0 ± 0.0 0.9 ± 0.2 T206 Domain 2 565.6 ± 50.8 2.6 ± 0.2 1.7 ± 0.1 G207 Domain 2 1347.9 ± 144.3 0.0 ± 0.0 0.8 ± 0.1 R208 Domain 2 921.5 ± 180.0 0.6 ± 0.1 3.8 ± 0.2 G209 Domain 2 1445.5 ± 375.4 0.7 ± 0.2 3.3 ± 0.6

V220 Fixed-Domain 1 Hinge 2359.6 ± 214.0 1.0 ± 0.1 1.3 ± 0.1 V222 Fixed-Domain 1 Hinge 4405.2 ± 1065.9 0.3 ± 0.1 29.0 ± 3.2

35 Table 2, continued

DynDom -1 Residue kex (sec ) pB (%) |Δω| (ppm) Location

E224 Fixed-Domain 1 Hinge 1138.6 ± 648.1 0.5 ± 1.4 1.5 ± 2.2 R229 Fixed-Domain 1 Hinge 361.3 ± 350.3 0.3 ± 0.2 2.5 ± 0.4 Q234 Fixed-Domain 1 Hinge * * *

F270 Fixed-Domain 1 Hinge 2826.3 ± 233.0 99.1 ± 0.8 2.3 ± 0.5 C271 Fixed-Domain 1 Hinge * * * N274 Fixed-Domain 1 Hinge 1103.8 ± 712.6 0.6 ± 0.1 3.6 ± 0.7 G276 Fixed-Domain 1 Hinge 1932.7 ± 339.3 1.4 ± 0.4 3.0 ± 0.6 V283 Fixed-Domain 1 Hinge 1199.4 ± 675.6 0.6 ± 0.7 1.7 ± 1.1

G332 Fixed Domain 1328.2 ± 323.1 1.5 ± 2.1 1.5 ± 1.0

36 Table 3: Summary of exchange parameters obtained from fitting of equation 1 to 15N transverse relaxation dispersion profiles of groups of residues representing potentially collective motions.

Each group assumes a single kex and pB value and Δω values are determined for each residue. -1 Cluster kex (sec ) pB (%) |Δω| (ppm)

D88 3.2 ± 0.3

H90 1925.2 ± 353.1 0.4 ± 0.1 4.4 ± 0.6 G92 3.4 ± 0.4 R126 2.4 ± 0.4 C127 2.1 ± 2.4 950.1 ± 186.7 0.3 ± 0.1 R129 5.6 ± 0.2 N137 3.7 ± 17.5 I182 0.8 ± 0.4 D184 0.6 ± 0.3 H185 0.8 ± 0.4 E190 2.4 ± 0.8 D192 1.0 ± 0.2 R193 1.0 ± 0.5 T197 1.1 ± 0.9 A198 787.6 ± 51.2 2.6 ± 0.5 0.7 ± 1.9 A200 1.3 ± 0.7 C201 1.2 ± 0.1 R202 0.8 ± 0.6 T206 1.7 ± 0.2 G207 0.7 ± 0.3 R208 1.1 ± 0.1 G209 1.1 ± 0.2 F270 2.4 ± 0.4

N274 2170.5 ± 250.0 1.6 ± 0.5 1.8 ± 0.3 G276 2.9 ± 0.5

37 38

Figure 9: 15N transverse relaxation dispersion profiles obtained for residues in substrate-free arginine kinase. Shown for each residue are data collected at static fields of 600 MHz (red circles), 720 MHz (green squares), and 800 MHz (blue triangles). Curves correspond to exchange parameters obtained from individually fitting each profile to equation 1. L31 and T316 are shown as motionless controls.

Figure 10: Collective motions in substrate-free arginine kinase. Shown for each residue are data collected at static fields of 600 MHz (red circles), 720 MHz (green squares), and 800 MHz (blue triangles). Curves correspond to exchange parameters obtained from joint fitting of each residue in the clusters listed in Table 3.

The parameters obtained from the fitting described above are on a per-residue basis and assume completely independent dynamics for each residue. Most of the residues observed to be involved in slow conformational exchange cluster together in terms of primary sequence, shown in Figure 12. Thus, Equation 3 can be fit to each of the residues in a cluster simultaneously, implying a collective motion of these residues and assuming a single kex and pB value for each residue in a cluster. Where this is appropriate, the increased amount of data solves the ill-conditioning of fitting individual residues, resulting in more robustly fit parameters with lower error (as estimated from the least-squares variance-covariance matrix). Note that some of the residues that could not be fit individually could be included within group fits. Table 3 summarizes fitted parameters obtained for each of these collective fits and curves resulting from jointly fit exchange parameters are depicted for selected residues in Figure 10. Attempts at fitting residues V220-Q234 collectively did not converge.

Figure 11: Amino acid composition of segments fit collectively. Residues colored red indicate those -1 -1 with Rex contributions to R2 > 2 sec , black residues indicate those with Rex < 2 sec , and grey residues indicate those unable to be analyzed, either due to degeneracy or lack of assignment.

Discussion Large conformational changes have been known to be associated with substrate binding in both arginine kinase and creatine kinase by comparison of x-ray crystal structures [17, 18, 141, 142]. Arginine kinase crystal structures show hinged rotations of three ‘dynamic domains’ with respect to a fourth, fixed domain and loop reconfigurations within these domains [17-20]. B-factor analysis of these structures implicates a number of regions with local dynamics [17, 18]. With recent advances in relaxation dispersion analysis, NMR has become a powerful tool for measuring micro- to millisecond timescale dynamics in enzymes [44, 143].

40 15N transverse relaxation dispersion experiments pinpoint a number of residues in substrate-free arginine kinase involved in slow, conformational exchange and a number of these residues cluster in primary sequence, shown in Figure 12. The majority of these residues are in loops or hinge regions about which domains were shown to rotate [17,

18]. Fitting of Equation 3 to individual relaxation dispersion profiles yields kex values spanning an order of magnitude, ranging from 500 to 4000 sec-1. High levels of noise and/or small Rex contributions to R2 likely cause fitting of exchange parameters to relaxation dispersion profiles to fail. Collective fitting of the residues associated with the five segments of the arginine kinase sequence shown in Table 1 failed for the V220-Q234 cluster, likely a result of small Rex contributions to R2 for the residues included, which might also be the cause of relatively large errors associated with fitted parameters for the individual residues. The remaining four clusters belong to loops (D88-G92 and I182-G209) or hinges (R126-N137 and F270-G276) in substrate-free arginine kinase [17, 18]. Interpretation of the D88-G92, R126-N137, and F270-G276 segments is complicated by the limited number of residues included in the collective fit. Including additional residues, which would ideally improve statistics and strengthen any arguments based on collective motions of these individual segments, is currently not possible due to high levels of resonance degeneracy. Furthermore, fitted populations of less than 1% are typically considered unreliable, as conformers with populations lower than this are inaccessible to relaxation dispersion experiments [110]. With these caveats in mind, pinpointing of these two hinge segments by 15N transverse relaxation dispersion experiments might reflect intrinsic, rigid-body motions of dynamic domains about these segments [17-20]. These motions can be thought of as a ‘breathing’ of these domains. Such a breathing motion has been observed in a number of multi-domain enzymes and has, in some cases, been found to be critical to function [144]. The loop spanning residues I182-G209 is a part of dynamic domain 2. A hinge motion upon substrate binding rotates this domain by approximately 18o. This loop is one of two which was observed to close a 10Å entrance to the nucleotide binding site of arginine kinase as the purine ring of substrate nucleotide stacks between the side chains of residues H185 and H284 [17, 18].

Figure 12: Conformational exchange in substrate-free arginine kinase. (A) Residues observed to have Rex contributions to R2 colored (red) mapped onto the substrate-free crystal structure of arginine kinase, along with unassigned residues (grey). (B) Close-up of boxed-in area, showing the -1 I182-G209 loop in detail. Residues colored red represent those with Rex contributions to R2 > sec , -1 black residues represent those with Rex < 2 sec , and grey residues are degenerate or unassigned.

42 The presence of milli-second timescale dynamics in this loop suggest that at least a part of the conformational changes seen upon substrate binding are intrinsic to substrate-free arginine kinase. B-factors observed in the substrate-free crystal structure of arginine kinase are consistent with this and elevated in this region to nearly twice that of the backbone N average value, while those observed in the transition state analog structure are roughly equal to the average value [17, 18]. The rate of collective interconversion between the two assumed states, approximately 800 sec-1 and relative populations of approximately 97.5% and 2.5% corresponds to individual exchange rates of ~20 sec-1 and 780 sec-1. These rates, which may reflect ‘opening’ and ‘closing’ of this loop, are commensurate with enzymatic turnover rates of ~135 sec-1 [12]. Note, however, that these rates are ambiguous – at this point, it cannot be determined which rate is associated with ‘opening’ and ‘closing.’ It is, however, tempting to speculate that one of these rates reflects the loop opening rate constant which would track with product release as the rate limiting step of this reaction. -1 The similarity of kex values between the R126-N137 (950.1 ± 186.7 sec ) and I182-G209 (787.6 ± 51.2 sec-1) regions suggest the possibility of a coupled motion between them. Joint fitting of these regions, however, is unstable, with parameters being -1 kex = 1270.0 ± 49.0 sec and pB = 96.6 ± 1.7%. In fact, when residues from the I182- G209 are sequentially omitted from the fit, the resulting population approaches 50 ± 300%. The instability of these refinements may result from the unreliably small fitted nd populations of the R126-N137 region. Note that the population of the 2 state (pB; R126-N137; Table 3) is lower than is considered a reliable indicator of a second state (see above), so perhaps it is not surprising that fitting is not consistent with the results of I182-G209. Crystal structures of arginine kinase show that the motion of this loop is concatenated with the 18o rotation of dynamic domain 2 [17, 18]. Relaxation dispersion experiments provide an opportunity to explore which of these motions, if any, are dominant. The hinge about which dynamic domain 2 rotates is comprised of residues L163-P169 [17] and one might expect these residues to exhibit relaxation dispersion if a domain rotation were present. Of these 7 residues, all but P169 are assigned and the remaining 6 residues exhibit no Rex contributions to R2, indicating that rotation of

43 dynamic domain 2 [17] is either not present or beyond the limits of detection of these experiments. Care must be taken; however, due to the usual caveats of interpreting negative results and basing the interpretation of a ~50 residue domain on only 6 residues may be naïve. Recently developed experiments based on residual dipolar couplings are capable of probing domain motions such as this on a slightly different timescale [145]. Taken together, these data suggest that at least some of the conformational changes observed in arginine kinase crystal structures, the motion of the loop containing H185, are, at least in part, intrinsic to the enzyme and not completely ligand gated [12, 17, 18]. Normal mode analyses on citrate synthase, for example, suggest that intrinsic motions in enzymes follow normal modes and that these are exploited in larger, substrate induced changes [102]. Extending this to arginine kinase, one can envision the intrinsic motions detected via transverse relaxation dispersion may be in a similar direction as those observed in the crystal structures [17, 18] but of smaller amplitudes [102]. In addition to the presence of intrinsic dynamics in this loop, exchange rates similar to turnover rates indicate that this motion may be rate-limiting upon enzyme turnover [12]. Enzymes typically have turnover rates that are slower than the chemical steps [146] and it has long been purported that conformational changes may be rate- limiting upon arginine kinase and other phosphagen kinases [147]. The work here potentially provides a quantitative link between turnover rates and rates of motions. Ideally, |Δω| encodes structural differences between conformers explored in substrate-free enzyme. Similarly, Δδ values obtained from substrate titrations (described in Chapter 4) describe conformational changes associated with substrate binding. Comparison of these values could provide an opportunity to explore the similarity of these conformational changes. One caveat here is that chemical shift perturbations (Δδ) arise from both conformational change and proximity to substrate. This is important, as many residues in the I182-G209 loop are in close proximity to substrate. A poor correlation is observed between |Δω| and Δδ values for residues in the I182-G209 loop that are farther away from substrate binding sited than 5-6 Å. Elimination of residues within a 5-6 Å sphere is a crude way of excluding residues whose Δδ values might be more influenced by direct interaction with substrate, rather than by protein conformational change. Lack of correlation in residues outside of this might be

44 construed to indicate that the alternate conformation of this loop exhibited within the intrinsic motions of substrate-free arginine kinase may not structurally resemble the conformation adopted in each of the binary complexes. One must be cautious, however, as the errors associated with |Δω|, shown in Table 3, are quite large and the structural impacts of substrate proximity may extend well beyond a 5 Å sphere. Evidence points to the presence of dynamics in the creatine kinase equivalent of the arginine kinase I182-G209 loop, which is highly conserved across the phosphagen kinases [10, 148, 149]. X-ray crystal structures of substrate-free creatine kinase [141] and transition state analog bound creatine kinase [142] show B-factors of backbone N atoms elevated above the mean in the substrate-free structure and near the mean in the substrate-bound structure, which is the identical pattern seen in arginine kinase crystal structures [17, 18]. Furthermore, hydrogen/deuterium exchange studies, which probe sub-second timescale dynamics, indicate the presence of dynamics in the creatine kinase equivalent of the arginine kinase I182-G209 loop in the absence of substrate [77, 80]. These correlations between arginine kinase and creatine kinase suggest that the phosphagen kinase family of enzymes has evolved not only in structure but also in dynamics. The presence of multi-timescale dynamics in different regions of arginine kinase yields a picture of the enzyme sampling many conformational sub-states in the absence of substrate. Substrates may, in fact, sequester and bind to a subset of these conformational states. This is not a new concept and has, in fact, been present in the literature for decades; studies on myoglobin come to similar conclusions in the 1970s [150, 151]. With the development of NMR transverse relaxation dispersion techniques, intrinsic dynamics have been observed in lysozyme [139, 152], cyclophillin A [93], RNase A [91], pin1 [92] and a number of other enzymes [44]. It is now the interplay between these dynamics and enzymatic catalysis which will provide intriguing insights into how enzymes may achieve catalysis.

45 4. SUBSTRATE INDUCED CHANGES IN ARGININE KINASE

Comparison of X-ray crystal structures of substrate-free and transition state analog bound arginine kinase suggest large conformational changes associated with substrate binding [17, 18]. These structures provide the overall conformational changes of a multi-step catalytic cycle, but do not describe changes induced by binding of individual substrates. Through substrate titrations monitored by nuclear magnetic resonance spectroscopy, these conformational changes have been segregated into those induced by each substrate in the random order mechanism of arginine kinase by tracking chemical shift perturbations observed as a result of substrate binding. Chemical shift perturbations were tracked by collection of 2D [15N, 1H]-TROSYs of 15N enriched arginine kinase as a function of substrate concentration. These titrations suggest that a loop near residue E190 consists of two semi- independent segments which fold over the active site as each substrate binds. Also, changes are seen in a loop near residue V65 as phosphagen binds and a loop near residue V308 as nucleotide binds. These substrate-dependant loop motions may allow the enzyme to prevent wasteful hydrolysis without occluding substrate binding sites. Equilibrium dissociation constants for each complex in an NMR-suitable buffer are also determined and are similar to those obtained via other techniques with the exception of the constant for phosphoarginine, which exhibits substantially weaker binding.

Materials and Methods Sample preparation Limulus polyphemus arginine kinase was expressed and purified in soluble form using previously published protocols [115], detailed in appendix A. The protein was uniformly isotope enriched in 15N by growth in M9 minimal media containing 0.1% 15 ( NH4)2SO4 supplemented with 0.001% thiamine and 0.001% FeCl3 [116, 117]. Purified enzyme was pooled and concentrated in NMR buffer (10 mM citric acid, 0.5 mM DTT, 2 o 50 mM KCl, 50 μM NaN3, 10% H2O, pH=6.5, 4 C). Stocks of substrates to be used as titrants (arginine, phosphoarginine, ADP, ATP, and AMPPNP) were made by dissolving substrate in NMR buffer and adjusting pH to

46 6.5. ATP, ADP, and AMPPNP solutions were prepared with a 0.5-fold excess of MgCl2 to ensure nucleotide binding. NMR spectroscopy 2D [15N, 1H]-TROSYs were performed on a Varian INOVA720 spectrometer operating at a proton frequency of 720 MHz and equipped with a triple resonance pulsed 15 field gradient probe. The following parameters were used: N; t1max = 46.5 ms, sweep width = 75.4 ppm, 1H; acquisition time = 43 ms, spectral width = 16.6 ppm. A total of 4 transients were collected for each t1 point with a recycle delay of 1.2 seconds. Final data matrices were processed to 1024 (15N) x 1024 (1H) points. 1H chemical shifts were referenced to the DSS methyl proton at 0 ppm and 15N and 13C chemical shifts were referenced indirectly [118]. All NMR data were processed with Felix [119] and analyzed with Sparky [120]. Substrate titrations and binding maps Titrations of arginine kinase were performed by collecting 2D [15N,1H]-TROSY spectra, described above, at various substrate:enzyme molar ratios. These range from 0 to 100 molar equivalents for phosphagen titrations and 0 to 10 molar equivalents for nucleotide and AMPPNP titrations. Arginine kinase samples to be titrated with ADP, ATP, or AMPPNP were initially titrated with 3 molar equivalents of Mg+2 in the form of

MgCl2 to ensure nucleotide binding. The chemical shift perturbation describing the change in position of an amide resonance in 2D [15N,1H]-TROSY spectra as a function of substrate concentration was calculated as [153]:

Δδ = (Δδ ) 2 + (Δδ )5.6/ 2 HN N (5) Residues with chemical shift perturbations > 0.05 ppm were included in substrate binding maps. Equilibrium dissociation constants and data fitting Since all NH signals in substrate complexes of arginine kinase are in the fast exchange limit, the equilibrium dissociation constant, KD, of each enzyme-substrate complex was determined by generating binding isotherms of substrate-proximal residues as a function of total substrate concentration. Non-degenerate NH signals from residues within a ~10 Å sphere of the substrate binding site showing Δδ > 0.01 ppm were included

47 for KD determinations. Binding isotherms were fit to the following equation using SigmaPlot (Systat Software, Inc).

Δδ = Δδ [(K + L + E ) − (K + L + E ) 2 − 4L E 2/] E obs max D tot tot D tot tot tot tot tot (6)

Here, for any given resonance, Δδobs is the observed chemical shift difference from the reference state, Δδmax is the maximal difference between the saturated and reference states, KD is the equilibrium dissociation constant for the given complex, Ltot is the total substrate concentration, and Etot is the enzyme concentration. Nonlinear regression was performed by allowing simultaneous refinement of Δδmax and KD and using both Ltot and

Etot as independent variables, thus taking into account the slight dilution of enzyme during titration. For each titration, overall KD values were calculated as error-weighted means of KD values determined for individual residues satisfying criteria described above.

Results Chemical shift mapping is a principal method of identifying the interface of a protein and ligand and to further identify more distant structural and/or dynamic changes. Chemical shift perturbations, Δδs, were calculated for all non-degenerate, assigned resonances in all titrations. Figure 13A depicts representative data obtained from titration of arginine kinase with arginine, showing the quality of data and the ability of resonances to be tracked as a function of arginine concentration. Δδs > 0.05 ppm were detected in 68 residues in the arginine titration, 55 in the phosphoarginine titration, 77 in the ATP titration, and 97 in the ADP titration. In the ternary titration, 22 residues exhibit Δδ > 0.05 ppm upon saturation of enzyme with AMPPNP followed by 70 residues in the subsequent arginine titration. Figures 14 and 15 depict chemical shift perturbations observed upon titration with arginine and ATP in histogram form and mapped onto the crystal structures of arginine kinase [17, 18]. A number of resonances broaden beyond detection during the titration and become untrackable; in fact, many of these are not detectable even in the first titration point. These residues include G64, V65, F136, F137 and L195 in both phosphagen titrations; T123, G172, F270, G276, T277, and M279 in the ATP titration. These residues, plus

Figure 13: Summary of titration data. (A) Region of overlaid 2D [15N,1H]-TROSY spectra obtained during titration of AK with arginine to a concentration of 0 mM (red), 1.2 mM (orange), 6.2 mM

(blue), 57.4 mM (maroon), and 83.0 mM (green). (B) Δδobs values measured for a sample residue, G57, during titration of AK with arginine (blue, circles) and phosphoarginine (red, squares). Curves shown are fits of Equation 6 to data. (C) Plot depicting fractional saturation of AK with arginine as

calculated from Δδobs/Δδmax at each titration point for each of the 15 residues included in KD calculation of the arginine binary complex.

F188, G191, S282, R294, and D324 are broadened in the ADP titration. F270 and G276 are broadened in the AMPPNP titration and V65, G66, and N137 are in the subsequent arginine titration. All of these residues, many of which are involved in direct interactions

with substrates or are part of hinge regions [17, 18], likely have very large Δδmax values, leading to extreme line broadening. No resonances exhibit chemical shift perturbations above the 0.05 ppm threshold

in the control experiment of titrating arginine kinase with 3 molar equivalents of MgCl2, indicating that there are likely no significant backbone conformational changes upon

49 binding of magnesium ions. Also, only 3 of 279 non-degenerate resonances exhibit chemical shift perturbations above 0.05 ppm upon a two-fold increase in enzyme concentration, indicating that protein-protein interactions likely do not contribute to measured chemical shifts. Δδ values are shown as a function of arginine and phosphoarginine substrate concentrations in Figure 13B for a sample residue, G57. Binding isotherms obtained from the arginine titration are shown in Figure 13C. Saturation of enzyme with substrate was gauged in two ways: asymptotic Δδ values with increasing substrate concentration

and comparison of measured Δδmax values to those obtained from fitting titration data to Equation 6 (Figure 13B).

For the calculation of KD values, elimination of residues outside a 10 Å sphere of the substrate binding site and degenerate resonances left 15 residues to be fit for the arginine titration, 16 residues for the phosphoarginine titration, 12 residues for the ATP titration, and 10 residues for the ADP titration. 6 residues were fit for the AMPPNP titration and 14 residues were fit for the subsequent arginine ternary titration.

Overall KD values obtained for nucleotide substrates agree well with previously published work. The NMR derived KD values of 0.26 ± 0.10 mM for ATP and 0.14 ± 0.04 mM for ADP are in close agreement (i.e. within the bounds of quoted errors) with published enzyme kinetics: 0.32 ± 0.01 mM for ATP [12] and 0.10 ± 0.05 mM for ADP

[13]. NMR derived KD values of 0.83 ± 0.09 mM for arginine and 6.61 ± 1.26 mM for phosphoarginine, however, differ from published values of 0.58 ± 0.10 mM obtained from equilibrium dialysis for arginine [154] and 1.4 ± 0.3 mM obtained from enzyme kinetics for phosphoarginine [13]. The KD for arginine calculated from the ternary

titration, 1.19 ± 0.14 mM, which is analogous to KM, also differs from the value obtained from enzyme kinetics, 0.27 ± 0.01 mM [12]. Critical to these comparisons are methods of error estimation, described below in the discussion. Equilibrium dissociation constants obtained for all complexes are summarized below, in Table 4:

50 Table 4: Summary of KD values obtained from substrate titrations of arginine kinase. KD values shown are error weighted means of values obtained for each residue fit. The KD value reported for the AMPPNP:arginine complex describes dissociation of arginine from the ternary complex. -1 Fraction of arginine kinase bound was calculated as (1 + KD / [S]tot) . Complex formed Number of residues KD (mM) Final fraction fit bound (%) Arginine 15 0.83 ± 0.09 99.0

Phosphoarginine 16 6.61 ± 1.26 94.4 ATP 12 0.26 ± 0.10 94.1 ADP 10 0.14 ± 0.04 97.4 AMPPNP 6 0.16 ± 0.05 97.2 AMPPNP:arginine 14 1.19 ± 0.14 98.8 (arg) / 96.9 (AMPPNP)

Discussion Most of the chemical shift changes observed in arginine kinase upon arginine or phosphoarginine binding map to the substrate contact surface of arginine kinase (Figures 14 & 15). Resonances corresponding to segments comprised of residues W221-I230 and T269-V283 exhibit large chemical shift perturbations and both define the binding surface for these substrates and contain residues, including N274 and G276, which were determined by Yousef et al [17] to be hinge residues about which domain motions occur. Chemical shift perturbations in hinge regions may reflect both substrate binding and/or change in conformational environment. Other resonances with chemical shift perturbations in the phosphagen titrations, for the most part, belong to residues in the N-terminal domain. The largest cluster of phosphagen-induced perturbations spans residues T44 through D71 (Figures 14 and 15). This includes the substrate specificity loop, residues L61-Y68, and a substantial stretch of residues N-terminal of this loop, reflecting the secondary structural change of this region from flexible loop to alpha helix seen in the x-ray structures. Only two residues in this loop, G66 and A69, exhibit chemical shift perturbations as a result of nucleotide binding, indicating that the large conformational changes associated with this loop are primarily a result of phosphagen binding [17, 18].

51 Figure 14: Histogram depicting Δδ values observed in arginine (blue bars) and ATP (red bars) titrations. Secondary structure observed in the substrate-free crystal structure of arginine kinase is noted [17]. For ease of comparison, unassigned residues (marked with *), degenerate resonances (marked with +), and untrackable resonances (marked with -) have been assigned Δδ values of 0 ppm.

52 Resonances corresponding to residues R126-L140, with side chains ranging from 6Å to over 15Å away from substrate phosphagen also exhibit large phosphagen-induced chemical shift perturbations and are thought to form the hinge about which the small, N- terminal domain of arginine kinase rotates [17, 18]. Similar chemical shift perturbation patterns for this region are not seen in the ATP/ADP titrations, indicating that binding of phosphagen is responsible for the hinge rotation of this domain. Another region exhibiting phosphagen-induced chemical shift perturbations spans residues E190-C201 (Figures 14 and 15). In the crystal structures of arginine kinase, a salt bridge is seen between R193 and D62, which is thought to stabilize the conformation of the substrate specificity loop [17, 18, 23, 155]. Interestingly, a segment of residues adjacent to E190- C201 exhibits chemical shift perturbations as a result of nucleotide binding (see below). Differences between the chemical shift perturbations detected in the arginine and phosphoarginine titrations are minimal and occur primarily in regions of the enzyme in close vicinity of substrate. Differences are observed in segments S130-C139 and F270- A281, along with V222 and H227, all of which the transition state crystal structure show to be near the guanidinium group of substrate arginine, i.e. proximal to the phosphoryl group. These are likely a reflection of the large electrostatic differences between arginine and phosphoarginine resulting from the phosphate moiety. Many residues in the S130- C139 segment were previously determined to be hinge residues about which the small, N- terminal domain rotates. Differences in arginine and phosphoarginine induced chemical shift perturbations in this region may imply that arginine and phosphoarginine binding elicits a similar, but not identical, rotation of this domain [17, 18]. Differences are also observed in a pair of residues near the substrate specificity loop, Q55 and S56, possibly an indication of subtle differences in the conformation of this loop induced by arginine and phosphoarginine binding. In contrast to the phosphagen titrations, the nucleotide titrations are distinguished by chemical shift perturbations located primarily in the larger, C-terminal domain of arginine kinase and a greater number of perturbations overall (Figures 14 and 15). Chemical shift perturbations arising from residues in close vicinity of substrate nucleotide are seen in S122-R129, H212-W221, I230-G237, and R280-I285, which primarily make up the β-sheet in the core of this C-terminal domain. Residues H212-

53 44-71 loop 182-201 loop

182-201 loop

307-330 loop

Figure 15: Details of substrate titrations. Shown are transition state structures of arginine kinase. The substrate-free structure is shown with high opacity for reference. (A) Binding maps depicting residues, colored red, with Δδ>0.05 ppm for each substrate titration. (B) Close-up of boxed regions in arginine (left) and ATP (right) binding maps. Blue residues denote those which are untrackable due to broadening and unassigned residues are colored grey. (C-E) Details of loops involved in substrate binding. Color coding is as follows: red-residues with Δδ>0.05 ppm in the arginine titration; magenta-residues with Δδ>0.05 ppm in the ATP titration; orange-residues with Δδ>0.05 ppm in both of these titrations; green-residues with Δδ<0.05 ppm; and grey-unassigned residues. (C,E) Loops spanning residues 44-71 and 307-330 exhibit perturbations primarily as a result of arginine and ATP binding, respectively. (D) Binding of arginine and ATP induce changes in two, independent regions in the loop spanning residues 182-201, along with a common, intervening region.

54 W221, comprising two of the β-strands in this sheet, are over 10 Å from the nucleotide binding site, suggesting that nucleotide binding may induce structural changes such as a bending or twisting of the β-sheet. A number of chemical shift perturbations as a result of nucleotide binding are likely due to substrate induced conformational exchange. One such region is defined by residues I182-R193, a segment adjacent to the E190-C201 region which exhibits perturbation upon phosphagen binding (Figure 15). The I182-C201 loop is important to arginine kinase for a number of reasons including stabilizing nucleotide binding through a base-stacking interaction between H185 and substrate nucleotide and formation of a salt bridge between R193 and D62. The latter might stabilize conformational changes in the substrate specificity loop, and/or exclude solvent from a substrate-occupied active site by packing over substrate [17, 18, 23]. The partitioning of the I182-C201 loop into two regions – one exhibiting chemical shift perturbations upon phosphagen binding and the other exhibiting perturbations upon nucleotide binding – implies that folding of this loop over the active site occurs in two steps; one as each substrate binds. Shown in detail in Figure 15D, two distinct regions, I182-K189 and F194-C201, contain residues which exhibit Δδ > 0.05 ppm upon binding of ATP and arginine, respectively, indicating that binding of different substrates impacts these regions specifically. It is difficult to imagine structural changes in this loop being confined to these small regions and the observation of the intervening region, E190-R193, exhibiting chemical shift perturbations in both titrations implies that the structural changes experienced in the two distinct regions are propagated somewhat through the intervening region – the intervening region is ‘dragged along for the ride.’ Chemical shift perturbations are also seen for this intervening region when arginine kinase saturated with AMPPNP binds arginine, suggesting that this intervening region adopts a different conformation in the binary complex with arginine than the cumulative changes seen in the ternary complex. Absence of chemical shift perturbations in the same titration for residues I182-K189, on the other hand, suggest that this region attains a conformation in the ATP binary complex that is similar to that in the ternary complex, and that phosphagen binding does not induce further changes. This complex series of substrate-

55 induced changes could possibly provide the enzyme a method of preventing wasteful hydrolysis by excluding solvent from bound substrate in a binary complex while not occluding the binding site for the other substrate. This theme is apparent in another loop, V308-R330, in which most residues show large perturbations upon nucleotide binding. Residues R309-G320 are absent from the substrate free crystal structure of arginine kinase (and creatine kinase) due to high disorder but can be modeled in the transition state analog structure, implying that substrate binding defines a single conformation for this otherwise flexible loop. Two residues in this loop, R309 and E314, are involved in hydrogen bonding to both substrates [17, 18]. In spite of these interactions, inspection of chemical shift perturbations of non-degenerate resonances implicates only two residues, N327 and R330, in changes associated with formation of the arginine binary complex and three residues, G310, I325, and R330, upon formation of the ternary complex. ATP binding, on the other hand, causes large chemical shift changes in the majority of non-degenerate resonances in this loop, 12 out of 20, including those for N327 and R330. These results indicate that it is binding of nucleotide that induces the conformational changes seen in this loop. Differences in chemical shift perturbations induced by titration of arginine kinase with ADP or ATP occur primarily in the core β-sheet in close vicinity of substrate nucleotide. Differences between the ADP- and ATP-induced chemical shift perturbations can also be detected in residues N327-R330 which are part of a hinge about which the R309-G320 loop, mentioned above, rotates, suggesting that ADP and ATP induce similar, but not identical, changes in these regions [17, 18]. Regions exhibiting Δδ > 0.05 ppm upon titration with AMPPNP are virtually indistinguishable from those seen in the ADP and ATP titrations but perturbation values themselves are different, likely indicating that AMPPNP binds in the same manner as ADP/ATP and induces similar conformational changes. In general, however, Δδ values observed in the AMPPNP titration are smaller than those observed in the ATP titration. In fact, many of these residues exhibit Δδ < 0.05 ppm as a result of titration with AMPPNP, even though saturation of enzyme with substrate analog is likely achieved.

56 Although unclear, differences in chemistry between AMPPNP and ADP/ATP may be the cause for many of the differences in chemical shift perturbations in these titrations. Titration of the arginine kinase:AMPPNP binary complex with arginine yields chemical shift perturbations in the same regions observed when substrate-free enzyme is titrated with arginine, implying that changes associated with phosphagen and nucleotide binding are mostly independent, except for the I182-C201 loop. Comparison of chemical shift perturbations observed in formation of the ternary complex and the arginine kinase:arginine binary complex yields only three residues with ΔΔδ > 0.05 ppm: V125, S282, and I325, all of which are part of or near hinge regions [17, 18]. While Δδ values greater than 0.05 ppm are only observed for two residues in the 190 loop, D184 and E190, upon binding of AMPPNP, formation of the ternary complex with arginine yields chemical shift perturbations greater than 0.05 ppm in all of the same residues observed in the arginine binary complex in this region, with the exception of F194, which has a Δδ of 0.04 ppm. This result further reflects the partitioning of this loop mentioned above, as the residues implicated in folding over substrate arginine, F194-C201, only does so as a result of arginine binding; no chemical shift perturbations are observed in this region as a result of AMPPNP binding. In the absence of crystal structures of binary complexes of arginine kinase, these data can be compared to available structures of creatine kinase. Similar to arginine kinase, there are substrate-free [141, 156] and transition state analog structures [142] of creatine kinase, which is an octamer. The latter structure, however, shows only one monomer in each of the dimers being bound to the transition state analog; the other monomer is bound only to MgADP [142], providing a structure for comparison of the ADP binary complex investigated here by NMR. Changes observed in these crystal structures for the T44-D71 and V308-R330 loops support observed chemical shift perturbations. Virtually no change is seen in the T44-D71 loop when comparing the substrate-free and ADP-bound creatine kinase structures, but large changes (main chain rms difference > 9 Å) are seen between the ADP-bound and transition state structures [141, 142, 156]. Conversely, these crystal structures show large changes in the V308-R330 loop between the substrate-free and

57 ADP-bound structures and smaller changes between the ADP-bound and transition state structure [141, 142]. No change is observed in the I182-C201 loop between the substrate-free and ADP-bound creatine kinase structures while moderate changes (main chain rms difference ~ 3 Å) are seen between the ADP-bound and transition state structures [141, 142, 156]. This may suggest that the chemical shifts for residues in this loop may be influenced more by direct interactions with substrate rather than substrate induced conformational changes. The I182-C201 loop moves a greater distance upon substrate binding in arginine kinase than creatine kinase, which suggests that comparison of chemical shift perturbations observed in this loop with creatine kinase crystal structures may be inappropriate [17, 18, 141, 142, 156]. Crystal structures of binary complexes of arginine kinase will ultimately address this issue. Chemical shift perturbations provide some limited insights into the substrate binding synergy observed in arginine kinase (and other phosphagen kinases), which must be interpreted with caution. Substrate binding synergy, α, is defined as KM/KS. Positive synergy (α < 1), as found in the phosphagen kinases, has classically been interpreted a the binding of one substrate enhancing the binding of another [157]. It should be noted first that synergy is conventionally measured by enzyme kinetics and, thus, is not a direct measure of binding. Rather, positive synergy indicates that as the concentration of one substrate is increased, less of the second substrate is required to achieve ½-maximal rate. This distinction becomes important when the chemical shift perturbations presented here, which are a direct measure of substrate-binding, are considered. A direct measure with real substrates is not possible, because with both substrates present, turnover would occur and the reaction would move to completion. In the data presented here, this is addressed by using a non-hydrolyzable ATP analog, AMPPNP. With the caveat that AMPPNP and its binding to arginine kinase is not exactly ATP (Table 4), we see that binding of arginine is actually weakened, not strengthened, by the presence of AMPPNP, albeit by only a small amount (Table 4). This might suggest that the distinction between direct and kinetic measures of substrate binding may be important. It is possible that observed synergy results from binding-induced conformational changes that enhance catalytic rate, rather than the binding of the other substrate. All interpretations of substrate binding

58 synergy, however, must be treated with caution. In recent years, more authors (see [13, 158, 159], for example) have obtained error estimates for kinetic parameters from nonlinear least-squares fitting of all data (both substrates) simultaneously, rather than from secondary plots of parameters already fit to the data for a first substrate. It is now apparent that errors in measuring synergy are much higher than once assumed, and that differences between enzyme variants, once thought to be important, are perhaps not experimentally significant. The methods by which these errors are determined form the basis by which dissociation constants obtained via NMR can be compared to those obtained from other techniques. Kinetic parameters for arginine and ATP obtained by Blethen [12] by assaying the forward reaction of arginine kinase (production of phosphoarginine) were determined using the outdated method described above which is known to greatly underestimate the errors associated with these parameters. Fitting all data simultaneously typically results in higher, but likely more realistic, error estimates which reflect the reproducibility of individual measurements. Comparison of values obtained using each method clarifies just how inadequate error estimates can be – there is 50% error,

estimated via simultaneous fitting, in the KS for ADP [13] while there is 3% error in the

KS for ATP when determined from secondary plots [12]. The problem is further exacerbated when one compares values obtained by different authors using the

simultaneous fitting approach – the KS for phosphoarginine has been reported as 0.75 ± 0.24 mM [13] and 1.4 ± 0.3 mM [115]. With errors in the literature likely underestimated, one generally looks for order of magnitude agreement when comparing substrate binding parameters. It is with these issues in mind that comparisons between binding constants

obtained from NMR and other methods are made. Comparisons are made to KS values

derived from enzyme kinetics as KS more closely reflects dissociation of the binary

complex, what is measured in the NMR experiments, as opposed to KM. The NMR- derived KD for ATP, 0.26 ± 0.10 mM, is within the error bounds of the value reported by Blethen [12] using enzyme kinetics assaying the forward reaction, 0.32 ± 0.01 mM, even though this error is likely underestimated. Likewise, the NMR-derived KD for ADP, 0.14

± 0.04, is within the error bounds of 0.10 ± 0.05 mM, the KS value determined by enzyme

59 kinetics of the reverse reaction (production of ATP) [13]. These dissociation constants are deemed to be in agreement with published values as they are within published errors.

The KD obtained from NMR for arginine, 0.83 ± 0.09 mM, is only slightly outside the error bounds of the value determined from equilibrium dialysis, 0.58 ± 0.10 mM [154]. Dialysis-based equilibrium constants are not available for all substrate / product complexes, but when they are, they are preferred over “apparent” constants from kinetics, because dialysis, like NMR, offers a “real” dissociation constant. Finally, the NMR-

derived KD for phosphoarginine, 6.61 ± 1.26 mM, is well outside the error bounds of published values obtained from enzyme kinetics: 0.75 ± 0.24 mM [13] and 1.4 ± 0.3 mM [115]. The binding constants for phosphagens, especially phosphoarginine, are not considered to be in agreement with published values as they are outside the errors associated with these values. These results presented here demonstrate that conformational changes associated with substrate binding in arginine kinase occur in a stepwise and, for the most part, independent manner. Chemical shift perturbations can be observed primarily in the N- terminal domain of arginine kinase upon binding of phosphagen and the C-terminal domain upon binding of nucleotide. The striking similarity of the chemical shift perturbations observed upon binding of arginine to a substrate-free and AMPPNP saturated enzyme further supports the idea of independent conformational changes. Binding of substrates was shown to influence three interesting loops. T44-D71, containing the substrate specificity loop, exhibits chemical shift perturbations only as a result of phosphagen binding. Also, chemical shift perturbations are only detected in V308-R330 as a result of nucleotide binding. Finally, the loop comprised of residues I182-C201 appears partitioned into two regions, each influenced by binding of only one substrate. These patterns of conformational changes associated with substrate binding possibly reflect the ability of the enzyme to prevent wasteful hydrolysis of a bound, phosphorylated substrate without occluding the binding site of the other substrate.

60 5. CONCLUSIONS AND FUTURE DIRECTIONS

Employing a unique combination of previously determined crystal structures of arginine kinase and recently developed NMR methods, this work describes the intrinsic dynamics of arginine kinase and dissects the changes associated with binding of individual substrates to the enzyme. This work provides a basis for beginning to understand the role that dynamics plays in the catalysis of arginine kinase. Substrate titrations in conjunction with NMR 2D [15N, 1H]-TROSY experiments have allowed for dissection of the substrate induced changes in arginine kinase. Arginine kinase crystal structures provide changes associated with binding of the transition state analog, but, to date, have provided no information as to changes associated with the binding of each individual substrate. Success in partially characterizing the substrate- induced conformational changes in the solution state (NMR) has provided increased motivation for renewing attempts to characterize the binary structures by x-ray crystallography. Existing data, NMR chemical shift perturbation maps, show that substrate phosphagen and nucleotide induced relatively independent changes in the N- and C-terminal domains, respectively - the domains closest to the respective substrates. Interestingly, there are a number of more distal changes associated with substrate binding. For example, perturbations are observed in the L170-M173 region, located ~20 Å from the active site, upon binding of substrate nucleotide. In light of the relaxation dynamics results (below), perhaps the most interesting result from the NMR titrations is that the N-terminal and C-terminal halves of the I182-C201 loop are influenced separately by binding of nucleotide and phosphagen respectively, with a short overlapping region of three residues where the binding of the two substrates appears to have additive effects. This all suggests that the loop may adopt different conformations in the substrate-free form, the binary complexes, and the turning over enzyme. Interestingly, this is the same loop which exhibits slow conformational exchange in substrate-free enzyme, discussed below. Thus, the conformation of this loop appears to be sensitive to the binding of both substrates. There has been prior speculation that conformational change in phosphoryl transfer reactions is used to limit the catalytic activity to times in the reaction cycle when solvent has been excluded from the active

61 site, and thus a wasteful hydrolytic side reaction minimized [57, 59]. Thus, this loop appears to be a prime candidate for future examination of whether it coordinates a change to a catalytically-competent active site configuration to the binding of both substrates. 15N transverse relaxation dispersion experiments implicate the loop spanning residues I182-G209 as being involved in exchange with a rate of approximately 800 sec-1 in substrate-free arginine kinase. Available crystal structures of arginine kinase show this loop moving over 10 Å to interact with substrate nucleotide [17, 18]. While the conformations monitored by the NMR experiments have not been determined directly, it is likely that one state corresponds to the substrate-free crystal structure. Furthermore, given the agreement between the residues with chemical shift perturbation and those seen to be in different conformation in the transition state analog crystal structure, it is plausible that another state probed by the NMR approximates closely the TSA crystal structure for this loop. It is particularly interesting, then, that the conformational dynamics of this loop are shown by the NMR to be an intrinsic property of the enzyme and not just substrate-induced. It is possible that the ‘excited’ state of the enzyme exhibiting the alternate conformation of this loop, which likely corresponds to the form seen in the transition state analog crystal structure, and which is found by NMR to have a relative population of approximately 2.5%, is sequestered by substrate binding and carried through to catalysis. This idea of conformational selection is gaining credence in the literature and has been described in systems such as cyclophillin A and dihydrofolate reductase [44]. The forward and reverse exchange rates of the I182-G209 loop, ~20 sec-1 and 780 sec-1, are also commensurate with the turnover rate, approximately 135 sec-1, determined by steady-state enzyme kinetics [12], suggesting that it may be rate limiting upon catalysis. It has long been thought that slow conformational changes, and not the chemical step, were rate limiting upon catalysis in arginine kinase and a number of other induced-fit enzymes [14, 44, 60]. Crystal structures of arginine kinase, however, have shown a large number of conformational changes with no indication as to which, if any, of the changes might limit turnover [17, 18]. The NMR analysis of dynamics has provided the first indication of which of these conformational changes is likely rate-

62 limiting. The forward and reverse rates of exchange listed above compelling evidence for dynamics of the I182-G209 loop being rate limiting upon catalysis. Stronger evidence for the rate-limiting nature of the dynamics in the I182-G209 loop can be obtained by measuring rates of exchange and turnover, via relaxation dispersion and enzyme kinetics, both as a function of temperature. It may be very difficult to prove definitively that this loop really controls the turnover, but the temperature dependence can test a necessary (if not sufficient) condition that the NMR dynamics is measuring a transition with the same activation barrier as also limits catalytic turnover, measured by enzyme kinetics. In fact, the dispersion experiments have already been collected at 15, 20, 25, and 30oC and data processing is underway. Experiments are planned to measure kinetic turnover as a function of temperature. Agreement between the activation barriers measured by NMR and kinetically will provide stronger evidence for the loop motion being rate-limiting. A stronger link between the dynamics of the I182-G209 loop and catalysis can be established by extending relaxation dispersion experiments to side-chains of these residues and by examining if mutations in this loop affect rates of both dynamics and catalytic turnover. Determination of the substrate binding (dissociation) constants through the NMR chemical shift titrations was not only of biochemical interest in its own right, but it was a pre-requisite of extending relaxation dynamics experiments from the substrate-free form of the enzyme to the enzyme to the substrate-bound forms. We now know approximately the correct stoichiometry of enzyme and substrates with which to perform relaxation dynamics of complexes, similar to our prior experiments with substrate-free enzyme. In fact, these experiments can also be extended to turning-over enzyme, providing a complete picture of the role of slow dynamics in the catalytic cycle of arginine kinase. It will be exciting to see if dynamics are redistributed as substrates bind and what dynamics are associated with turnover. In fact, the work of Dorothee Kern on the small enzyme cycolphillin A [93], shows a path to how arginine kinase, catalyzing a reaction in an NMR experiment, might be titrated with equilibrium mixtures of substrates and products to determine which of the conformational exchanges might be limiting respectively upon substrate-binding and upon chemical steps of the reaction.

63 With the amenability of arginine kinase to both x-ray crystallography and NMR, future work combining these approaches will provide unique insight into the catalytic cycle of arginine kinase. Crystal structures of binary and ternary complexes will describe amplitudes of substrate-induced conformational changes. Relaxation dispersion experiments probing these complexes and turning-over enzyme will elucidate the dynamics associated with substrate binding and complex formation. Together, these will provide a ‘four-dimensional’ representation of the catalytic cycle of arginine kinase, combining three-dimensional structures of stable states with a fourth dimension describing time constants of inter-conversions between these states. Site-directed mutagenesis and use of substrate analogs will perturb dynamics and/or catalysis. This will potentially permit dissection of the contribution of individual residues to these processes. A more global view may also be taken by comparison to other phosphagen kinases, allowing for an understanding of why evolution may have chosen to conserve or not conserve specific residues of the phosphagen kinases. The role dynamics plays in enzyme catalysis has long been overlooked, but recently developed techniques and methodologies are the cause of a new and growing appreciation for this connection [28, 44, 51]. In some enzymes, such as cyclophillin A [93, 94], dynamics are suggested to be rate limiting upon catalysis. While this work has had tremendous impact in the field, cyclophillin A, however, is a relatively small enzyme (18 kDa) catalyzing a unimolecular, isomerization reaction [93]. The work in this dissertation extends relaxation dispersion experiments to explore the dynamics of arginine kinase, a medium sized (42 kDa), bimolecular, induced-fit enzyme catalyzing a representative reaction – phosphoryl transfer. In addition, the phosphagen kinase family of enzymes, of which arginine kinase is a member, is well studied in terms of structural, functional and evolutionary contexts [10]. All of this makes arginine kinase a unique model system for understanding the connections between dynamics and catalysis and how both structure and dynamics have evolved together. The work presented here provides the foundation for future experiments which will give insight into how slow dynamics impact enzyme catalysis and other biomolecular processes.

64 APPENDIX A: EXPRESSION AND PURIFICATION OF ISOTOPE ENRICHED ARGININE KINASE

Arginine kinase overexpression Arginine kinase from the Atlantic horseshoe crab Limulus polyphemus had previously been cloned for expression. Briefly, the cDNA for arginine kinase was cloned into the pET-22b(+) plasmid vector (Novagen) which carries an ampicillin resistance gene. This vector was then transformed into E. coli expression strain BL21(DE3) (Stratagene, Inc) [115, 122]. Cultures of the arginine kinase expression strain were grown in modified minimal media M9 (1.28% Na2HPO4, 0.3% KH2PO4, 0.05% NaCl, 0.1% NH4Cl, 0.2% D-glucose,

0.024% MgSO4, 0.0015% CaCl2, 0.001% thiamine, 0.001% FeCl3, pH=7.4) [116, 117]. These supplements were required to achieve high levels of expression of isotopically enriched enzyme. This media is typically sterilized by filtration through a 0.2 μm filter and not autoclaved. Immediately prior to use, ampicillin was added to the media to a final concentration of 1 mM. A 25 mL starter culture was inoculated with a 1 μL of a 30% glycerol stock of the expression strain and allowed to grow overnight at 37 oC and 250 rpm. This culture was then transferred to 1 L of media with ampicillin and allowed to grow at 37 oC and 250 rpm to an optical density (OD) of 0.6 AU at 600 nm. Expression was induced by addition of isopropyl-1-thio-β-D-galactopyranoside (IPTG) to a final concentration of 1 mM and cultures were allowed to continue growing overnight at 37 oC and 250 rpm. Production of sample that is uniformly isotopically-enriched differed from the 15 13 unenriched protocol (above) as follows. For incorporation of N and/or C, the NH4Cl 15 and D-glucose in the modified M9 formulation are replaced with ( NH4)2SO4 (Spectrum 13 Stable Isotopes) and C6-D-glucose (Spectrum Stable Isotopes), respectively. Doubling times of the expression strain are not affected by these isotopes. Incorporation of 2H 2 requires replacement of H2O with H2O (Spectrum Stable Isotopes) and ampicillin and 2 IPTG are either added as solids or solutions made in H2O. Doubling times are 2 lengthened by growth in H2O; starter cultures typically take 48-50 hours to become

65 turbid and larger cultures inoculated with this starter take 10-12 hours to reach an OD of 0.6 AU at 600 nm. Induction of deuterated enzyme is typically extended to 24 hours. Expression of amino acid type specific labels is accomplished with a few changes to the unlabeled protocol. Individual unlabeled amino acids are added to the media to final concentrations of 0.01%, except for histidine, phenylalanine, proline, tyrosine, and tryptophan, which are added to final concentrations of 0.02%. Note that the labeled amino acid is not added at this point and this media should not be autoclaved. The overnight starter culture is grown as described above and transferred to the 1 L of media. This culture is allowed to grow at 37 oC and 250 rpm to an OD of 0.3 AU at 600 nm. At this point, the labeled amino acid is added to the media and the culture is grown at 37 oC and 250 rpm to an OD of 0.6 AU at 600 nm and induced with IPTG for 2 hours. In all cases, cells are harvested by centrifugation at 5000 g and 4 oC. Supernatant is discarded and cell pellets are then either used in purification or stored at -20 oC. Empirical evidence shows that cell pellets stored in this manner are viable for 1-2 weeks. Purification of arginine kinase Purification of arginine kinase from the soluble fraction of cell lysate follows a previously determined procedure [115]. Harvested cell pellets from 1 L of culture are resuspended in approximately 30 mL of lysis buffer (50 mM Tris, 7 mM dithiothreitol (DTT), pH=8.0, 4 oC) after being allowed to thaw, if using frozen cell pellets. Cells are lysed by either passage through a microfluidizer (Microfluidics, Inc) under nitrogen gas or by sonication. Optionally, if lysis is achieved by sonication, lysozyme is added to the cell suspension to a final concentration of 50 μg/ml and incubated for 30 minutes at room temperature. Cell debris is removed by centrifugation of lysate for 30 minutes at 12000 g and 4 oC. Crude lysate is exhaustively dialyzed against 1 L of DEAE running buffer (10 o mM Tris, 1 mM Na2EDTA, 1 mM DTT, pH=8.0, 4 C) for 4 hours. All chromatography is performed on an AktaFPLC (GE/Amersham) at 4 oC; all buffers and solutions are filtered through 0.2 μm filters. Before application of the lysate to the HiPrep 16/10 DEAE FF column (GE/Amersham), it is equilibrated with 3 column volumes of DEAE equilibration buffer (100 mM Tris, 10 mM KCl, 1 mM Na2EDTA, 1 mM DTT, pH=8.0, 4 oC) followed by DEAE running buffer until the conductivity establishes a baseline.

66 Crude lysate is applied to the column with a flow rate of 1.5 mL/minute and running buffer is then applied until the conductivity establishes a baseline. Arginine kinase is eluted via a gradient elution with DEAE elution buffer (10 mM Tris, 1 M KCl, 1 mM o Na2EDTA, 1 mM DTT, pH=8.0, 4 C) at a rate of 6 mM KCl/column volume. Arginine kinase typically elutes at 50 mM KCl. Fractions containing arginine kinase are pooled and concentrated, using an Amicon stirred cell, to a final volume of approximately 5 mL for size exclusion chromatography. The HiPrep S300 column (GE/Amersham) is washed with 2 column volumes of S300 running buffer (10 mM Tris, 100 mM KCl, 1 mM Na2EDTA, 1 mM DTT, pH=8.0, 4 oC). The arginine kinase sample is then loaded and isocratically eluted with running buffer at a flow rate of 0.7 mL/minute. Fractions containing arginine kinase are pooled, concentrated, and stored at 4 oC. Exchange of arginine kinase into NMR sample buffer (10 mM citric acid, 0.5 mM 2 o DTT, 50 mM KCl, 50 μM NaN3, 10% H2O, pH=6.5, 4 C) is accomplished by 5-fold repetition of dilution of pooled arginine kinase fractions to 15 mL with NMR sample buffer and concentration to 1 mL, using an Amicon centrifugal concentrator. The sample is then concentrated to the desired final concentration/volume. Protein concentrations are determined spectrophotometrically by converting absorbance at 280 nm to concentration using Beer’s law and an extinction coefficient of 0.76 mL(mg-1)(cm-1), estimated from the sequence of arginine kinase using tools available at the ExPASy server [160]. Refolding of arginine kinase Urea-induced unfolding and refolding of arginine kinase follows a previously published protocol [122] and is only necessary if a deuterated sample is being purified. Unfolding is performed following the DEAE chromatographic step in which fractions containing arginine kinase are pooled and diluted to 0.25 mg/mL with unfolding buffer o (50 mM Tris, 1 mM DTT, 1 mM Na2EDTA, 6 M urea, pH=8.0, 4 C). This solution is incubated at 4 oC for 2 hours with gentle stirring. Refolding is accomplished by sequential dialysis into decreasing urea concentrations. The unfolded arginine kinase solution from above is dialyzed against 3.6

L of each of the refolding buffers (50 mM Tris, 1 mM Na2EDTA, 100 mM 2-

67 mercaptoethanol, 4/2/0.5 M urea, pH=8.0, 4 oC) for 4 hours. The solution is then dialyzed twice against 3.6 L of each of the refolding buffers with DTT (10 mM Tris, 1 o o mM Na2EDTA, 1 mM DTT, 10 mM KCl, pH=8.0, 4 C) for 4 hours at 4 C. The arginine kinase solution is then concentrated to approximately 5 mL for subsequent size exclusion chromatography.

68 APPENDIX B: ADDITIONAL SPECTRA AND CHEMICAL SHIFT TABLES

Chemical shift assignments Residue 1H 15N 13Ca 13Cb M1 - - - - V2 - - 61.19 33.00 D3 8.15 123.00 53.55 41.18 Q4 8.64 121.20 58.09 27.95 A5 8.36 120.60 54.91 16.98 T6 7.84 117.60 66.44 50.54 L7 8.09 123.60 58.22 40.14 D8 8.98 120.00 57.29 39.21 K9 7.71 122.00 59.21 32.33 L10 8.71 123.70 57.86 41.51 E11 9.01 119.60 59.04 28.00 A12 7.98 122.00 54.53 17.16 G13 8.37 109.90 47.20 - F14 8.60 122.50 61.66 38.34 K15 7.62 118.90 59.19 31.73 K16 7.74 119.60 58.96 31.83 L17 7.75 117.90 57.35 41.52 Q18 7.81 117.00 57.68 27.53 E19 7.68 116.30 56.31 29.00 A20 7.07 124.20 50.90 17.57 S21 8.11 120.90 57.79 64.35 D22 8.64 118.60 53.89 38.98 C23 7.64 121.30 56.98 27.30 K24 8.92 130.30 54.61 31.65 S25 7.80 118.90 57.15 65.79 L26 8.16 120.60 57.31 40.66 L27 7.87 118.80 58.19 40.22 K28 7.46 117.90 58.19 31.65 K29 7.45 117.10 58.65 33.07 H30 7.64 111.90 56.91 31.93 L31 8.24 124.40 52.77 38.17 T32 7.28 114.70 60.19 70.04 K33 9.23 122.70 59.58 31.33 D34 8.33 115.60 56.81 39.75 V35 7.43 122.00 66.48 31.40 F36 9.01 120.60 61.22 38.80 D37 8.85 117.90 56.91 38.88 S38 7.57 114.10 60.62 63.66 I39 7.36 111.10 61.32 38.77 K40 7.92 120.10 58.91 29.80 N41 8.17 115.10 52.87 38.97 K42 7.62 120.50 56.38 33.33 K43 7.88 116.80 54.11 35.79 T44 9.04 114.70 60.31 70.41

69 Residue 1H 15N 13Ca 13Cb G45 9.78 111.90 46.52 - M46 7.76 117.70 56.24 30.96 G47 7.91 108.40 44.72 - A48 7.87 124.60 51.91 19.36 T49 9.51 111.90 59.79 72.06 L50 10.41 120.00 55.58 39.38 L51 7.97 121.80 57.13 40.95 D52 6.94 115.20 56.40 41.01 V53 6.92 117.20 62.52 32.23 I54 7.66 109.80 62.03 39.22 Q55 7.99 120.60 59.48 25.29 S56 9.27 114.30 60.61 62.85 G57 7.36 109.10 46.14 - V58 7.42 119.10 64.45 31.35 E59 7.68 115.50 57.02 29.32 N60 7.81 115.70 50.73 38.55 L61 - - 57.05 40.46 D62 9.21 115.70 53.12 37.73 S63 7.44 115.80 58.87 64.31 G64 8.26 111.90 46.05 - V65 8.33 124.20 64.79 29.73 G66 8.19 103.50 44.38 - I67 5.98 104.60 57.13 40.45 Y68 7.99 118.00 56.45 42.93 A69 9.51 121.70 48.75 20.08 P70 - - 62.68 32.44 D71 7.34 113.60 51.87 39.92 A72 8.07 120.00 54.78 18.15 E73 7.90 119.20 57.77 29.22 S74 8.65 117.40 63.48 62.58 Y75 6.61 117.70 62.58 38.30 R76 7.72 114.80 58.20 30.01 T77 8.66 121.10 63.28 66.72 F78 7.79 113.40 58.49 36.79 G79 7.73 113.80 48.99 - P80 - - 65.11 31.56 L81 7.63 112.50 54.66 44.05 F82 7.91 115.60 63.35 39.09 D83 10.07 118.40 59.96 36.69 P84 - - 64.97 29.49 I85 6.60 120.40 66.18 36.34 I86 8.87 122.90 66.08 46.97 D87 7.97 118.50 57.11 41.79 D88 7.50 117.20 55.87 41.81 Y89 8.99 118.40 62.37 37.83 H90 8.30 112.80 57.28 29.50 G91 7.53 109.10 46.66 - G92 8.48 111.00 45.06 - F93 9.99 133.80 59.87 38.70

70 Residue 1H 15N 13Ca 13Cb K94 9.30 126.70 54.79 32.73 L95 8.57 122.10 57.80 40.64 T96 6.87 101.80 60.50 68.29 D97 7.00 123.40 54.36 40.34 K98 7.99 116.00 55.18 34.54 H99 9.12 129.30 54.63 31.39 P101 - - 62.40 31.09 K102 7.85 126.00 56.57 30.89 E103 8.63 129.90 55.30 30.44 W104 8.57 126.50 57.24 31.65 G105 8.51 102.70 43.41 115.40 D106 7.21 115.20 52.38 39.21 I107 8.66 130.80 63.73 37.21 N108 8.17 114.70 54.82 37.42 T109 7.69 108.10 61.77 70.17 L110 7.53 124.00 53.23 40.66 V111 7.69 110.50 58.64 34.86 D112 7.60 117.20 53.64 39.57 L113 8.35 125.60 55.52 42.29 D114 7.90 110.00 51.98 42.61 P115 - - 64.55 30.69 G116 8.53 107.00 45.08 - G117 7.84 109.20 46.60 - Q118 8.63 119.50 56.85 29.16 F119 10.07 118.50 59.43 41.21 I120 9.32 120.80 62.97 37.64 I121 9.20 131.20 63.01 38.62 S122 7.71 114.70 58.26 64.34 T123 8.42 117.90 63.10 71.12 R124 9.04 124.50 54.38 33.76 V125 9.23 121.60 61.75 34.04 R126 8.42 125.70 52.49 34.15 C127 9.31 119.40 56.80 31.16 G128 9.05 108.90 43.80 - R129 8.67 118.20 52.81 37.04 S130 9.15 116.20 55.89 63.64 L131 13.21 131.90 54.47 40.54 Q132 8.54 124.60 57.02 28.27 G133 8.87 111.00 44.36 - Y134 7.36 117.30 55.51 41.07 P135 - - 62.02 31.34 F136 8.32 116.40 52.76 36.31 N137 8.60 115.90 58.22 37.75 P138 - - 65.29 32.04 C139 7.92 109.20 57.98 31.43 L140 6.97 124.00 55.74 42.33 T141 8.51 112.60 59.34 70.76 A142 8.02 123.80 55.73 16.40 E143 8.43 116.10 59.65 28.11

71 Residue 1H 15N 13Ca 13Cb Q144 7.75 120.70 58.76 30.21 Y145 8.50 119.00 63.72 37.66 K146 7.63 117.40 59.01 31.95 E147 8.15 121.50 59.04 29.82 M148 8.74 119.30 59.05 33.65 E149 8.08 119.20 59.67 28.40 E150 7.87 121.50 59.46 28.32 K151 7.66 119.60 59.02 31.95 V152 8.98 121.10 66.30 30.83 S153 8.89 116.70 62.21 61.19 S154 7.60 118.30 61.19 62.65 T155 7.43 119.90 66.94 67.85 L156 8.51 121.60 56.91 38.66 S157 8.24 114.30 61.20 62.34 S158 7.20 114.60 58.25 64.14 M159 7.13 121.40 56.82 32.33 E160 8.48 120.30 54.60 33.10 D161 8.97 120.60 55.47 39.36 E162 8.60 124.00 58.39 28.59 L163 7.48 118.20 54.03 40.72 K164 6.73 118.50 56.36 32.12 G165 8.60 113.60 46.29 - T166 6.98 118.40 61.45 71.52 Y167 8.47 125.10 57.01 39.59 Y168 9.23 128.90 53.67 38.43 P169 - - 61.69 30.74 L170 8.83 122.20 57.93 40.37 T171 8.26 117.90 64.86 67.85 G172 9.02 117.70 45.09 - M173 7.05 121.50 56.61 33.64 S174 9.12 126.30 57.33 64.79 K175 8.83 122.90 58.84 30.85 A176 8.34 121.60 54.75 17.23 T177 7.90 119.10 65.88 67.55 Q178 8.24 121.20 59.49 28.18 Q179 8.09 116.80 57.81 27.51 Q180 7.56 119.50 58.13 27.84 L181 7.90 118.00 57.04 41.53 I182 8.56 124.40 65.05 37.03 D183 8.32 124.70 57.05 38.98 D184 7.00 116.70 54.27 40.49 H185 7.84 113.60 56.19 25.16 F186 8.53 115.20 53.48 40.11 L187 7.23 121.10 54.74 42.56 F188 5.67 119.60 54.01 38.83 K189 8.20 118.30 53.89 34.23 E190 8.24 119.60 56.95 28.37 G191 6.90 109.70 44.80 - D192 7.81 119.20 52.55 40.80

72 Residue 1H 15N 13Ca 13Cb R193 8.25 114.70 58.36 28.28 F194 7.69 122.00 60.78 36.39 L195 7.36 119.90 56.64 40.92 Q196 9.20 121.00 58.41 27.03 T197 7.59 108.20 63.30 69.01 A198 6.82 120.60 51.00 18.74 N199 7.84 112.90 53.24 34.14 A200 7.54 114.80 52.36 20.20 C201 8.41 117.30 55.86 29.02 R202 9.16 123.00 57.41 30.22 P205 - - 63.48 30.88 T206 8.84 123.30 64.76 67.96 G207 8.58 113.10 45.59 - R208 7.66 120.40 54.44 31.15 G209 8.27 108.60 45.59 - I210 8.20 119.00 59.08 42.13 F211 9.67 127.00 54.71 45.07 H212 7.17 120.40 53.81 32.12 N213 8.69 118.80 51.74 38.40 D214 9.05 127.80 57.97 38.92 A215 8.11 117.80 52.52 18.73 K216 7.96 113.60 58.53 28.41 T217 8.82 107.70 59.76 70.60 F218 7.81 123.60 56.34 42.64 L219 8.64 130.10 52.63 46.25 V220 9.47 123.20 59.30 35.44 W221 9.15 126.10 52.94 31.72 V222 9.51 129.60 61.50 32.01 N223 9.15 120.00 55.54 35.80 E224 7.91 120.00 57.88 24.64 D226 - - 53.12 44.66 H227 8.39 121.20 58.38 31.50 L228 8.04 110.70 53.55 45.68 R229 8.36 123.20 55.22 31.94 I230 8.81 128.20 61.30 39.41 I231 9.04 127.00 60.12 40.72 S232 8.61 120.00 54.22 65.51 M233 8.90 126.00 54.74 35.20 Q234 8.23 111.30 55.07 31.64 K235 8.26 118.80 56.26 31.92 G236 8.16 112.50 44.43 - G237 8.56 106.10 46.22 - D238 8.70 121.40 52.93 37.04 L239 8.41 128.20 56.84 41.16 K240 6.95 117.70 60.30 30.38 T241 7.22 116.80 66.15 67.00 V242 7.93 121.80 66.13 31.49 Y243 9.11 122.90 60.64 38.77 K244 8.63 119.40 59.34 31.44

73 Residue 1H 15N 13Ca 13Cb R245 7.75 120.30 58.90 28.79 L246 6.99 118.90 58.34 40.88 V247 7.85 118.00 65.32 29.60 T248 7.50 113.10 65.44 68.62 A249 7.76 123.00 54.98 20.30 V250 8.85 118.90 67.86 30.49 D251 8.41 119.10 57.12 38.68 N252 7.85 119.60 56.19 37.99 I253 8.63 122.60 65.71 37.88 E254 8.60 121.60 56.58 28.64 S255 7.20 110.30 60.62 62.75 K256 7.23 119.40 56.00 34.32 L257 8.05 122.60 50.66 42.68 P258 - - 62.28 31.63 F259 8.88 121.50 53.30 40.84 S260 9.00 118.40 59.05 63.36 H261 9.04 130.00 55.66 31.47 D262 8.41 128.20 52.48 47.53 D263 8.72 125.50 56.48 40.27 R264 8.19 117.20 57.88 29.36 F265 8.43 114.80 56.52 40.13 G266 7.62 106.60 45.12 - F267 8.40 125.00 61.07 37.03 L268 6.39 118.10 54.69 42.21 T269 6.37 111.00 58.83 71.53 F270 9.85 125.50 52.80 39.07 C271 9.05 119.70 55.59 28.93 T273 - - 63.27 68.43 N274 7.60 121.50 52.76 39.33 L275 - - 54.12 43.84 G276 7.23 105.20 45.28 - T277 9.34 117.20 62.65 69.97 T278 - - 64.64 70.40 M279 8.57 123.30 56.05 34.84 R280 8.83 128.20 55.04 31.99 A281 9.95 136.10 49.90 19.80 S282 9.47 115.30 56.65 65.78 V283 8.83 117.30 58.75 34.73 H284 8.40 124.20 53.58 30.41 I285 9.77 126.90 58.82 43.19 Q286 8.85 128.00 54.17 30.09 L287 8.42 125.00 51.00 42.24 P288 - - 65.21 31.36 K289 11.67 123.90 59.19 30.65 L290 10.67 127.10 57.16 40.34 A291 8.20 118.30 53.57 18.87 K292 7.21 115.20 56.83 31.39 D293 7.83 122.10 52.36 40.11 R294 8.07 122.00 58.59 29.20

74 Residue 1H 15N 13Ca 13Cb K295 8.30 119.40 58.81 31.15 V296 7.50 120.00 65.64 31.02 L297 7.06 120.00 57.99 41.19 E298 8.32 117.20 58.72 28.31 E298 8.31 - - - D299 8.38 122.20 57.17 39.86 I300 8.06 121.60 64.82 37.38 A301 8.22 120.50 55.48 17.05 S302 8.41 113.00 61.93 - K303 7.64 123.30 58.49 31.17 F304 7.31 115.70 57.53 38.80 N305 7.55 110.90 54.62 37.22 L306 8.74 117.50 52.73 42.05 Q307 9.33 120.90 53.68 30.70 V308 8.88 126.00 61.01 32.20 R309 8.87 127.80 54.28 32.78 G310 8.85 112.10 44.91 - T311 8.09 113.80 61.72 69.18 R312 8.33 122.40 55.32 29.70 G313 8.07 109.90 45.85 - E314 8.64 121.40 56.76 29.12 H315 8.44 118.30 55.52 29.02 T316 7.80 114.10 62.10 69.31 E317 8.61 122.70 57.12 28.88 S318 8.11 115.80 58.04 63.50 E319 8.25 123.60 56.32 29.17 G320 8.29 110.30 45.03 - G321 8.05 108.00 46.05 - V322 7.16 119.10 61.22 31.10 Y323 9.08 126.10 57.12 42.07 D324 9.00 122.10 52.99 42.77 I325 9.07 128.00 59.27 37.72 S326 8.59 118.60 56.17 67.63 N327 8.70 116.90 54.52 37.47 K328 8.53 122.10 57.81 34.06 R329 8.85 118.10 57.41 32.03 R330 9.45 120.70 56.46 32.99 L331 8.29 123.30 53.30 44.32 G332 12.09 116.00 44.55 - L333 7.44 122.70 53.79 42.02 T334 8.13 107.60 59.45 72.36 E335 10.29 123.40 62.55 27.13 Y336 7.90 115.60 61.21 37.16 Q337 8.06 117.10 58.64 27.95 A338 8.46 122.60 54.82 17.85 V339 8.17 116.30 65.11 30.43 R340 8.41 122.30 61.80 - D344 - - 57.08 39.20 G345 7.80 108.60 46.57 -

75 Residue 1H 15N 13Ca 13Cb I346 8.40 122.30 61.95 33.49 L347 8.49 119.00 58.02 40.28 M349 - - 59.84 - I350 8.26 118.80 65.58 37.10 K351 7.74 120.30 59.52 31.41 M352 7.99 118.00 57.00 30.61 E353 8.52 125.50 58.75 28.37 K354 8.16 117.10 58.76 32.05 A355 7.38 119.80 52.17 18.69 A356 7.31 123.30 52.16 18.20 A357 7.93 129.50 53.74 19.15

76 2D [15N, 1H] TROSYs of amino acid type specific labels 15 N-Asn ar g inine kinase

77 15N-Cys arginine kinase 78

15N-Leu arginine kinase 79

15N-Lysarginine kinase 80

15N-Val arginine kinase 81

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94 BIOGRAPHICAL SKETCH

Relevant Skills Recombinant protein expression and purification; liquid chromatography; UV/Vis spectroscopy; denaturing gel electrophoresis; steady state enzyme kinetics; collection and analysis of NMR spectra, including relaxation dispersion experiments; protein crystallization; DNA isolation and purification; agarose gel electrophoresis; PCR; cloning and subcloning; sequence analysis.

Education • Ph.D., Biochemistry, Florida State University, Tallahassee, FL 2008 Advisor: Dr. Michael S. Chapman Dissertation title: The intrinsic dynamics of arginine kinase • B.S., Biochemistry, University of Texas, Austin, TX 2000

Experience • Graduate Student, Florida State University, Tallahassee, FL 2002-present - Conducted aspects of NMR relaxation dispersion based investigation into the dynamics of arginine kinase, including expression and purification of isotope enriched arginine kinase, NMR data acquisition and analysis, and steady state enzyme kinetics analysis. - Mentored new students in aspects of protein expression and purification and instrument use. - Experience with Unix, Linux, Windows, C++, and many other software suites. • Teaching Assistant, Florida State University, Tallahassee, FL 2002-2003 - Taught undergraduate introductory Chemistry laboratory classes. - Assisted in preparation and grading of exams, laboratory procedures, and reports.

95 Presentations • Skalicky, J.J., Davulcu, O., Clark, S.A., Ellington, W.R., Chapman, M.S. Functional dynamics of arginine kinase. 2003, Southeast Magnetic Resonance Conference, Tallahassee, FL. • Davulcu, O., Skalicky, J.J., Chapman, M.S. Functional dynamics of arginine kinase. 2007, Keystone Symposia - Frontiers of NMR in Molecular Biology X, Snowbird, UT.

Publications

• Davulcu, O., Clark, S.A., Chapman, M.S. & Skalicky, J.J., Main chain (1)H, (13)C, and (15)N resonance assignments of the 42-kDa enzyme arginine kinase. J Biomol NMR, 2005. 32(2): p. 178. • Hoffman, G.G., Davulcu, O., Sona, S. & Ellington, W.R., Contributions to catalysis and potential interactions of the three catalytic domains in a contiguous trimeric creatine kinase. FEBS Lett., submitted. • Davulcu, O., Skalicky, J.J. & Chapman, M.S., Dissection of the substrate induced conformational changes of arginine kinase using NMR and crystallography. In preparation

Awards

• Hoffman teaching award, Florida State University, 2002. • American heart association, Florida/Puerto Rico affiliate, Predoctoral fellowship, 2004-2005.