DEVELOPING CHEMICAL EXCHANGE SATURATION TRANSFER (CEST) BASED NMR TECHNIQUES TO STUDY PROTEIN DYNAMICS ZHOU YANG NATIONAL UNIVERSITY OF SINGAPORE

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1 DEVELOPING CHEMICAL EXCHANGE SATURATION TRANSFER (CEST) BASED NMR TECHNIQUES TO STUDY PROTEIN DYNAMICS ZHOU YANG NATIONAL UNIVERSITY OF SINGAPORE 017 1

2 DEVELOPING CHEMICAL EXCHANGE SATURATION TRANSFER (CEST) BASED NMR TECHNIQUES TO STUDY PROTEIN DYNAMICS ZHOU YANG (B.Sc. HUST) Supervisor: Professor Yang Daiwen Examiners: Associate Professor Yuan Yu-Ren, Adam Associate Professor Kunchithapadam Swaminathan Associate Professor Surajit Bhattacharyya, Nanyang Technological University A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF BIOLOGICAL SCIENCES NATIONAL UNIVERSITY OF SINGAPORE 017

3 DECLARATION I hereby declare that this thesis is my original work and it has been written by me in its entirety. I have duly acknowledged all the sources of information which have been used in the thesis. This thesis has also not been submitted for any degree in any university previously Zhou Yang 16 August 017 3

4 ACKNOWLEDGEMENT I wish that I can fully express my sincere gratitude to my supervisor Professor Yang Daiwen for his continuous support and enlightening guidance in the past four years. Without his guidance, support, patience and trust, I could not have been able to complete the work and the thesis. I am deeply impressed by his rigorous attitude of conducting research, his patience in teaching. I remember the very moments when he chose the NMR books for me at the very beginning of my Ph. D study, when he reminded me to work harder, when he let me revise my writing again and again. He has been a great teacher to whom I owe really much. I would like to take this opportunity to thank Dr. Fan Jingsong. His help in NMR experiments made my life easier. I really learned a lot from him, from NMR experimental methods to data analysis protocols. Special thanks to my fellow graduates, postdoctoral fellows and research staff from the Department of Biological Sciences. Mr. Lai Chong Cheong, Mr. Kenneth Lee, Dr. Liu Wei, Dr. Xiao Tianshu and Dr. Gao Zhenwei have been a teacher and sincere friends to me. Their help and guidance in my experiments and daily life have been making the past four years a pleasant journey in my life. Thank Li Jiaxin, Yang Yadi, Dr. Lei Cheng, Dr. Liu Xiao and all other friends I

5 for their help. I owe thanks to my family in China. My parents have been supportive and dedicated. My younger sister has been cheerful. Without their love and understanding, I would not have been here and started the thesis. Last but not the least, thanks to the Department of Biological Sciences, National University of Singapore for providing financial assistance and an enjoyable, wonderful campus life. II

6 Table of Contents Chapter 1: Introduction Protein dynamics An overview The protein folding problem Spider silk formation The chemical exchange saturation transfer (CEST) NMR Basic principle The J-coupling effects on CEST experiments The objectives Chapter : Literature review NMR methods to study protein dynamics The chemical exchange saturation transfer (CEST) The CEST history J-coupling effects on CEST experiments Protein folding Protein folding theories Folding studies of meacp protein Solvent effects of deuterium water and urea on protein folding 9.4. Spider silk formation Chapter 3: Materials and methods Simulation test on the approximation method of J-coupling effects III

7 on CEST experiments CEST experiments on ACP protein CEST Data analysis Pre-process of CEST raw data Individual and global fitting using a two-state model Individual fitting and global fitting using three-state models Error estimation Energy calculation Cα NMR peak assignment for meacp protein in 4M urea Expression and purification of RPmi protein N CEST experiment on RPmi The CPMG experiment on RPmi Chapter 4: Results and discussion The J-coupling approximation method in CEST experiments Theoretical derivation of considering J-coupling effects on CEST experiments Simulation test of the J-coupling approximation method on CEST experiments Experimental test of the J-coupling approximation method The hidden intermediate state I of meacp Evidence of the state I Three-state models IV

8 4..3. Structural features of the state U and state I The partially unfolded form (PUF) The transition state of meacp Comparison of folding dynamics in DO, HO, and urea Solvent effects of DO on protein folding Effects of low concentration of urea on meacp folding and unfolding Folding of meacp at 4 M urea Discussion on the transition state of meacp folding RPmi protein dynamics CEST and CPMG experiment on RPmi The minor state of RPmi was possibly an unfolded state Chapter 5: Conclusions and future work... 9 References V

9 Summary Chemical exchange saturation transfer (CEST) based methods have broad applications in the field of magnetic resonance. The recent rapid development in CEST nuclear magnetic resonance (NMR) techniques makes them powerful and versatile tools to study different protein dynamics at almost atomic resolution. We first demonstrate here an approximation method of considering J-coupling effects on CEST NMR experiments. In this method, a multiplet caused by J-coupling splitting effects is treated as multiple isolated spins that evolve independently. We provided a theoretical derivation for the method and then examined the method by simulations and comparing 13 CO and 15 N CEST experiments on the acyl carrier protein domain from Micromonospora echinospora spp. Calichensis (meacp, Protein Data Bank ID: l9f), a protein which has been shown to undergo a conformational exchange process between the native folded state and an unfolded state. The consistency of 13 CO and 15 N CEST results demonstrated that the method takes into account the J-coupling effects successfully. The method helps the accurate characterization of chemical exchange processes in systems with multiple weakly coupled spins, thus extending the application of CEST methods in more complex situations where J-coupling effects cannot be ignored. Furthermore, based on our recently developed 13 Cα CEST pulse scheme and the J-coupling-consideration method, we did 13 Cα CEST experiments on meacp in VI

10 different solvent conditions. Taken all the CEST ( 13 CO, 15 N and 13 Ca) experimental data on meacp together, we showed there exists a hidden intermediate state I besides the native state and unfolded state for each residue of the protein. Analysis of the CEST data using three-state models demonstrated that the hidden state I is a partially unfolded form (PUF), whose N-terminal region is unfolded while the C-terminal region is folded. At the same time, the quantification of solvent effects on the folding process of meacp suggests the transition state of folding is native-like. Overall, we characterized the structural features of the intermediate state and a transition state of meacp folding, providing a more comprehensive picture of the folding process of meacp by CEST techniques. The studies on meacp folding contribute to our understanding of the long-standing protein folding problem. In addition, the dynamics of the repetitive domain from minor ampullate spider silk protein (RPmi) was also investigated by using CEST and relaxation dispersion (RD) experiments. We showed there exists a fast exchange process (~3900 s -1 ) between the native state and a possibly unfolded state in the system. This initiated a possible future study on folding dynamics of spider silk protein, which might provide insights into the processes of silk fiber formation. VII

11 List of figures Figure 1-1. Simplified NMR spectrum for a two-state (ground (G) and excited (E)) exchange system Figure 1-. Simplified illustration of CEST experiments and expected results Figure -1. Multiple sequence alignment of meacp with selected type Ⅰ and type Ⅱ ACPs Figure -. The NMR solution structure of meacp protein. (J. Lim et al., 011)... 9 Figure -3. The NMR 1 H- 15 N assignment of RPmi protein. (Gao et al., 013) Figure -4. The NMR solution structure of RPmi protein. (Gao et al., 013) Figure 4-1. Dependences of extracted kex (a) and pb (b) on the J coupling of a two-spin system. The synthesized CEST profiles with 1% Gaussian noise were fitted by three methods: 1. accurate method without approximation (dotted line),. J-coupling- neglected method (filled dot), and 3. J-coupling-considered method (filled square). The error bars represent standard deviations of kex and pb which were extracted from 100 sets of profiles Figure 4-. Distribution of kex and pb values extracted from individual fits of 4 15 N CEST profiles (a) and 1 13 CO CEST profiles (b) using the J-couplingneglected method (grey dot) and J-coupling-considered method (black square). VIII

12 Figure 4-3. Examples of CEST profiles for spins belong to same amino acids or peptide bonds. (a) and (b): 13 CO and 15 N CEST profiles for H968; (c) and (d): profiles for T973; (e) 13 CO profiles for A98; (f): 15 N profiles for R983. (e) and (f) are in the same peptide bond. Dots: experimental CEST data from 15 N, 13 C- labelled meacp sample; Lines: fitting results based two-state or three-state (N U I, for a-c) models Figure Cα CEST 1 H- 13 C correlation spectrum of meacp in 95% HO and 5% DO. The noise in the region around 4.73 ppm is from residual water signals Figure 4-5. (a) Number of states that each Ca spin occupies. (b) Examples of CEST profiles with different states are colored correspondingly. Profiles with two weak RF field of 15 and 30 Hz are in dark and light color, respectively (see methods). Regions uncertain are colored in gray Figure 4-6. Representative 13 Cα CEST profiles in HO, DO, and 0.5 M urea. RF weak field used in the three experiments was ω1 = 15 Hz. Solid lines are the best fits Figure 4-7. Representative 15 N CEST profiles in HO and 0.5 M urea Figure 4-8. Population of state U pu (a), the pu distribution of the two half regions (N-terminal: red; C-terminal: grey) of meacp in DO (b), HO (c), 0.5 M urea (d) and 0.5 M urea (e) Figure 4-9. Population of state U (pu) extracted from individual 15 N CEST IX

13 profiles recorded in HO and 0.5 M urea. The two-state model was used in fitting Figure Examples of DO 13 Ca CEST global fitting using the two-state model. Grey squares are experimental data, red lines are calculated profiles based on global fitting using the two-state model, where all residues share same kex and pu. The fitting based on the two-state model was bad, especially for the minor dip regions. By comparing profiles of residues in C- and N-terminal regions, we can see obvious differences in the depth of the minor state, which indicate the differences of pu for the two regions Figure Ca secondary chemical shifts of state N, U and I in DO. 13 Ca chemical shifts experimentally measured in 4 M urea (fully denatured) were used as the reference Figure N Secondary chemical shifts of state N, U and I in HO. Chemical shifts of 15 N in 4 M urea were used as the reference.(j. Lim et al., 014b) Figure A possible hypothesized folding pathway (left) and its apparent equivalent triangle model (right). It is hypothesized there might be an onpathway I0 which shares structural similarity with the state I we observed Figure H/D solvent isotope effect correlates with protein size Figure Schematic plot of energy profile of meacp folding in HO and low concentration of urea. The free energies in states TS and N are relative to that in state U X

14 Figure CEST profiles for residue R943 of meacp in 4 M urea and 0 M urea Figure The minor state of meacp in 4 M urea has a native-like folded structure. (a) The minor state chemical shifts in 4 M urea vs. the folded state chemical shifts in 0 M urea. (b) The chemical shifts differences between the minor states in 4 M urea and the native folded state in 0 M urea Figure Schematic plot of energy profile of meacp folding in DO and 4 M urea. The free energies in states TS and N are relative to that in state U Figure Overlapping of CEST profiles for different residues in RPmi protein. ΩF is the ( 15 N) chemical shift of the residue in the folded (F) state.85 Figure 4-0. CPMG profiles for residues in different regions of RPmi Figure 4-1. Examples of the analysis combining CEST and CPMG data. The two set of data were fitted into the same two-state model with same dynamics parameters Figure 4-. The minor state of RPmi is possibly an unfolded state. (a) 5 eff residues with R drop more than 3 s -1 were selected for fitting into CEST and CPMG data, chemical shifts of 6 residues (red circles) were possibly wrong. (b) All of the chemical shifts were determined based on Ω (from CPMG) and assuming the minor state is close to random coil. The 15 N chemical shifts in the random coil were predicted from the free online server 89 XI

15 List of tables Table -1. Isotope effects on different proteins. Amide isotope effect refers to the replacement of amide hydrogen NH with ND. Positive values of (ΔGDOND ΔGDONH) indicate NH is more stable than ND. Solvent isotope effect (ΔGDONH ΔGHONH) refers to the change of solvent from HO to DO without changing the amide hydrogen, the negative values of (ΔGDONH ΔGHONH) shows proteins are more stable in DO Table 3-1. CEST experiments Table 4-1. Individual kex and pb values extracted from 15 N or 13 CO CEST data Table 4-. Reduced χ using different models Table 4-3. Folding and unfolding based on the triangle model XII

16 List of abbreviations 1D/D/3D CEST CPMG RD CS DEST meacp One-/Two-/Three-dimensional Chemical exchange saturation transfer Carr Purcell Meiboom Gill relaxation dispersion Chemical shift Dark-state exchange saturation transfer Acyl carrier protein domain from Micromonospora echinospora spp. Calichensis MS HSQC HX I IPTG N PDB ppm PUF RF RPmi Mass spectrometry Heteronuclear single quantum coherence Hydrogen exchange Intermediate (state) Isopropyl-β-D-thiogalactopyranoside Native (state) Protein data bank Parts per million Partially unfolded form Radio frequency Repetitive domain from minor ampullate spider silk proteins T1 Longitudinal relaxation time T Transverse relaxation time XIII

17 Tris TS U -amino--hydroxymetheyl-propane-1,3-diol Transition state Unfolded (state) XIV

18 Chapter 1: Introduction 1

19 1. Chapter 1: Introduction The primary purpose of this chapter is to provide overviews of major important topics in this thesis, detailed reviews can be found in Chapter. A summary of the objectives of the work will be presented at the end of this chapter Protein dynamics An overview Protein dynamics has been an increasingly interesting area with the growing awareness that proteins stay in more than one conformations under native conditions (Korzhnev, Neudecker, Mittermaier, Orekhov, & Kay, 005; J. Lim, Xiao, Fan, & Yang, 014a; Vallurupalli, Bouvignies, & Kay, 01; Yang, Noble, & Yang, 009). The multiple forms of a protein are an exchange system themselves, in which there exists a dynamic equilibrium between differently populated conformations (or states) of the molecule. The population distribution of the different conformations (or states) follows the Boltzmann distribution: p i = e E i /kt N 1 e E i /kt (Eq 1-1) Where p i is the population of state i, E i is the energy level of state i, k is the Boltzmann constant. The population of state i depends on its energy level (stability): the more stable it is, the larger population it has.

20 Transitions between those different states of proteins, occurring at various spatial and time scales, have been linked to functionally activities such as enzyme catalysis (Fraser et al., 009), allosteric signaling (Bu & Callaway, 011), protein folding processes (Bollen, Kamphuis, & van Mierlo, 006) and molecular polymerization (Fawzi, Ying, Torchia, & Clore, 01). Studying these conformational transition processes provides understanding in important biological processes such as protein folding, protein binding, and protein oligomerization. To observe the protein transition processes, it requires techniques that can provide information on different states during the transition, not only the dominant native state, but also the sparse-populated excited states. Traditional biophysical techniques such as structure-solving protocols by nuclear magnetic resonance, X-ray and electron microscopy, have been very successful in determining the dominant (most populated) state of biomolecules. However, they often fail in capturing the states at higher energy levels. One of the major challenges is that the states at higher energy levels are sparsely populated and transiently formed conformations, and that they are often invisible in most imaging techniques. There are only a limited number of methods that can detect low populated transient states of the molecules. Even fewer methods can reach a high time or spatial resolution. 3

21 The situation has been improving over the past half century with the development of new biophysical methods, including new nuclear magnetic resonance (NMR) techniques. Experimental methods for quantifying protein transition processes by NMR mainly include R 1ρ relaxation dispersion (Massi, Johnson, Wang, Rance, & Palmer, 004; Zhao, Hansen, & Zhang, 013), Carr Purcell Meiboom Gill (CPMG) relaxation dispersion (RD) (Carr & Purcell, 1954; Meiboom & Gill, 1958; P. Neudecker et al., 01; Vallurupalli, Bouvignies, & Kay, 011), longitudinal magnetization exchange, line shape analysis(a. Schmidt & Vega, 1987; Wang et al., 003), and hydrogen exchange (HX) labelling NMR. Different exchange processes, fast or slow, require different methods mentioned above. These methods have been demonstrated successfully in extracting chemical exchange processes of different proteins and also RNA molecules and characterizing the sparse populated excited states in the systems The protein folding problem Protein folding/unfolding (transitions between folded and unfolded states) is an important category of dynamics. Studies of folding processes of different proteins provide insights into the general mechanism of protein folding, which remains missing. 4

22 More than 50 years ago it was discovered that a single chain of amino acids can form a well-structured shape of a protein molecule by itself (Anfinsen, Haber, Sela, & White, 1961). Following this discovery, the famous Levinthal s paradox (Levinthal, 1969) proposed that because an unstructured polypeptide chain has astonishingly large number (estimated as 3 n where n is amino acid number) of possible conformations, folding by random searching to the only one native conformation would take proteins astonishing time to complete. As proteins can fold fast (within milliseconds and even microseconds), proteins must fold through several intermediate states. This raised interests of experimentally characterizing folding intermediate states. However, one of the major challenges is that the intermediate states are often sparse populated and can easily escape detection. Many proteins have been found to fold as a two-state, all or none, behavior, without evident intermediate states (Jackson, 1998). With the emerging of powerful techniques such as CEST NMR, hydrogen exchange mass spectrometry (HX MS), protein intermediate states begin to be discovered in excellent details. However, the lack of detailed structural characterization of protein folding intermediate states, or transition state, remains one of the major obstacles for understanding the general mechanisms of protein folding. The equilibrium folding/unfolding dynamics of the acyl carrier protein domain from Micromonospora echinospora spp. Calichensis (meacp, PDB ID: l9f) has been studied in our laboratory by using different methods such as hydrogen 5

23 exchange (HX) NMR, CPMG relaxation dispersion (RD) and chemical exchange saturation transfer (CEST) (J. Lim et al., 014a; Zhou & Yang, 014, 015). Under the native conditions, there exists an equilibrium between native state (N), unfolded state (U) and an intermediate state (I) of meacp. The three states are in relatively slow conformational exchanges on the sub-second timescale, following the pathway N U I or U N I. However, the overall structure of this third state I was mostly uncertain. To provide a further insight into the folding process of meacp, we will characterize the intermediate state (I) as well as a transition state (TS) on the folding pathway by using CEST experiments Spider silk formation Spider silk is an ideal super material due to its outstanding mechanical properties. The spider silk fiber mainly consists of β-sheets structures, while the silk proteins before fiber formation exist as helices and disordered conformations. It is still not well understood how the transitions from the helical and disordered structures to the well-formed β-sheets structure happen during fiber spinning. In the efforts to understand the molecular structures, selfassembly mechanism and fiber formation of spider silk proteins, our laboratory has solved solution structure of the C-terminal domain, repetitive domain (CTDmi, RPmi) of the minor ampullate silk protein (MiSp) (Gao et al., 013). 6

24 In aqueous solution, the structure of RPmi adopts a globular fold which is composed of a compact seven-helix bundle (Gly17-Ala141) and an unstructured region (Pro14-Gly148). Seven helices are intercepted by short turns. It is hypothesized that an unfolding or partially unfolding transformation process happens during the fiber formation of spider silk protein. To study the possible transformation of spider silk protein, here we also present the studies of dynamics of RPmi protein by using CEST and CPMG RD NMR method. 1.. The chemical exchange saturation transfer (CEST) NMR Basic principle For slow exchange processes, the chemical exchange saturation transfer (CEST) NMR technique (Vallurupalli et al., 01; Zhao et al., 013) now emerges as a powerful tool. The application of CEST can be demonstrated in Figure 1-1. Simplified NMR spectra for a two-state (ground (G) and excited (E)) exchange system., which depicts a common situation where a protein exists as a dominant ground (G) state and a sparsely populated excited (E) state and the two states are interconverting to each other. Since the population (concentration) of the excited state is too small to be observable, we basically only can read the signal for the dominant ground state when using a conventional method. It is our wish that to read out the invisible excited states signal! To accomplish this, the idea 7

25 of saturation transfer via exchange can be used. The CEST experiment is illustrated schematically in Figure 1-. In a classical context, the definition of saturation is MX = MY = MZ = 0. A single, long and typically weak RF pulse is often used to saturate a single signal. A continuous long on-resonance irradiation (RF) equalizes these population, the population difference, thus the MZ (also MY and MZ) goes to zero. By doing a series of experiments with varied RF positions (in the frequency domain), the chemical shifts of both states can be mapped out in the CEST profiles. Furthermore, not only the chemical shifts of different states, the chemical exchange rates and longitudinal relaxation and transverse relaxation rates can be extracted from fitting the CEST profiles. Therefore, CEST experiments provide per-atom information about the chemical exchange processes of the molecules. The overall principle of the CEST technique was established more than 50 years ago, but the application of CEST method in studying protein dynamics only became popular in very recent years. This is partly because of the growing awareness and interests in protein dynamics. The method is still under heated development to improve the accuracy or extend application in broader situations. There have been excellent extensions and demonstrations of the CEST methods in studying protein dynamics. 8

26 Figure 1-1. Simplified NMR spectra for a two-state (ground (G) and excited (E)) exchange system. Figure 1-. A simplified illustration of CEST experiments and expected results. (a) A weak B1 field is applied at a specific offset from the major state peak for a time TEX, followed by a 90 pulse and recording of the 15 N spectrum. Successive experiments step the weak field through the entire spectrum, and the intensity of the visible major-state peak is quantified as a function of offset to detect the position of the corresponding minor-state. When the B1 offset is far from either the major or minor state position, it has no effect on the spins of interest, and the intensity of the major state peak is unaffected relative to the case where B1 = 0 (b). When the offset is placed at major state, ω G, the signal of ground state will be saturated to be invisible. The interesting part is that when the offset is at the minor state, ω E, the signal of ground state decreases 9

27 but not fully saturated to be unobservable (d). This is because the saturation of E has been transferred to G via the -state chemical exchange. The amount of saturation transfer depends on exchange rates, equilibrium populations and other factors, and can be quantitatively described by Bloch equations The J-coupling effects on CEST experiments In CEST NMR experiments, uniformly 13 C or 13 C, 15 N labeled protein samples are often necessary for characterization of high energy states. The isotope labeling methods introduce the J-couplings effects among 13 C and 15 N spins which cannot be removed in existing CEST pulse schemes. Ignoring the splitting effects of J-coupling in CEST is not appropriate when J-coupled values are large. Therefore, here we will evaluate the J-coupling effects in CEST experiments. We propose and examine an approximation method of considering J-coupling effects The objectives The thesis work covers mainly from NMR methodology development to characterization of two different protein dynamic processes. The main objectives of the study are as the following: 1. To extend the application of CEST methods to more complex situations where J-coupling cannot be ignored, we propose and evaluate an approximation method to consider J-coupling effects in CEST NMR 10

28 experiments. The method will be constructed from theoretical derivation, evaluated by simulations and experimentally tested on meacp protein.. To provide a further understanding of the protein folding mechanism, we will investigate the folding dynamics of meacp protein by using the CEST NMR method. We will characterize the intermediate state of meacp as well as the transition state of meacp folding. 3. To help understand the mechanism of spider silk protein conformational transitions, we will study the dynamics of the spider silk protein RPmi by using CEST and CPMG techniques. 11

29 Chapter : Literature review 1

30 . Chapter : Literature review In this chapter, the current progress in different NMR methods to study molecular dynamics will be firstly reviewed, followed by the history of the development of CEST methods. Then I will review the literature on protein folding theories and summarize what we have known about the folding process of meacp. Because the transition state of protein folding can be indirectly characterized by quantifying the solvent effects on protein folding, which is also explored in this study, I will also review the deuterium water and urea effects on protein folding. At the end, I will review the literature on spider silk formation processes..1. NMR methods to study protein dynamics In this section, I will review several major NMR methods (hydrogen exchange NMR, CPMG relaxation dispersion and R 1ρ spin relaxation) that are used to study protein dynamics. A detailed review of the CEST method will be addressed in the next section. Nuclear magnetic resonance (NMR) spectroscopy, can provide rich information about the atoms or molecules, ranging from molecular structures, chemical environments of molecules to dynamics and reaction state and so on. NMR has been shown to be highly successful to determine structures of small proteins 13

31 and protein domains. Structures with a molecular weight of more than 50K ~ 100K, are generally considered difficult to be solved by solution NMR. By applying TROSY-based NMR techniques (TROSY: Transverse Relaxation Optimized SpectroscopY), it is possible to analyze the protein complex as large as 900K by NMR. (Fiaux, Bertelsen, Horwich, & Wuthrich, 00) Not only molecular structures, the dynamics of molecules such as proteins and RNA can be also studied at almost atom resolutions by NMR. Different NMR techniques have been developed, since the very first demonstration more than half a century ago of NMR study on chemical exchange processes. (Forsén & Hoffman, 1963) The hydrogen exchange (HX, or proton/deuterium amide hydrogen exchange NMR spectroscopy) is one of the few methods that are capable of characterizing protein dynamics and it is especially successful in studying protein folding processes. (Roder, Elöve, & Englander, 1988) The hydrogen-deuterium exchange (H/D exchange) is a chemical exchange process where a covalently bonded hydrogen atom (for example the amide hydrogen in the backbones of proteins) is replaced by a deuterium atom and vice versa. The H/D exchange processes during a protein folding process can be monitored by different methods such as NMR spectroscopy (Roder et al., 1988) and mass spectrometry (Wales & Engen, 006). The H/D exchange can, therefore, provide site-specific information when studying protein folding/unfolding equilibrium. 14

32 Another powerful NMR method that is widely used to study protein dynamics is the so-called Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion (RD) technique (Mulder, Mittermaier, Hon, Dahlquist, & Kay, 001). The method has been shown to be sensitive to minor excited conformations with a population as low as 0.5% provided that the exchange rates are on the microseconds to milliseconds timescale and there are large chemical shift differences between the ground native state and excited minor states. In a CPMG RD experiment, a conformational exchange between the native state and a minor state can make a contribution to the effective decay rate of the transverse magnetization (R eff ). The R eff value deceases with the increase of the repetition rate of the refocusing pulses, υ CPMG (Mulder et al., 001). A typical CPMG RD experiment consist of several individual measurements of R eff values with varied υ CPMG. A set of the estimated exchange parameters can be obtained by fitting the so-called CPMG RD profiles. Nowadays, with different isotope labelling schemes and CPMG RD pulse schemes, the chemical shifts of excited states in different positions of proteins ( 1 HN, 15 N, carbonyl 13 CO, 1 Hα, 13 Cα) can be extracted, therefore the detailed structure of excited states are ready to be solved (Philipp Neudecker, Lundström, & Kay, 009). R 1ρ spin relaxation in the rotating frame is another NMR technique that can be used to characterize chemical exchange processes occurring on the microsecond to millisecond time scale (Palmer & Massi, 006). 15

33 Comparing the NMR methods mentioned above, the CEST technique has one important advantage: the number of conformations (or states) in the exchange system can be readily observed in the CEST profiles. Therefore the assumption of number of states, which is necessary for methods such as CPMG RD and R 1ρ spin relaxation, can be avoid in CEST experiments. In methods such as CPMG RD, usually the two-state exchange model will be assumed, this assumption often agrees the data well. However, there is still possibility that additional minor states are ignored if only two-state model is used... The chemical exchange saturation transfer (CEST) In this section, I will review the history of the development of the CEST based NMR techniques and their applications...1. The CEST history In the early 1960s, Forsen and Hoffman first incorporate the idea and theory of saturation transfer into a nuclear magnetic double resonance method to determine chemical exchange rates (Forsén & Hoffman, 1963). The very simple idea of the saturation transfer is that when a molecular species is reversibly transformed between state A and B, a disturbance of the magnetization in state 16

34 B would be detectable at state A. Later, different extensions of this saturation transfer idea were demonstrated in studying varies types of chemical exchange reactions such as protein folding/unfolding, ligand binding, protein polymerization. In 1978, saturation transfer NMR were used to obtain assignments for the six heme c methyl resonances in ferricytochrome c (Keller & Wüthrich, 1978). 31 P saturation-transfer NMR experiments were designed to study the ATP synthesis (Matthews, Bland, Gadian, & Radda, 1981) and regulation of creatine kinase (Matthews, Bland, Gadian, & Radda, 198), a process which was also measured by 14 C and 15 N NMR saturation transfer methods (Brindle & Radda, 1985). The literature mentioned above mainly reported one-dimensional saturation transfer experiments on different chemical exchange processes, later in more recent years, the idea was further extended to two-dimensional saturation transfer experiments. The so-called saturation transfer difference (STD) NMR spectroscopy was first proposed in 1999 by B. Meyer and co-authors to characterize ligand binding activities with dissociation constants KD between 10-3 and (Mayer & Meyer, 1999) In the STD method, the on- and offresonance NMR (such as TOCSY) spectra were recorded separately, and the subtraction of on-resonance spectra from the off-resonance spectra gives a saturation difference spectra with signals for mapping ligand-binding sites. In 011, the so-called dark-state exchange saturation transfer (DEST) method, a 17

35 two-dimensional experiment, was used to study the exchange process between amyloid-β (Aβ) monomers and polydisperse, NMR-invisible ( dark ) protofibrils. The DEST experiment extracted the 15 N transverse relaxation rates for the protofibril-bound species per residue. Following the DEST experiments, Kay s group demonstrated the application of 15 N CEST experiments to quantify the slow exchange process and the chemical shifts of minor states (Vallurupalli et al., 01). The HSQC-based saturation transfer experiments were extended later to measure other isotope labeled spins in protein backbones (Alexandar L Hansen, Guillaume Bouvignies, & Lewis E Kay, 013; Vallurupalli & Kay, 013) and side-chains (Bouvignies, Vallurupalli, & Kay, 014). In the field of magnetic resonance imaging (MRI), the CEST class of techniques has also been extensively explored. Developing CEST-based MRI approaches has been popular in recent years (reviewed by (van Zijl & Yadav, 011)). In a study in 1989, the exchange between 1 H magnetization in free water ( 1 Hfree) and that with restricted motion ( 1 Hrestricted) was observed in tissues in vivo using saturation transfer methods (Wolff & Balaban, 1989). The study demonstrated the exchange is tissue-specific and can be used as a novel form of MRI contrast. Later, it was shown that a new class of exogenous contrast agent for MRI can be screened and built based on proton CEST (Ward, Aletras, & Balaban, 000). 18

36 ... J-coupling effects on CEST experiments Scalar or J- coupling, originating from the interactions between two nuclear spins which are connected through chemical bonds, is fundamental in magnetic resonance physics. J-coupling contains important information about the connectivity of the observed molecules. The J-coupling effects have therefore been important to develop multi-dimensional correlation NMR experiments. Different decoupling techniques have been developed to selectively eliminating or reducing the homonuclear or heteronuclear J-coupling effects, as the J- coupling effects can often complicate data analysis and reduce experimental sensitivity. For example, when a spin that is affected by a neighboring heteronuclear spin, a selective radio frequency irradiation can be applied to reduce the J-coupling effects of the neighbor. In a 15 N or 13 C CEST experiment, the heteronuclear J-coupling effects between 15 N/ 13 C and 1 H can be easily eliminated by applying the selective radio frequency irradiation on 1 H during the exchange time period (Vallurupalli et al., 01). However, the removal of the couplings between 15 N and 13 C spins and between 13 C spins is extremely difficult. The 13 CO based CEST experiment that has been recently reported (A. L. Hansen, G. Bouvignies, & L. E. Kay, 013) involves a coupled two-spin system in which the J-coupling effect was taken into account by considering the two 13 CO lines (due to the coupling of the adjacent 13 Cα) as not correlated. This idea of treating each line/peak of multiplet that arises from scalar coupling as an isolated spin was proposed and applied in a very recent work of applying 19

37 CEST to scalar coupled systems (protein side chains) (Bouvignies et al., 014). However, this method has not been evaluated rigorously..3. Protein folding In this section, I will review the history of our understanding advancement in the protein folding problem Protein folding theories An astonishing number of functions can be carried out in an organism by the equal amount of proteins with varied structures. The structures of proteins determine their functions. In order to maintain the functional activities, proteins must fold into their correct native structures. Folding intermediate states Although a general mechanism that applies to most of the protein folding remains missing (Dill & MacCallum, 01), our understanding of protein folding has advanced significantly in the past half-century, thanks to the increasing observations in different protein folding processes. More than 50 years ago, Anfinsen demonstrated that proteins can re-fold to most stable native state spontaneously, and concluded that the information for the native structure 0

38 of a protein is contained in its amino acid chain sequence itself (Anfinsen et al., 1961). Later on, Levinthal proposed the famous paradox (Levinthal s paradox) that because an unstructured polypeptide chain has astonishingly a large number (estimated as 3 n where n is amino acid number) of possible conformations, folding by random searching would take protein astonishing time to complete (Levinthal, 1969). As protein can fold fast (within microseconds), protein must fold through several intermediate states on the predetermined folding pathways. This classical view of protein folding brought up wide interests of experimental characterization of folding intermediate states over decades. Later studies of several proteins in the 1970 s and 1980 s (reviewed by (Baldwin, 1993)) demonstrated the existence of folding intermediates. The early evidence of protein folding intermediates tend to originate from studies on large protein. Unfolded forms of RNase A (Garel & Baldwin, 1973), lysozem (Kato, Okamura, Shimamoto, & Utiyama, 1981), cytochrome c (Ridge, Baldwin, & Labhardt, 1981) were found to exist as mixture of fast and slow-folding forms. The threestate (N-I-U) of folding equilibrium was observed in α -Lactalbumin (Kuwajima, Nitta, Yoneyama, & Sugai, 1976), penicillinase (Robson & Pain, 1976). Multiple disulfide intermediates on multiple pathways were found in BPTI (Creighton, Hillson, & Freedman, 1980). 1

39 Protein folding models Based on the experimental evidence of the folding intermediates and the idea of folding pathways, different models such as framework model (Udgaonkar & Baldwin, 1988), diffusion-collision (Karplus & Weaver, 1976), were generalized in the 1970 s and 1980 s. Most of the models agree the assumption that protein folding through one or several predetermined pathways. The framework model, it was proposed that a framework of stable native secondary structures are first formed, followed by forming of tertiary interactions that lead to the native structure of proteins. The framework model suggests predetermined folding pathways and the existence of folding intermediates that have at least several stable secondary structure units. The diffusion-collision model (Karplus & Weaver, 1979), similar to the framework model, the model assumes that a protein molecule has several units that are called microdomains. The native secondary structures of the microdomains can be rapidly formed by random searching. Those units are not stable, but their stability can be enhanced when two (or several) diffuse together and coalesce. Consequently, the microdomains diffuse together and collide into a native structure. The process may follow a single pathway or multiple different sequences of diffusion-collision steps.

40 The hydrophobic collapse model, it predicts that the non-specific collapsing of polypeptide chains happens before the formation of secondary and tertiary structure. While at the same time, many theoretical and experimental studies have also focused on folding mechanisms other than predetermined folding pathways to solve the Levinthal s paradox, that is, developing models that avoid to random search all the conformational space and that can explain experimentally measured fast folding kinetics. A different view that folding is via a large number of multiple parallel routes rather than single pathway were also proposed as an alternative to explain protein folding data (Karplus & Weaver, 1976). It was argued that solving Levinthal s paradox does not necessarily require predefined folding pathways. The jigsaw puzzle model (Harrison & Durbin, 1985), the multiple-pathways model states that the evolution of an amino-acid chain should favor the multiple paths to the single unique native state. This view is quite same with the funnel landscape view. Most of the models assume the importance of intermediates states on the folding pathway. However, in the early 1990 s, dozens of proteins, mostly small proteins, were found to fold rapidly in two-state, all or none, behaviors (Jackson, 3

41 1998). The absence of evidence of intermediate states for those proteins was often taken as the absence of intermediate states at all, to doubt that intermediate states may be unnecessary in directing protein folding (Fersht, 1995). Studying those small-protein folding was viewed as one of the keys to understanding the initial events of protein folding processes (Fersht, 1995). The so-called protein engineering method, based on site mutagenesis and ϕ-value analysis, was used to gain structural information of the transition state for fastfolding protein at high resolution. Based on ϕ -value analysis on different proteins, the nucleation-condensation model was brought up to describe the simple two-state fast-folding protein and it was also suggested to play a role in the foldon formation in the multiple-state slow folding process (Fersht, 1997). Different from the classical nucleation models (the framework model and diffusion-collision model), the nucleation-condensation model does not assume the must-existence of folding intermediate states. The nucleation-condensation model (Fersht, 1995), According to the nucleation-condensation model, a largely extended nucleus can be built up from the weak local nucleus that is stabilized by long-range interactions. The formation of the condensed nucleus will only be initiated once the transition state is reached. The consolidating of nucleus happens so rapidly that nucleus is not fully formed in the transition state. Therefore the formation of the nucleus 4

42 and the condensation are concurrent steps. Overall, those different models may touch different stages of protein folding processes, and even may be only valid for different types of proteins, but they may not be mutually exclusive. For instance, the hydrophobic collapse model and the nucleation-condensation model are mainly for describing the initial events of folding processes, while the framework model and diffusion-collision model are better suited to describe the whole folding processes for large protein. And it is often the case that experimental data can be explained by different models which may be fundamentally different from each other. There has been a long discussion on whether protein folding follows predetermined folding pathway(s) or a large number of parallel pathways (Baldwin, 1989). Later in the late 1990 s, this view of multiple parallel folding routes through funnel landscape stood out because of advances in both experimental and theoretical studies to replace the classic view of folding pathway (Dill & Chan, 1997). The folding funnel view states that the traditional predetermined-pathway concept of sequential folding should be replaced with the funnel concept of parallel folding events. The new view emphasizes the ensemble nature of protein conformations, seeing macroscopic states as ensembles of individual chain conformations during parallel folding events. 5

43 The off-pathway folding intermediates are an important species that cannot be ignored (Baldwin, 1996). An off-pathway product is often viewed as a misfolding intermediate that slows down protein folding. According to the folding funnel view, a traditional-viewed off-pathway state could be energetic traps that are direct and on-route for part of the chain population (Dill & Chan, 1997). The foldon hypothesis The debate on protein folding mechanism remains active, as no conclusive agreements can be reached. This partly due to the low resolution of observing methods, many studies only gave some nonspecific information about the intermediate states but failed to provide specific structural information about the intermediate states. Nevertheless, thanks to the advancement of imaging techniques such hydrogen exchange labeling NMR and mass spectrometry, more recent evidence has provided specific structural information of the intermediate states, supporting the classic view of predefined pathway intermediates (Englander & Mayne, 014). Englander and co-workers elegantly demonstrated cytochrome c and two-domain maltose binding protein (MBP) fold sequentially through partially unfolded forms (PUFs) using hydrogen exchange labeling NMR experiments and mass spectrometry (Hu et al., 013; 6

44 Maity, Maity, Krishna, Mayne, & Englander, 005). Following the classic view, they proposed the foldon hypothesis in which protein folds through several cooperative folding units called foldons, in a sequential pathway or few parallel folding pathways. They suggested this foldon hypothesis and funnel landscape view can be complementary to each other as they touch different parts of the folding mechanism (Englander & Mayne, 014). An off-pathway PUFs of apoavodoxin were identified recently, and was used as the evidence against the sequential nature of foldon theory (Bollen et al., 006). Later, Englander responded that an off-pathway misfolding PUF does not necessarily undermine the sequential folding theory as an off-pathway PUF may reflect a fraction of on-pathway products which occur to be misfolded (Englander & Mayne, 014). Overall, the foldon view of protein folding can resolve the Levinthal s paradox and be supported by recent results from HX- MS and HX-NMR. However, it still lacks enough experimental evidence and it will need more experimental supports from studies on different protein systems..3.. Folding studies of meacp protein The NMR structure (PDB code: l9f) of the ACP domain (meacp) of CalE8, was determined in 011, representing the first structure of a HR type I iterative PKS ACP domain (J. Lim et al., 011). meacp, 10 residues (molecular weight: 7

45 11. kd, including a His-tag), stays as a three-helix bundle with two long loops. The first evidence on the existence of folding/unfolding equilibrium of meacp came from the relaxation dispersion studies (J. Lim et al., 01), and later was more clearly demonstrated in the 15 N CEST experiment (J. Lim, Xiao, Fan, & Yang, 014b). What was interesting was that there exists an off-pathway folding intermediate state (I) in the folding equilibrium of meacp, as observed by the CEST experiment. But the structural features of this intermediate state I is mostly unknown. Figure -1. Multiple sequence alignment of meacp with selected type Ⅰ and type Ⅱ ACPs (J. Lim et al., 011). 8

46 Figure -. The NMR solution structure of meacp protein (J. Lim et al., 011) Solvent effects of deuterium water and urea on protein folding While protein molecules usually present in water solution, replacing water (HO) with heavy water (DO) is often necessary to avoid the interference of HO signal in many experiments such as nuclear magnetic resonance (NMR) and infrared (IR) spectroscopy. This replacement causes H/D isotope effect, which has been widely recognized. The H/D isotope effects, originating from the H bond and D bond energy difference, results in changes of solvent-solvent and solvent-protein interactions that are critical in protein folding. Most of the protein molecules are more stable (Table -1), more rigid (Cioni & Strambini, 00) and folds more rapidly (Parker & Clarke, 1997) in DO than in HO, because of stronger D bond than H bond in neutral water (Scheiner & Cuma, 1996), which may enhance the hydrophobic effects. 9

47 The H/D isotope effects on protein stability and folding rates have two origins: the replacement of protein backbone amide H by D (amide isotope effect) and replacement of solvent (solvent isotope effect). The amide isotope effect is caused by the difference of H-bonding and D-bonding associated with backbone NH and CO moieties. This effect destabilizes α-helical proteins but is negligible to β-sheet proteins (Krantz et al., 00). The extent of destabilization to a protein is correlated with the number of helical hydrogen bonds in the protein. On the other hand, the solvent isotope effect has been shown to stabilize a protein, which is independent of helical hydrogen bonding. Protei n Amide isotope effect Solvent isotope effect Total (ΔG ND D O Referenc es PDB code lengt h Volu me (ΔG ND D O (ΔG NH D O ΔG NH H O) rat CD RNas e A RNas e T1 ΔG NH D O) /kcal/m ol ΔG NH H O) /kcal/m ol /kcal/m ol ~ (Parker & Clarke, 1997) (Huyghue s- Despointe s, Scholtz, & Pace, 1999) (Huyghue s- Despointe s et al., 1CD B AA S 1BT A

48 NTL9 GCN4 coil 1999) 0.1(in or (Kuhlman HO) 0.67(N & 0.7(in H) (two Raleigh, DO) - methods 1998; 0.61(N ) Sato & D) Raleigh, 007) ~0.4 ~ (Krantz, Moran, Kentsis, & Sosnick, 000) LSZ (Efimova, Haemers, Wierczins ki, Norde, & Van Well, 007) BSA (Efimova et al., 007) HV F 1ZI K 1E8 L F5S Table -1. Isotope effects on different proteins. Amide isotope effect refers to the replacement of amide hydrogen NH with ND. Positive values of (ΔG ND D O ΔG NH D O) indicate NH is more stable than ND. Solvent isotope effect (ΔG NH D O ΔG NH H O) refers to the change of solvent from HO to DO without changing the amide hydrogen, the negative values of (ΔG NH D O more stable in DO. ΔG NH H O) shows proteins are As the D-bond of water is kcal/mol more stable than the H-bond (Scheiner & Cuma, 1996), the deuterium water provides a more rigid and compacting environment for protein, enhancing the hydrophobic interactions 31

49 noticeably through the solvent isotope effect. Urea is a widely used denaturant, while its mechanism of denaturing remains not clearly known. Studies suggest that urea denatures proteins by a direct interaction mechanism, as urea has preferential binding to all regions of proteins and can form H-bond with protein backbones (Hua, Zhou, Thirumalai, & Berne, 008; W. K. Lim, Rösgen, & Englander, 009). The interactions of denaturants like urea with proteins has been well shown to exist a linear dependence of Gibbs energy of unfolding ( G u ) on urea concentration [urea], the slope was given the symbol m: (Myers, Nick Pace, & Martin Scholtz, 1995) G u = G u (H O) + m [urea] (Eq. -1) It has been established and well accepted that the m value is proportional to the changes in accessible surface areas ( ASA) of protein unfolding (Myers et al., 1995). The co-solvents effects on protein folding include not only the energetics changes of different states, the effect results from structural interactions, but also the effects on the reaction rates due to the viscosity change of the solvent environment. The relationship between the folding reaction rates ( k f ) and solvent viscosity can be described by, (Ansari, Jones, Henry, Hofrichter, & Eaton, 199; Pabit, Roder, & Hagen, 004) 3

50 k f = A(σ + η) 1 e G RT (Eq. -) where A is the frequency factor for the folding process, σ refers to the internal friction, and η is the viscosity of solvent. The change of reaction rates by a co-solvent like urea comes from the change of viscosity (η) and/or the change of activation energy ( G, transition state energy level). The quantification of the solvent effects on the transition states (TS) of folding processes can provide indirect but valuable knowledge on protein folding. The so-called linear free energy relationships were firstly used in chemistry to locate the transition state along the reaction coordinate, and were later also used for the two-state protein folding processes (Ramos, Weisbuch, & Jamin, 007). Following a similar principle of the Φ-value analysis (Fersht, Matouschek, & Serrano, 199), which has been a widely used experimental method to characterize transition state of folding, the position of the transition state in protein folding can also be inferred by quantifying the stabilizing (or destabilizing) effects of co-solvents like urea on both the kinetics and the energetics of folding. From Eq. -1, the ratio of activation energy change to the Gibbs energy change is, φ = m m = ΔG ΔG (H O) G U F ΔG U F (H O) = ΔG (Eq. -3) GU F 33

51 The φ factor, or so-called Tanford s β value, is an indicator of average degree of changes of accessible surface areas ( ASA) in the transition state related to that in the unfolded state as protein folding (Ramos et al., 007). It should be noted that the measured effects should be corrected by excluding the viscosity effects of the solvent..4. Spider silk formation A female orb-weaving spider can produce and spin out seven different types of spider silk fibers from their corresponding silk glands to construct their orbwebs (Römer & Scheibel, 008). Each type of silk is built from one type of proteins. Synthesized and stored as an extremely high concentration of spidroins with no precipitation, the silk proteins transform into well-structured silk fibers as the spiders spin out the proteins from their glands. The assembly process of the spider silk proteins into silk fibers has been an interesting puzzle that researchers have been trying to solve. Of the seven types of silk proteins, the minor ampullate spidroins (MiSp) forms the temporary auxiliary spiral of the webs. The structure of C-terminal domain and repetitive domain of the MiSp was solved previously (Gao et al., 013). The study of the dynamics of spider silk proteins is, therefore, likely to provide an understanding of the silk fiber formation processes. 34

52 Figure -3. The NMR 1 H- 15 N assignment of RPmi protein (Gao, 013). Figure -4. The NMR solution structure of RPmi protein (Gao, 013). 35

53 Chapter 3: Materials and methods 36

54 3. Chapter 3: Materials and methods 3.1. Simulation test on the approximation method of J- coupling effects on CEST experiments To test the performance of our approximation method of describing weakly coupled multiple-spin systems as the sum of pseudo-spins, a weakly coupled hypothetical 15 N- 13 C system was used to simulate how kinetic parameters can be extracted accurately from CEST profiles. A number of CEST data sets were generated based on Eqs. 4-5, 4-9 and 4-10 (in chapter 4) with a series of J values at two weak RF fields applied to spin 15 N (15 and 30 Hz). In the generation of CEST data, the total exchange rate k ex (k ex = k AB +k BA ) was set as 50 s 1, population of minor state B (p B = k AB /k ex ) was 0.05, relaxation rates were: R 1A = 1 s 1, R 1B = 1 s 1, R A = 18 s 1, R B = 1 s 1, R mq = 30 s 1, dω(ω B Ω A ) = 5 ppm and δ N = η s = σ = 0, CEST saturation time was 0.5 s, offset for 13 C was zero, and offsets for 15 N were between ppm in an interval of 0.5 ppm (40.5 Hz on an 800 MHz spectrometer). For each J-coupling value, 100 sets of profiles with 1% random noise were repetitively generated. The synthesized data were used to extract kinetic parameters (k ex and p B ), chemical shift differences (dω) and relaxation rates (R 1A, R A and R B ) with three approaches by χ minimization. In the first approach, we employed Eqs. 4-9 and 4-10 to fit the data without any approximation. In the second approach, we used a single Eq. 4-8 to fit the data, which means we neglected the J-coupling 37

55 effect and considered 15 N as an isolated single spin. In the third approach, we used the sum of Eq. 4-8 with Ω A = Ω A + πj and Ω B = Ω B + πj and Eq. 4-8 with Ω A = Ω A πj and Ω B = Ω B πj to fit the data. In other words, we used two isolated pseudo-spins to represent the spin in a coupled two-spin system. Other parameters in Eq. 4-8 were assumed to be independent of Ω A and Ω B. In all simulations, J was not a fitting parameter but was assumed to be known; R 1B was assumed to be the same as R 1A, since the effect of R 1B on the extracted parameters is negligible (Vallurupalli et al., 01). The average and standard deviation of the parameters extracted from the 100 sets of profiles were reported. 38

56 3.. CEST experiments on ACP protein Different isotope labeled acyl carrier protein samples (Table 3-1) were prepared by following previous protocols (J. Lim et al., 011). All NMR samples contained 0.6~1 mm protein, 50 mm NaCl, 5 mm EDTA, 50 mm phosphate at ph 6.9. No. Sample Solvent Condition Experiment labeling 1 15 N, 13 C 95% HO, 5% DO 15 N CEST and CO CEST 13 C 95% HO, 5% DO 13 Cα CEST 3 13 C 100% DO 13 Cα CEST 4 13 C 95% HO, 5% DO M 13 Cα CEST urea 5 13 C 95% HO, 5% DO M 13 Cα CEST urea 6 15 N 95% HO, 5% DO 15 N CEST 7 15 N 95% HO, 5% DO M 15 N CEST urea 8 15 N 95% HO, 5% DO + 4 M urea 15 N CEST Table 3-1. CEST experiments. All CEST NMR experiments were performed on an 800 MHz NMR spectrometer equipped with a cryoprobe at 5 C. 15 N CEST experiments were carried out with two weak RF fields of 15 and 30 Hz. For each RF field, 49 D 1 H- 15 N HSQC spectra were acquired with a series of 15 N carrier frequencies ranging from 104 to 18 ppm at an interval of 0.5 ppm. Each D data set comprised complex points in the 1 H and 15 N dimensions and was recorded with 8 scans, an inter-scan delay of 1.3 s, a saturation time (TEX) of

57 s. A reference spectrum was also acquired using similar parameters except that TEX = 0 s. 13 CO CEST experiments were performed using the previous pulse scheme (Vallurupalli & Kay, 013) with two weak RF fields of 17.5 and 35 Hz. For each RF field, 38 D spectra were recorded with a series of 13 CO frequencies ranging from ppm to ppm at a spacing of 0.5 ppm. Each D data set comprised complex points in the 1 H and 15 N dimensions and was acquired with 16 scans, an inter-scan delay of 1.5 s, a saturation time (TEX) of 0.35 s and spectral widths of Hz for 1 H and 1930 Hz for 15 N. Similarly, a reference spectrum was acquired with TEX = 0 s. The total experimental times were 86 and 64 hours for 15 N and 13 CO CEST experiments, respectively. For 13 Cα CEST experiment, the NMR data were acquired with two weak RF fields of 17.6 and 35. Hz. For each RF field, 51 D HSQC spectra were acquired with a series of 13 C carrier frequencies ranging from 50. to 70. ppm at an interval of 0.4 ppm. Each D data set comprised 640x100 complex points in the 1 H and 13 C dimensions and was recorded with 4 scans, an inter-scan delay of 1.5 s, a saturation time (TEX) of 0.5 s, and spectral widths of 9615 Hz for 1 H and 404 Hz for 13 C. A reference spectrum was also acquired using similar parameters except that TEX = 0.05 s. The acquisition time in the 13 C dimension was 7.1 ms. The total experimental time was ~56 hours. 40

58 3.3. CEST Data analysis Pre-process of CEST raw data The CEST raw data consists of a series of ser files, which can be converted to HSQC spectra by using nmrpipe (Delaglio et al., 1995) software. The reference ser file was first converted to HSQC spectrum, and then the series of HSQC spectra in CEST data were generated by the same conversion settings as those for the reference, based on the raw data. In each of the HSQC spectrum, the peak intensities were quantified as the average of readings for ± X-axis points and ± Y-axis points, and then and normalized by the corresponding peak intensities in the reference spectrum. This was done by using the seriestab function in the nmrpipe program, which outputs a normalized intensity table for all the HSQC peaks Individual and global fitting using a two-state model The residues displaying two dips separated by more than 1 ppm were chosen to extract kinetics parameters. Their CEST profiles were first fitted individually using a two-state model (N U) to obtain parameters for each residue, i.e., folding and unfolding rates (k f, k u ), populations of the minor state (p u ), chemical shifts in the minor state (Ω U ), longitudinal relaxation rates of major (R 1N ) and minor states (R 1U ), transverse relaxation rates of the major (R N ) and 41

59 minor states (R U ). In the fitting, we assumed that 1 JCOCα = 55 Hz and 1 JCαCβ = 35 Hz for all residues in 13 C labelled protein samples, and for uniformly 13 C, 15 N- labeled sample, the J-coupling constants were assumed to be 1 JNCO = 15 Hz, 1 JNCa = 11 Hz, JNCa = 7 Hz and 1 JCOCa = 55 Hz for all residues (Juranic, Ilich, & Macura, 1995; J. M. Schmidt et al., 011); We set R U = R N and R 1U = R 1N for each residue. In global fitting, all residues shared a common exchange rate (k ex ) and a common population of the minor state (p u ), but they each had unique R 1N, R N, and Ω U values Individual fitting and global fitting using three-state models The procedure for fitting the CEST data of individual residues to three-state models (N U I, U N I and the triangle model) was the same as that described above. The residues displaying two and three dips were also fitted globally to the three-state models. In the fitting, we set R I = R U = R N and R 1I = R 1U = R 1N for each residue, and assumed 1 JCOCα = 55 Hz and 1 JCαCβ = 35 Hz in 13 C labelled protein samples and assume 1 JNCO = 15 Hz, 1 JNCa = 11 Hz, JNCa = 7 Hz and 1 JCOCa = 55 Hz for 13 C, 15 N-labeled sample. For residues displaying three well separated dips, Ω I was already certainly known, while for residues displaying two-dip profiles, Ω I should be close to either Ω N or 4

60 Ω U. Optimization was done by extensive grid-search of Ω I. To extract the Ω I value as accurate as possible, we used the following procedure: a. The Ω I of each residue was first estimated by individual fitting via grid search of Ω I ; b. Ω I values obtained in step a were used as the input values in the global fitting to obtain global exchange rates between states N and U (k 1 ) and between I and U or I and N (k ), populations of states N (p N ), and U (p u ); c. Ω I values were re-calculated by individual fitting with fixed global k 1, k, p N, p U values (obtained in step b); d. Repeat steps b and c, until χ of the global fitting decreased to a stable value Error estimation For each CEST profile, the uncertainty (δ) in intensity ratio (I/I 0 ) was estimated by calculating the standard deviation of data points in the non-saturation area. The following Monte Carlo simulations were used to estimate fitting errors of extracted CEST parameters for each residue: a. Generate 10 sets of profiles using extracted parameters, add random noise with a standard deviation of δ and mean of 0; b. The 10 set of profiles were fitted to extract 10 sets of fitting parameters. The standard deviation of each parameter was considered as the fitting error. 43

61 To determine global fitting errors, 80% of the residues used in the global fitting were randomly taken to extract global parameters and repeat 10 times to obtain standard deviations Energy calculation According to the population of each state, the Gibbs energy change ( G) of process A to B was calculated by G AB = RTln(p B p A ) (Eq. 3-1) where p A and p B are the populations of states A and B, respectively. The subscript AB is short for A B. The folding rate (k f ) is related to the activation energy ( G ) by (Ansari et al., 199; Pabit et al., 004) k f = A(σ + η) 1 e G RT (Eq. 3-) where A is the frequency factor for the folding process, σ refers to the internal friction, and η is the viscosity of solvent. 44

62 Cα NMR peak assignment for meacp protein in 4M urea The uniformly 13 C, 15 N-labeled meacp sample was purified and HNCA 3D NMR experiment was done on the 800 MHz NMR spectrometer. As the HN assignment of the denatured protein has already been completed previously (J. Lim et al., 014b), 13 Cα chemical shifts were assigned based on this HN chemical shift table, by using Sparky software (Goddard & Kneller, 004) Expression and purification of RPmi protein The pet3-derived expression vector for RPmi was previously constructed (Gao et al., 013). After transforming the vector into E.coli BL1, a single colony was inoculated into 10 ml LB medium containing 100 ug/ml ampicillin. Cultured at 37 overnight, the cells were then cultured in a 1L M9 medium which contained 15 N labeled NH4Cl and 13 C labeled (or non-labeled) glucose as the sole nitrogen and carbon source. When the OD600 reached ~0.6, the cells were induced with 0.5 mm IPTG, and shifted to 0 and cultured for ~18 hours. The cells were harvested from the 1L culture, and then re-suspended in 40 ml lysis buffer (10 mm Tris, 100 mm NaCl, ph 8.0) and sonicated thoroughly, and then centrifuged at 18000g for 30 minutes. The overexpressed proteins were 45

63 mainly in the supernatant. The supernatant of lysate was loaded into a ~10 ml Ni-NTA resin column. After ~3 hours binding, the resin was washed with 80 ml wash buffer (10 mm Tris, 100 mm NaCl, 0 mm imidazole ph 8.0), and then eluted out by 40 ml elution buffer (10 mm Tris, 100 mm NaCl, 300 mm imidazole, ph 8.0). The buffer condition of elution was later changed to 10 mm Tris, 10 mm NaCl, 1mM EDTA, ph 7.0 by dialysis, for the following ion exchange purification step. In the ion exchange purification step, buffer A (10 mm Tris, 1 mm EDTA, ph 7.0) and buffer B (10 mm Tris, 1 M NaCl, 1 mm EDTA, ph 7.0) were first prepared. After injecting the protein sample into the monoq column, the protein will bind to the column under 100% buffer A. As increasing the percentage of buffer B from 0% to 100%, the protein will be eluted out when buffer B reached ~10%, corresponding to a salt concentration ~100 mm. The protein sample was further purified by gel filtration column (buffer condition: 10 mm Tris, 100 mm NaCl, mm EDTA, ph 7.0) and finally concentrated using a centrifugal filter with the 3kD cutoff membrane at a centrifugal force of 3000 g. The final concentration should be ~10 mg/ml, determined by Nanodrop N CEST experiment on RPmi The 15 N CEST experiment as well as the CEST data analysis on RPmi protein, was same as the previously described on meacp protein except that the rf 46

64 frequency range was 105 ~18.5 ppm with an interval of 0.5 ppm The CPMG experiment on RPmi The CPMG experiment was only conducted on Bruker 800 MHz machine using the pulse scheme proposed previously (Jiang, Yu, Zhang, Liu, & Yang, 015). In the experiment, a constant time delay (TCPMG = 30 ms) was used with a series of CPMG field strengths (νcpmg = 33.3, 66.7, 100, 133.3, 166.7, 00, 66.7, 333.3, 400, 533.3, 666.7, 800, 1000, 100, 1400, 1600, 1800, 000 Hz). Each D data set comprised complex points in the 1 H and 15 N dimensions. The D data was recorded with 16 scans and inter-scan delay of s. The experiments at νcpmg of 60 Hz were repeated once more for estimation of experimental errors. As the longitudinal relaxation T1 and transverse relaxation T values were needed for the R eff values corrections. (Jiang et al., 015). T1 and T1 ρ experiments were done to obtain relaxation rates R1 and R 1ρ values, respectively, by following protocols described elsewhere. (Palmer 3rd, Kroenke, & Loria, 001). Based on the R1 and R1ρ values, the R values were calculated by, R1ρ = R cos (θ) + R 1 sin (θ) (Eq. 3-3) where θ = tan 1 ( π υ γb 1 ), where Δν is the resonance offset and γb 1 is the strength of the spin-lock field. 47

65 Chapter 4: Results and discussion 48

66 4. Chapter 4: Results and discussion 4.1. The J-coupling approximation method in CEST experiments Theoretical derivation of considering J-coupling effects on CEST experiments For a single nuclear spin system, the time evolution of density operators is described by: (Ernst, Bodenhausen, & Wokaun, 1991) d dt [ E/ I + I ] = I z [ R iω 0 + iω R + iω iω 1 R 1 M eq iω 1 / iω + 1 / R 1 ] E/ I [ + I ] (Eq. 4-1) I z where E is the unit operator, I + = I x + ii y and I = I x ii y, I x, I y and I z are the x, y, and z components of angular momentum operator I, R 1 and R are the longitudinal and transverse relaxation rates, Meq is the equilibrium magnetization, Ω is the offset of the radiofrequency (RF) field applied to the + system from the resonant frequency of the spin, ω 1 = γb 1 e +iφ, ω 1 = γb 1 e iφ, B 1 and φ are the strength and phase of the applied RF field, respectively, and γ is the gyromagnetic ratio of the spin. In the experiment of CEST (Vallurupalli et al., 01) or R 1 measurement (Kay, Torchia, & Bax, 1989), one often aligns alternatively the magnetization along the +z axis and z axis just before the CEST period or relaxation delay (or at time zero) and 49

67 inverts the receiver phase every the other scan. In this way, the observed values for [E/ I + I I z ] are [0 0 0 c] at time zero, where c is a constant. When E(0)=0, Eq. 4-1 is reduced into d I+ [ I dt + R iω 0 iω 1 I + ] = [ 0 R + iω iω 1 ] [ I ] (Eq 4-) I z iω 1 / iω + 1 / R 1 I z For a weakly coupled system of two spins (I and S), a complete base set is formed by the following 16 operators: [E/ I + S α I S α I z S α I + S β I S β I z S β I α S + I α S I β S + I β S S z I + S I S + I + S + I S ], where I α = E/ + I z, I β = E/ I z, S α = E/ + S z and S β = E/ S z. Due to the J-coupling between spins I and S, spin I gives rise to two lines (peaks). The magnetizations for the down-field line correspond to [ I + S α I S α I z S α ], while those for the up-field line corresponds to [I + S β I S β I z S β ]. Under the initial condition of E(0)=0, the evolution of the operators is given by d dt M = R M (Eq 4-3) where M is a 15 1 column vector, M = [ I + S α I S α I z S α I + S β I S β I z S β I α S + I α S I β S + I β S S z I + S I S + I + S + I S ] t (Eq 4-4) t is the transpose operator, R is a matrix derived from the matrix (Allard, Helgstrand, & Härd, 1997, 1998; Helgstrand, Härd, & Allard, 000) based on Cartesian spin operators. 50

68 R = [ + D 1 0 iω 1I R 1S 0 D iω 1I 0 R 1S iω 1I R 1S iω + 1I 0 R 1S D R 1S iω 1S iω 1S 4 iω 1S + 4 iω 1S 4 + iω 1S 4 (σ+δ S ) D 4 0 iω 1I R 1S D 5 iω 1I iω 1S + iω 1S 0 0 iω 1S iω 1S 0 0 iω 1S iω 1I iω + 1I D iω 1S iω 1S + iω 1S 0 0 iω 1S iω 1S 4 + iω 1S 4 iω 1S 4 D 7 0 R 1I iω 1S D 8 0 R 1I R 1I 0 0 σ + δ S 0 0 σ δ S iω 1S iω 1S 0 + iω 1S iω 1S 0 iω 1S iω 1S 0 0 iω 1S 0 0 iω 1S R 1I iω 1S 0 iω 1I + iω 1I 0 0 D 9 0 iω 1S + + iω 1I iω 1I (σ δ S ) + iω 1S iω 1S + iω 1S 0 D 10 iω 1S iω 1S iω 1S iω 1I iω 1I + 0 iω 1I 0 0 iω 1S iω 1S iω 1S iω 1S 0 iω 1S iω 1S iω + 1I iω 1I 0 iω 1I iω 1I iω 1I + iω 1I iω 1I iω 1I D D D D 14 0 iω 1I D 15 ] (Eq 4-5) 51

69 In Eq. 4-5, ω 1I (ω 1S ) is the RF field (in radius) applied to spin I (S); R 1I (R 1S ) is the longitudinal relaxation rate of spin I (S); σ is the cross-relaxation rate between I z and S z. δ s and η s are the longitudinal and transverse cross-correlation relaxation rates attributed to the interaction between dipole IS and chemical shift anisotropy (CSA) of spin S. Under the following approximations: R I a R I + R 1S (Eq 4-6) R S a R S + R 1I (Eq 4-7) R IS R 1I + R 1S (Eq 4-8) where R I a (R S a ) is the relaxation rate for I + S z (I z S + ) or I S z (I z S ), RI (RS) is the transverse relaxation of spin I, R IS is the relaxation rate for I z S z, and the diagonal elements are given by D 1 D D 3 D 4 D 5 D 6 D 7 D 8 D 9 D 10 D 11 D 1 D 13 D 14 [ D 15 ] = [ R I + 0.5R 1s i (Ω I + πj) R I + 0.5R 1s + i (Ω I + πj) R 1I + 0.5R 1s R I + 0.5R 1s i (Ω I πj) R I + 0.5R 1s + i (Ω I πj) R 1I + 0.5R 1s R S + 0.5R 1I + η S i (Ω S + πj) R S + 0.5R 1I + η S + i (Ω S + πj) R S + 0.5R 1I η S i (Ω S πj) R S + 0.5R 1I η S + i (Ω S πj) R 1S R mq μ mq i (Ω I Ω S ) R mq μ mq + i (Ω I Ω S ) R mq + μ mq i (Ω I + Ω S ) R mq + μ mq + i (Ω I + Ω S ) ] (Eq 4-9) where J is the scalar coupling constant between spins I and S, R mq is the relaxation rate for multiple quantum coherences (I + S + and I + S ); μ mq is the cross-relaxation rate between double and zero coherences. 5

70 The matrix in Eq. 4-5 can be partitioned into nine blocks (four 3 3, two 3 9, two 9 3 and one 9 9 blocks). The first block R11 and fifth block R represent the matrices for the down-field and up-field lines of spin I, respectively, which each are equivalent to the matrix in Eq. 4-. When a weak B1 field is applied only to spin I (i.e., ω 1S = 0), R1S << J, σ << J and δ s << J, all elements in block R1, R13, R1, R3, R31 and R3 can be approximated as zero, indicating that the two lines of spin I evolve independently. Thus the two lines can be approximately considered as two isolated pseudo-spins with offsets at Ω I + πj and Ω I πj, respectively. In this way, the evolution of spin I can be treated as the sum of the evolution of two coupled pseudospins described using Eq. 4-. Similarly, the evolution of a spin (spin A) in a multiplespin system can be treated as the sum of the evolution of multiple isolated spins under the same approximation condition as that for the two-spin system. According to the J- coupling rule, one easily determines the number of uncoupled pseudo-spins and their frequencies which are needed for describing spin A. For instance, spin A in a weakly coupled AMXW spin system gives rise to eight lines at π(±jam±jax±jaw), thus the evolution of spin A can be considered as the sum of eight isolated spins resonant at these frequencies. For spin systems involving only 13 C and 15 N spins, the approximation condition (R1S << J, σ << J and δ s << J) is always met. Thus the approximation method shown here shall be suitable for CEST data analysis. 53

71 k AB For a single spin system exchanging between two states A and B (A B), the evolution k BA of the operators under the initial condition of E(0) = 0 is given by d dt I A + I A I za I B + I B [ I zb ] R A iω + k AB A 0 + iω 1A k BA I A 0 R A + iω A + k AB iω 1A 0 k BA 0 I A = iω 1A / iω 1A / R 1A + k AB 0 0 k BA I za k AB 0 0 R B iω B + k BA 0 + iω 1A + I B 0 k AB 0 0 R B + iω B + k BA iω 1A I B [ 0 0 k AB iω 1A / iω 1A / R 1B + k BA ] [ I zb ] (Eq 4-10) In the presence of conformational or chemical exchange, a weakly coupled spin system can also be approximated as the sum of isolated pseudo-spins. Without approximation, the evolution of a weakly coupled I-S system is given by d dt M = L M (Eq 4-11) where M = MA MB, MA (MB) is the vector for an I-S system in state A (B) given in Eq. 4-4, denotes direct sum, and matrix L is described by L = [ R R ] + [ k AB k BA ] 1 k AB k 15 (Eq 4-1) BA Here R is assumed to be the same in states A and B and is given by Eq. 4-5, 015 (115) is a null (identity) matrix. 54

72 4.1.. Simulation test of the J-coupling approximation method on CEST experiments When the data synthesized with Eqs and 4-1 were fitted back to the same equations, values of k ex and p B obtained were 50 s 1 and 5% for all J-coupling constants (Figure 4-1), respectively, which were the same as the input values as expected. When the data were fitted using the J-coupling-neglected approach based on a single Eq (i.e., neglecting J-coupling), the deviations of the obtained k ex and p B values from their respective input values increased with the J-coupling (Figure 4-1). The result shows that the J-coupling effect must be taken into account in order to obtain accurate kinetics parameters, especially when the coupling value is larger than 15 Hz. When the data were fitted using the J-coupling-considered approach (i.e., considering each line/peak of a multiplet as an isolated pseudo-spin), the k ex and p B values obtained were nearly identical to the input values (Figure 4-1). Even when the J-coupling value used in the fitting deviated by ±3 Hz from that used to synthesize the data, the deviations in extracted k ex and p B were smaller than 1.5%. The results demonstrate that the kinetics parameters for an I-S two-spin system can be accurately extracted from the CEST data of spin I by treating spin I in the coupled system as the sum of two uncoupled pseudo-spins resonant at δ I + πj and δ I πj. The method can be extended to any weakly coupled multiple-spin systems. 55

73 Figure 4-1. Dependences of extracted k ex (a) and p B (b) on the J-coupling of a twospin system. The synthesized CEST profiles with 1% Gaussian noise were fitted by three methods: 1. accurate method without approximation (dotted line),. J-couplingneglected method (filled dot), and 3. J-coupling-considered method (filled square). The error bars represent standard deviations of k ex and p B which were extracted from 100 sets of profiles Experimental test of the J-coupling approximation method By performing CEST experiments on a 15 N-labeled meacp sample, it was demonstrated previously (J. Lim et al., 014b) that meacp exists in three states: one major folded (N) form (~ 95.%), one unfolded (U) form (~4.1%) and one intermediate (I) form (~0.7%). The three states are in a dynamic equilibrium and the intermediate state is an off-pathway folding product rather than an on-pathway product under native conditions. Here we used a 13 C, 15 N-labeled sample to show the effect of J-coupling on the extraction of kinetics parameters. Although 1 JNCO, 1 JNCa, JNCa and 1 JCOCa vary from one residue to another in a protein, the small variation (<±3 Hz) causes negligible changes in the extracted kinetics parameters as shown in Figure 4-1. Thus, all the couplings were assumed to be independent of amino acid types and structure in our data analysis N and 1 13 CO CEST profiles displayed two obvious dips and were fitted 56

74 individually to a two-state model. The k ex extracted from the 15 N data by neglecting J-couplings was about 10 s 1 larger than that obtained by considering the J-couplings, while the p B by the former method is ~0.04% smaller than that by the latter method (Figure 4-). The differences in k ex and p B extracted from the 13 CO data by the two methods were about 70 s 1 and 0.%, respectively. Figure 4-. Distribution of k ex and p B values extracted from individual fits of 4 15 N CEST profiles (a) and 1 13 CO CEST profiles (b) using the J-coupling-neglected method (grey dot) and J-coupling-considered method (black square). When the 15 N CEST data were fitted simultaneously, the global k ex and p B extracted using the J-coupling-considered method were 75 ± 3 s 1 and 3.85 ± 0.0%, while they were 83 s 1 and 3.8% using the J-coupling-neglected method. The goodness of the fits by the two methods was similar since the reduced χ (χ red ) values were 1.17 and 1.5 by the former and latter methods, respectively. The k ex value obtained here is significantly larger than that extracted from 15 N-labeled meacp (18 s 1 ). The difference may come from 13 C labeling or/and slight difference in sample buffers since the HSQC spectra of the two samples were slightly different. When the 1 13 CO CEST profiles were fitted globally, the resultant k ex and p B were 93 ± 4 s -1 and 3.60 ± 0.04% by the J-coupling-considered method, while they were 367 s -1 57

75 and 3.4% by the J-coupling-neglected method. The goodness of the fit by the J- coupling-neglected method (χ red =.3) was much worse than that by the J-coupling- considered method (χ red =1.). The systematic differences between the two methods are consistent with the simulation results (Figure 4-1). Note that the separation of the two outer lines in the 15 N multiplets is about 33 Hz and it is about 70 Hz in the 13 CO multiplets. Therefore, the coupling effect should be considered in the CEST data analysis when the total coupling is larger than 15 Hz. Otherwise, overestimated k ex and underestimated p B values will be obtained. 4.. The hidden intermediate state I of meacp Evidence of the state I When the J-coupling effect was taken into account, the global k ex and p B values obtained from the 15 N CEST data were expected to be the same as those from the 13 CO data because they were derived using the same 13 C, 15 N-labeled sample. Indeed they were consistent, but there was a difference of ~18 s 1 in k ex, which was larger than the errors (< 6 s -1 ). Moreover, spins 15 Ni and 13 COi-1 which are located on the same peptide bond (rotation around this bond is extremely difficult) are expected to undergo same or similar dynamics, but the difference of individual k ex values obtained from spins 15 Ni and 13 COi-1 ranged from -40 to +100 s 1 (see Table 4-). Such a large variation cannot be explained by experimental errors in CEST intensities and small 58

76 deviations of the J-couplings used from the true values. One possible interpretation is the presence of a second minor state. Table 4-1. Individual k ex and p B values extracted from 15 N or 13 CO CEST data. RESIDUE 15 N i ( 13 CO i 1 ) 15 N CEST DATA 13 CO CEST DATA k ex (s 1 ) p B (%) k ex (s 1 ) p B (%) L939(A938)* E940(L939) L941(E940) R943(V94) H944(R943) L945(H944) V946(L945) A947(V946) R949(E948) A950(R949) E951(A950) L95(E951) V954(P953) E955(V954) V956(E955) R958(L957) D960(D959) S961(D960) F963(R96) D965(L964) D966(D965) L967(D966) H968(L967) S970(M969) I97(S971) V974(T973) G975(V974) Q976(G975) N979(V978) T998(A997) E1003(R100) E1006(A1005) A1007(E1006) L1008(A1007) A1010(E1009)

77 *Spin 13 COi-1 in residue i-1 and 15 Ni in residue i are indicated inside outside the parentheses on each row, respectively. Since 15 Ni and 13 COi-1 are in the same peptide bond, results from the same peptide bonds were aligned on the same row for comparison. Figure 4-3. Examples of CEST profiles for spins belong to same amino acids or peptide bonds. (a) and (b): 13 CO and 15 N CEST profiles for H968; (c) and (d): profiles for T973; (e) 13 CO profiles for A98; (f): 15 N profiles for R983. (e) and (f) are in the same peptide bond. Dots: experimental CEST data from 15 N, 13 C-labelled meacp sample; Lines: fitting results based two-state or three-state (N U I, for a-c) models. Cases were observed where 15 Ni CEST profiles display three dips while the corresponding 13 COi or (and) 13 COi-1 CEST profiles only showed two observable dips (See Figure 4-3). In these cases, the chemical shift of spin 13 COi in the second minor state might be close to that in either the first minor state or major state. In other words, the third state I may be hidden (overlapping) in the dips for state N or state U. To obtain the information of exchange from the 13 Cα spin, we designed a new 13 Cα CEST pulse scheme (Zhou & Yang, 015), for uniformly 13 C- or 13 C, 15 N-labeled samples in either water or heavy water (see HSQC spectrum in Figure 4-4). We later applied the 13 Cα CEST method on the meacp samples in different solvent conditions 60

78 to get the information from the 13 Cα of meacp as well as the solvent effects on the folding process of meacp. Figure Cα CEST 1 H- 13 C correlation spectrum of meacp in 95% HO and 5% DO. The noise in the region around 4.73 ppm is from residual water signals. 13 Cα CEST experiments on meacp in HO, DO, HO M urea, and HO M urea were performed. 43 residues displayed two dips in their 13 Cα CEST profiles, showing those residues existed in at least two forms. 61

79 Figure 4-5. (a) Number of states that each Ca spin occupies. (b) Examples of CEST profiles with different states are colored correspondingly. Profiles with two weak RF field of 15 and 30 Hz are in dark and light color, respectively (see methods). Regions uncertain are colored in gray. As demonstrated previously on the basis of chemical shifts, the minor form was mainly unfolded (U) with α-helical propensity (J. Lim et al., 014b; Zhou & Yang, 015). While for several residues, a third state (I) was clearly seen in their CEST profiles (Figure 4-6 and Figure 4-7). 6

80 Figure 4-6. Representative 13 Cα CEST profiles in HO, DO, 0.5 M and 0.5 M urea. RF weak field used in the three experiments was ω1 = 15 Hz. Solid lines are the best fits. Figure 4-7. Representative 15 N CEST profiles in HO and 0.5 M urea. For the residues displaying two-dip CEST profiles, we first performed individual fitting using the two-state model. The extracted populations of state U (p u ) are shown in Figure 4-8 ( 13 Cα CEST, see 15 N CEST in Figure 4-9). Of great interest, the average p u values for the residues in the C-terminal half region (helix, helix 3: from V974 to 63

81 A1010) were larger than those for the residues in the N-terminal half region (helix 1 and loop 1: from A938 to I97). The p-tests confirmed that the differences were significant. The population differences between the two regions showed that the folding of meacp was not globally all or none. Is there a partially folded state where the C- terminal region remains folded while the N-terminal region is unfolded? Figure 4-8. Population of state U p u (a), the p u distribution of the two half regions (N-terminal: red; C-terminal: grey) of meacp in DO (b), HO (c), 0.5 M urea (d) and 0.5 M urea (e). Figure 4-9. Population of state U (p u ) extracted from individual 15 N CEST profiles 64