16 NMR Investigations on Ruggedness of Native State Energy Landscape in Folded Proteins

The ability of proteins to adopt their functional, highly structured states in the intracellular environment during and after its synthesis is one of the most remarkable evolutionary achievements of biology. Deciphering the code of protein self-organization process has been an intellectual challenge for scientists over the past few decades. Although the structurefunction paradigm about folded structures and functions remains valid, the role of internal dynamics and conformational fluctuations in protein function is becoming increasingly evident (Bhabha et al 2011; Boehr et al 2006; Eisenmesser et al 2005; Fraser et al 2009; Mittermaier and Kay 2006; Parak 2003b; Popovych et al 2006; Tzeng and Kalodimos 2009; Whitten et al 2005). Further, recent structural and genomic data have clearly shown that not all proteins have unique folded structures under normal physiological conditions. Hence, the way a protein exists, is bound to have a profound effect on its function.


Introduction
The ability of proteins to adopt their functional, highly structured states in the intracellular environment during and after its synthesis is one of the most remarkable evolutionary achievements of biology.Deciphering the code of protein self-organization process has been an intellectual challenge for scientists over the past few decades.Although the structurefunction paradigm about folded structures and functions remains valid, the role of internal dynamics and conformational fluctuations in protein function is becoming increasingly evident (Bhabha et al 2011;Boehr et al 2006;Eisenmesser et al 2005;Fraser et al 2009;Mittermaier and Kay 2006;Parak 2003b;Popovych et al 2006;Tzeng and Kalodimos 2009;Whitten et al 2005).Further, recent structural and genomic data have clearly shown that not all proteins have unique folded structures under normal physiological conditions.Hence, the way a protein exists, is bound to have a profound effect on its function.
A complete understanding of protein folding process requires characterization of all the species populating along the folding coordinate, these include the unfolded state, the partially folded intermediate states, low energy excited states and the fully folded native state.The most recent and widely accepted model is the 'funnel view' of protein folding (Bryngelson et al 1995;Dill and Chan 1997;Onuchic et al 1997;Shoemaker et al 1999;Wolynes 2005) also known as the 'Energy landscape model' (Fig. 1), which is inclusive of the earlier concepts of 'folding pathways'.According to this model protein folding is a parallel, diffusion-like motion of conformational ensemble on the energy landscape biased towards the native state.This model is free from the Levinthal paradox (Dill and Chan 1997;Levinthal C 1969) as it envisages the process of reaching a global minimum in free energy as a rapid process occurring by multiple routes on a funnel like energy landscape (Fig. 1).This view focuses on the rapid decrease of the conformational heterogeneity in the course of the folding reaction and is based on a statistical description of a protein's potential surface (Wolynes et al 1995;Wolynes 2005).The depth in the funnel represents the free energy of the polypeptide chain in fixed conformations and the width indicates the chain entropy (Fig. 1).The funnel becomes narrower in the lower energy region because of the low chain entropy.The broad end of the funnel reflects the heterogeneous unfolded state, while the narrow end represents the supposedly homogeneous native state (Dill and Chan 1997;Dobson and Karplus 1999;Dyson and Wright 2005).Different members of the ensemble may fold/unfold along independent pathways and their energy profiles could be different.Protein folding theories start from the unfolded state (Fig. 1) and encompass a range of topologies like the pre-molten globule, the molten globule and various other ordered or disordered forms as the protein folds down the funnel (Dunker et al 2002;Uversky 2002;Uversky 2003).Fig. 1.A schematic energy landscape view of protein folding: The surface of the funnel represents a whole range from the multitude of denatured conformations to the unique native structure (Dill and Chan 1997).The ordered state is the natively folded structure of a protein that has a well defined secondary and tertiary structure.Alternative conformations are higher energy native state conformations and contain all the secondary and tertiary structural characteristics of folded state.Molten globule states are intermediates in the protein folding pathway with compact structures that exhibit a high content of secondary structure, nonspecific tertiary structure, and significant structural flexibility.Random coils are highly unstructured protein denatured states.
In a living cell, a polypeptide chain chooses between three potential fates -functional folding, potentially deadly misfolding and mysterious non-folding (Dobson 2003).This choice is dictated by the peculiarities of amino acid sequence and/or by the pressure of environmental factors.The biological function of a protein arises as a result of interplay between specific conformational forms, namely, native state (ordered forms), low energy excited states, molten globules, pre-molten globules, and denatured state (random coils).In view of this, it will not be an exaggeration to assume an ensemble existence of all these states at any particular time, their relative abundance being governed by basic thermodynamics.Upon ligand binding or some signaling modification, concentration of one state may increase at the expense of the others.This can explain the fast regulatory steps involved in various biological functions.
Much of structural biology of proteins is so focused on studies of native state, providing detailed atomic descriptions and coordinates of static three-dimensional (3D) structures.A large body of evidence using a diverse spectrum of biophysical methods clearly establishes that proteins are dynamic over a broad range of timescales and such dynamics play critical roles in various biological processes, such as: initial formation of encounter complexes in macromolecular association, target searching in specific protein-protein/protein-DNA recognition, conformational preferences in ligand binding, conformational transitions associated with allostery, the course of enzyme catalysis, intermediates along the protein folding pathway, and early events in self-assembly processes (Bai et al 1995;Boehr et al 2006;Clore 2011;Dunker et al 2002;Eisenmesser et al 2005;Feher and Cavanagh 1999;Fraser et al 2009;Kitahara et al 2005;Korzhnev et al 2003;Kumar et al 2007;Lambers et al 2006;Mohan et al 2006;Piana et al 2002;Popovych et al 2006;Tang et al 2008;Villali and Kern 2010).The amplitudes and the timescales of motion that characterize the dynamics of a protein under a given set of conditions can be understood in terms of an 'energy landscape' as described above.Ground-state conformers that occupy the bottom of the energy landscape funnel and are separated from other conformational states by very small kinetic barriers that are easily overcome by thermal energy form the basis of structural studies by NMR (Nuclear Magnetic Resonance Spectroscopy) and X-ray diffraction for last few decades.
In general, the dynamic phenomenon involves the inter-conversion between ground state conformers with higher energy structures known as 'excited states'.The populations of these low-energy excited states/near native states/alternative conformations at equilibrium are very sparse and their lifetimes are short.Moreover, these transient states arising from rare but rapid excursions between the global free energy minimum and higher free energy local minima are extremely challenging to study at atomic resolution under equilibrium conditions since they are effectively invisible to most structural and biophysical techniques including crystallography and conventional NMR spectroscopy (Bhabha et al 2011;Boehr et al 2006;Eisenmesser et al 2005;Fraser et al 2009;Mittermaier and Kay 2006;Popovych et al 2006;Tzeng and Kalodimos 2009;Whitten et al 2005;Clore and Iwahara 2009;Clore 2011).However, a complete understanding of the conformational fluctuations these bio-molecules undergo is essential to gain an insight into their biochemical and biophysical properties.Hence, it is critical to characterize the structural ensembles that describe these functionally important states and the mechanisms by which they interconvert with the ground-state conformers.
such as paramagnetic relaxation enhancement (PRE) (Clore and Iwahara 2009;Clore 2011), relaxation dispersion (RD) (Boehr et al 2006;Mittermaier and Kay 2006;Tzeng and Kalodimos 2009) and non-linear temperature dependence of amide proton chemical shifts (Krishna Mohan et al 2008;Mohan et al 2008b;Tunnicliffe et al 2005;Williamson 2003) have emerged and significantly contributed to our understanding of the relationship between structure, dynamics and function of proteins with respect to the excited-state conformers that are sparsely populated and often exist transiently.
In the present chapter the theoretical basis of NMR approach for the curved temperature dependence of amide proton chemical shifts will be discussed in detail.Theoretical simulations will be presented to understand the nature and extent of curvature of the chemical shifts.Further, experimental studies performed till date on different protein systems will be reviewed to demonstrate the curved temperature dependence of amide proton chemical shifts as a tool to detect the low populated near native states/ alternative conformations of the protein residues.Moreover, the significance of these conformational fluctuations will be evaluated with regard to protein function and folding.

Theory of curved temperature dependence of amide proton chemical shifts
NMR chemical shift is a sensitive indicator of the environment and molecular conformation.In proteins 1 H, 13 C and 15 N chemical shifts are sensitive to protein secondary structures and are used to deduce the preliminary structural information (Schwarzinger et al 2000;Schwarzinger et al 2001;Wishart and Sykes 1994;Wishart et al 1995;Wüthrich K 1986).The temperature dependence of amide proton chemical shifts in globular proteins has been investigated for over more than three decades by many researchers and continues to be investigated even today (Anderson et al 1997;Baxter and Williamson 1997;Cierpicki and Otlewski 2001;Krishna Mohan et al 2008).The amide proton chemical shifts are directly proportional to bond magnetic anisotropy (σ ani ) and this is crucially dependent on H-bonding, either intramolecular or intermolecular.In the former case, the carbonyl groups, the H-bond acceptors play a crucial role.The bond magnetic anisotropy is proportional to r -3 where r is the distance between the affected amide proton and the centre of the bond magnetic anisotropy, which lies close to the oxygen atom in the carbonyl groups (Krishna Mohan et al 2008).In case of solvent accessible groups, H-bonding with solvent molecules influences the amide proton chemical shifts.Thus the amide proton chemical shift is critically dependent on the length of the H-bond the proton is engaged in.
When the temperature of the solution is raised, thermal fluctuations increase which results in an increase in the average distance between atoms; X-ray crystallographic studies at several temperatures (98 -320 K) on ribonuclease-A indicated that the protein volume increases linearly with temperature to an extent of about 0.4% per 100 K (Tilton, Jr. et al 1992).Such an increase in the distance between the atoms participating in a H-bond results in weakening of the H-bond.Consequently, chemical shifts of most amide protons move up field when the temperature is increased.Since bond magnetic anisotropy (σ ani ) is proportional to r -3 and molecular volume (V) is proportional to r 3 , there is an inverse relationship of their variation with temperature ((σ ani ) α1/V).However, over a small temperature range, (σ ani ) may appear to decrease linearly with temperature, and Fig. 2. Simulations of the dependence of H N chemical shift variation with temperature (290 K -315 K).In all the calculations shown chemical shifts are calculated and fitted to a straight line.Then the deviations from linearity are used to derive the residual curvatures (Krishna Mohan et al 2008;Williamson 2003).(A) Different curves show the dependence on free energy difference between the native and the higher energy alternate state: ∆G = 1 kcal/mol (dashed), ∆G = 2 kcal/mol (solid), ∆G = 3 kcal/mol (dotted) and ∆G = 4 kcal/mol (dash double dot dash); for these T∆S at 298 K was fixed at 5.1 kcal/mol and ∆H varied as 6.1, 7.1, 8.1, and 9.1 kcal/mol respectively.The chemical shift and gradient parameters are: δ 1 = 8.5 ppm, δ 2 = 8.0 ppm, and g 1 = -2 ppb/K, g 2 = -7 ppb/K for convex shapes and δ 1 = 8.0 ppm, δ 2 = 8.5 ppm, and g 1 = -7 ppb/K, g 2 = -2 ppb/K for concave shapes.(B) The solid curve is the same as in 'A' (∆G = 2 kcal/mol); Dashed curve, δ 1 = 8.1 ppm, δ 2 = 8.0 ppm, g 1 = -2 ppb/K, g 2 = -7 ppb/K, ∆G = 2 kcal/mol; dotted curve, δ 1 = 9.0 ppm, δ 2 = 8.0 ppm, g 1 = -2 ppb/K, g 2 = -7 ppb/K, ∆G = 2 kcal/mol (C) The solid curve is the same as in 'A' (∆G = 2 kcal/mol); dashed curve, δ 1 = 8.5 ppm, δ 2 = 8.0 ppm, g 1 = -2 ppb/K, g 2 = -4 ppb/K, ∆G = 2 kcal/mol; dotted curve, δ 1 = 8.5 ppm, δ 2 = 8.0 ppm, g 1 = -4 ppb/K, g 2 = -7 ppb/K, ∆G = 2 kcal/mol.(D) The solid black curve (∆G = 2 kcal/mol) and the dotted curve (∆G = 3 kcal/mol) are the same as in 'A'; solid grey curve is for δ 1 =8.1 ppm, δ 2 =8.0 ppm, g 1 = -2 ppb/K, g 2 = -4 ppb/K with ∆G = 2 kcal/mol.www.intechopen.comconsequently amide proton chemical shifts would appear to vary linearly with temperature.In BPTI (basic pancreatic trypsin inhibitor) and lysozyme which are known to be extremely stable under a variety of extreme conditions, including temperature, it was indeed observed that the amide proton chemical shifts change linearly with temperature over the ranges, 279-359 K for BPTI and 278 -328 K for Lysozyme (Baxter and Williamson 1997).Such measurements have been carried out on many other proteins (Cierpicki and Otlewski 2001;Cierpicki et al 2002) and the temperature coefficients or the gradients of temperature dependence of the amide protons have been found to span a wide range, -16 to + 4 ppb/K.For a strongly H-bonded amide this value is more positive than -4.5 ppb /K (Baxter and Williamson 1997).This is because the lengthening of the average H-bond distance will be greater for the intermolecular H-bond, such as those with bulk water, than for the intramolecular H-bonds.
However, if the protein structure is not very rigid, as would be the case for many systems, the chemical shifts would also be influenced by local structural and dynamics changes, and then the temperature dependence of chemical shifts may deviate from linearity.Indeed, in certain situations the amide proton chemical shifts have been seen to be non linearly dependent on temperature, and this has been interpreted to indicate existence of alternative conformations the residues can access (Baxter et al 1998;Williamson 2003).Identification of such residues provides a description of the energy landscape of the protein in the native state.The observed curvatures can be theoretically deduced as described in the following paragraphs.
Consider a residue having two conformational states accessible to it i.e., a native state and a higher energy state.Following the discussion in the above paragraphs, each of them can be assumed to have a linear variation of chemical shift with temperature as, δ 1 = δ ο 1 +g 1 T and δ 2 = δ ο 2 +g 2 T, where g 1 and g 2 are the gradients of temperature dependence, δ 1 andδ 2 are the chemical shifts of the native and the excited states respectively, and T is the temperature.If P 1 and P 2 are the corresponding populations of the native and the excited states, the observed chemical shift,δ obs , of the amide proton will be given by, These populations depend on the free energy difference between the two states.If there are more states contributing, then the observed shift will be a weighted average over all the accessible states.It is this complex dependence of chemical shifts on many thermodynamic and other factors, which leads to non linear dependence of chemical shifts on temperature.
To understand the influence of these factors, simulations of H N chemical shift variation are performed with temperature in the range, 290 K -315 K, using a two state model (Krishna Mohan et al 2008;Williamson 2003) where, ∆G is the free-energy difference between the two states, and ∆G =∆H -T∆S, where, ∆H and ∆S are the enthalpy difference and the entropy difference respectively.The results of the simulations are shown in Fig. 2. Fig. 2A shows the curves for∆G ranging from 1 -4 www.intechopen.comkcal/mol keeping the gradients and chemical shifts of the native and the excited states constant.Here, it is worthwhile to note that in the chosen temperature range (290 K -315 K) the curvature almost disappears above ∆G = 3 kcal/mol.Fig. 2B and Fig. 2C show the dependence of curvature on chemical shift differences and gradient differences respectively, between the native and the excited states, when ∆G is held constant (∆G = 2 kcal/mol).In Fig. 2B, three values ofδ 1 : 8.5 (reference), 8.1 and 9.0 are considered, keeping the other parameters the same as in Fig. 2A for convex shape of curvature.Similarly, in Fig. 2C, three combinations of gradients: (g 1 ,g 2 ) (ppb/K) = (-2, -7) (reference), (-2, -4) and (-4, -7) are considered keeping the other parameters same as in Fig. 2A for convex shape of curvature.From these it is evident that neither the chemical shift difference nor the difference in gradients, by itself changes the curvature to a noticeable extent.A simulation carried out for a combination of changes in 'chemical shift difference' and 'gradient difference' (δ 1 =8.1 ppm, δ 2 =8.0 ppm, g 1 = -2 ppb/K, g 2 = -4 ppb/K) keeping the free energy constant (∆G = 2 kcal/mol).This is shown by solid grey line in Fig 2D .Interestingly, this curve almost exactly overlaps with the curve for which ∆G = 3 kcal/mol in Fig. 2A which has a lower curvature compared to that of the curve with∆G = 2 kcal/mol; for ease of comparison, the corresponding curve from Fig. 2A is redrawn in Fig. 2D as a dotted line.This clearly suggests that although the appearance of curvature confirms the presence of alternative states, the lack of curvature does not necessarily imply the absence of low energy excited states.These theoretical simulations will be of great help for interpreting the experimental results on temperature dependence of amide proton chemical shifts.

Investigations on native state ruggedness of complex protein systems
A deep well, the bottom of which corresponds to the native state would imply high stability of the native state (Fig. 1).In contrast, a potential well with low lying excited states for the native state would be shallow, and this would have significant influence on the dynamics, structural adaptability, or susceptibility of the protein to various functions (Agarwal 2005 Piana et al 2002).In fact, these environment sensitive residues of polypeptide chains adopt unique 3D structures, they access various near native states which are structurally similar and energetically closer to the native state.These low populated alternative conformations dictate the ruggedness of the native structure and its biological function.

Differential native state conformational fluctuations in calcium sensor proteins
Calcium ion plays a crucial role in the regulation of various biological processes.To perform several of its functional activities, Ca 2+ binds to different protein molecules, which are called as calcium binding proteins (CaBPs) (Heizmann and Schafer 1990).undergo modest conformational changes upon Ca 2+ binding.In the current section the experimental evidence for the native state ruggedness on a Ca 2+ sensor protein from the protozoan Entamoeba histolytica ( EhCaBP), an etiologic agent of amoebiasis has been demonstrated (Atreya et al 2001;Bhattacharya et al 2006).
As an illustration, .The total number of residues which access alternative conformations at least 3 out of 5 measured GdmCl concentrations turned out to be 39 (residues shown with asterisks in Fig. 3), implying that ~ 30 % (39 out of 134) of the residues are accessing alternative conformations.
The theoretical simulations described above suggest that the observed curvatures are ~ 2-3 kcal/mol.All these residues are shown in Fig. 5 on the 3D structure of the protein.Further, the extent of curvatures of individual residues increases or decreases with change in concentration of GdmCl (Fig. 3) (Williamson 2003).The residues that become more curved with the increasing concentrations of GdmCl are most likely due to the presence of alternate states which are more similar in energy, or more different in shift or gradient to the corresponding native state.This is primarily an off-shoot of contracted unfolding energy landscape in the presence of GdmCl since the GdmCl is not expected to change the nature of the alternative state.Whereas the decrease of curvature can be explained by considering more than one alternative states within 5 kcal/mol, or have an alternative state that becomes very close to native state as GdmCl is increased.It is interesting to note that the low energy excited states detected in EhCaBP are not uniformly distributed along the polypeptide chain; different segments of the protein have their own intrinsic preferences to access the alternative conformations.Out of the 39 residues which access low energy excited states, 7 residues belong to EF-hand I; 5 to EFhand II; 11 to EF-hand III; 13 to EF-hand IV and 3 to the interconnecting loops (Fig. 4).It is evident from the data that the density of the conformational fluctuations in the C-terminal domain (24 residues) are twofold compared to the N-terminal counterpart (12 residues) (Fig. 4).This suggests that the C-terminal domain is more flexible and susceptible to structural rearrangements.Further some novel features have been observed in the locations of alternative conformations.The residue at the 5 th position of the calcium binding loop (Asp/Asn) that coordinates with Ca 2+ shows alternative conformations consistently in all the EF-hands.The Gly-6 (the residue at 6 th position in the calcium binding loop), which acts as a hinge in the calcium binding loop accesses alternative states in both EF III (Gly-90) and EF IV (Gly-122) hands.Among the calcium binding loops, the IV EF-loop is found to be the most dynamic with maximum number of residues (6 residues out of 12 residue loop) access low energy excited states.This loop has relatively low affinity towards Ca 2+ compared to the other three loops as demonstrated earlier by the EGTA titration (Mukherjee et al 2005), though highly specific for Ca 2+ .Moreover, recently it has been observed that IV EF-loop also differs with the remaining three EF-loops in the case of Mg 2+ binding as evidenced by the Mn 2+ titration (Mukherjee et al 2007a).Thus from all the discussion, it can be established that the native state of EhCaBP is rugged due to accessing of various alternative states and the ruggedness is more in the C-terminal domain compared to that in the N-terminal domain.It is interesting to note that among the four EF hands, EF-hands I and II belonging to the N-terminal domain show different conformational dynamics from that of EF-hands III and IV belonging to the C-terminal domain (Mohan et al 2008b;Mukherjee et al 2007b).
Recently Chandra et al (Chandra et al 2011) measuring nonlinear temperature dependence of the backbone amide proton chemical shifts on non-myristoylated (non-myr) and myristoylated (myr) neuronal calcium sensor-1 (NCS-1).The authors reported that ~20% of the residues in the protein access alternative conformations in non-myr case, which increases to ~28% for myr NCS-1.These residues are spread over the entire polypeptide stretch and include the edges of α-helices and β-strands, flexible loop regions, and the Ca 2+binding loops.Besides, residues responsible for the absence of Ca-myristoyl switch are also found accessing alternative states.The C-terminal domain is more populated with these residues compared to its N-terminal counterpart.Individual EF-hands in NCS-1 differ significantly in number of alternate states.Such differences in the conformational dynamics between the two domains and among the EF-loops have significant influence on the specificity and affinity of the metal binding properties and also have implications to domain dependent calcium signaling pathways of calcium sensor proteins (Mohan et al 2008b;Mukherjee et al 2007b).

Near native states and structure adaptability of dynein light chain protein
Dynein light chain protein (DLC8), a 10.3 kDa protein (89 residues) is the smallest subunit of the Dynein motor complex.DLC8 is a dimer at physiological pH and a stable monomer below pH 4.0 (Barbar and Hare 2004;Mohan et al 2006;Nyarko et al 2005).The differences between the monomeric and dimeric structures are, (i) the β3 strand in the dimer loses its secondary structure on dissociation to the monomer, and (ii) the helices α1 and α2 and the strands β1and β2 get shortened by two residues (Liang et al 1999;Makokha et al 2004).DLC8 dimer acts as a cargo adapter and recognized as interactive "protein hub" (Barbar 2008).The dimer binds the target molecules in an anti-parallel β-strand fashion through its β3-strand, whereas the monomer form of DLC8 is not capable of binding to target proteins (Alonso et al 2001;Fan et al 2001;Fan et al 1998;Fuhrmann et al 2002;Jaffrey and Snyder 1996;Lo et al 2001;Naisbitt et al 2000;Puthalakath et al 1999).This property is expected to have a regulatory role in the protein function.Temperature dependence of the amide proton chemical shifts in the DLC8 dimer (pH 7) and in the monomer (pH 3) has been measured in the temperature range 290-315 K (Krishna Mohan et al 2008).Among the above mentioned environment perturbations, pH variation is a mild perturbation and in general it changes the protonation states of the various residues depending on the chosen pH range.In order to identify the pH sensitive conformational dynamics in DLC8 protein the temperature dependence of the amide proton chemical shifts in both the dimer and the monomer were measured at slightly different pH conditions i.e., dimer at pH 6 and monomer at pH 3.5.A summary of all these results at various pH values i.e., pH 7 and 6 for the dimer and pH 3.5 and 3 for the monomer are shown in Fig. 6.
Comparison of Figs.6A and 6B reveals that the residues accessing alternative conformations have many differences between the dimer and the monomer.The number of residues accessing alternative conformations in the dimer at pH 7 and 6 are 13 and 21 respectively (Fig. 6A).Figs.7A and 7B display the locations of these residues on the native structures of the protein.Likewise, the number of residues accessing alternative conformations in the monomer at pH 3.5 is 15 and that at pH 3 is 11 (Fig. 6B).The locations of these residues are marked with red color on the native structure of the monomeric protein in Figs.7C and 7D respectively.
The differences observed in the positions of the residues accessing alternative conformations in the dimer and in the monomer due to small pH perturbations provide insights into the sensitivity of the conformational fluctuations due to environment perturbations in the two cases.In fact, the perturbation of the dimer landscape would have functional significance since small pH differences are known to exist in different parts of a cell ( Liang et al 1999), noticeable differences have been observed in both α1 and α2 helices.Interestingly, the α2 helix participates in several inter-monomer contacts once the dimer is formed and hence its sensitivity to small perturbations may have a crucial role for the proper formation/folding of the functional dimer.

Relationship between sequence, structure and pH sensitivity of DLC8 landscapes
The roughness of the energy landscape and the consequent fluctuations in the native state of a protein is a reflection on the nature of the interactions between the side chains of the different amino acid residues in the three dimensional structure of the protein.While this is not generally predictable, some insights may be obtained in some cases by closely examining the structure and the properties of the amino acids along the sequence.For example, the behaviors of residues with titratable groups, which are likely to be affected by a pH perturbation, can provide useful clues.An observed perturbation at such locations would indicate that conformational fluctuations could be arising due to existence of species with different protonation states; a change in the protonation state of a side-chain causes a local change in the electrostatic potential, and thereby results in some population of an alternative conformation on energetic considerations.Inter-conversion between the major population and the minor population so created leads to the so-called conformational fluctuations.
In the above background it is interesting to note that most of the residues with titratable groups in the side chains in DLC8 (Fig. 7E) are located in the regions which are exhibiting conformational fluctuations, and hence, their perturbation by small pH changes provides useful mechanistic insights.In the case of the dimer, the sensitivity of conformational dynamics can be readily traced to partial protonation of the His side chains as described earlier (Mohan et al 2006;Nyarko et al 2005).There will be inter-conversions between charged and neutral His and there will also be charge-charge repulsions.These will cause fluctuations in local electrostatic potentials and consequently in local side chain packing, which in turn will affect the main chain conformations.Among the three histidines, His 55 (pK 4.5,), His 68 and His 72 (both have pK of 6.0, (Mohan et al 2006;Nyarko et al 2005), the latter two would be the major contributors to the observed differences in the fluctuations of the native state in the pH range of 6-7.
In the case of DLC8 monomer His 68 and His 72 do not have any effect on the observed differences as they are completely protonated below pH 4.0.On the other hand His 55 (pK 4.5, (Mohan et al 2006;Nyarko et al 2005)), would have a significant effect.At pH 3.5 the side chain of His 55 will be protonated to the extent of 90 % and exchange between protonated and free His will contribute to a local dynamics.The environmental perturbation due to this dynamics would get relayed through the β2 strand and theα1, α2 helices and the β5 strand due to the close packing of the side chains in the protein structure (Fig. 7F).The side chains for a few residues of α1, α2 and β5 are shown in the figure and all of these residues are seen to exhibit curved temperature dependence.At pH 3.0, the population of protonated His will increase and this results in the observed perturbation differences.Similarly, the perturbations at the other titratable groups such as aspartates and glutamates in the α1 and α2 helices (see Fig. 7E) would also cause local relays and contribute to the accessibility of different low energy excited states.All these influence the native energy landscape of the protein.

Conformational fluctuations at the phosphorylation site of dynein light chain protein
Recent studies on p21-activated kinase 1 (Pak1), revealed DLC8 as its physiological interacting substrate (binding sites aa 61-89) and the phosphorylation site at Ser 88 (Vadlamudi et al 2004).Pak1 phosphorylation of DLC8 on Ser 88 controls vesicle formation and trafficking functions, whereas mutation of Ser 88 to Ala (S88A) prevents macropinocytosis (Song et al 2008;Song et al 2007;Vadlamudi et al 2004;Yang et al 2005).Further, DLC8 phosphorylation by Pak1 prevents the interaction with apoptotic protein Bim and plays an essential role in cell survival (Vadlamudi et al 2004) and also promotes the dissociation from Intermediate chain (IC74) and hence regulates the assembly of the motor complex (Song et al 2007).All these results highlight any perturbation at or near the interface is likely to affect the biological function.
Intuitively, the remote effects of any perturbation in a protein must be a consequence of a strong network of interactions which may cause rapid relay of perturbations from any one particular site on the protein structure.However, specific knowledge of how the perturbations travel will be essential in each case to understand the specificities of interactions.In general, perturbations are often introduced deliberately in the form of specific mutations in an attempt to understand the regulatory roles of specific residues involved in target recognition, structural architecture, stability, aggregation and folding features of the wild type protein (Buck et al 2007;Frankel et al 2007;Grant et al 2007;Ishibashi et al 2007;Piana et al 2008;Riley et al 2007;Stollar et al 2003).
The phosphorylation site Ser 88 represents an unusual behavior.To understand the conformational behavior phosphorylation site, the amide proton temperature coefficients of Ser 88 in the WT dimer with those of Ala 88 in the S88A mutant and of Ser 88 in the DLC8 monomer (at pH 3) are measured (Mohan and Hosur 2008).The plots of temperature dependence for these residues are shown in Fig. 8A.The measured temperature coefficients are -19.8 ± 0.3, -9.3 ± 0.2 and -5.6 ± 0.1 ppb/ o C for Ser 88 in WT dimer, Ala 88 in S88A mutant and Ser 88 in DLC8 monomer respectively.In general the temperature coefficients range between (-2 to -4) ppb/K for a strongly H-bonded amide protons and between (-5 to -10) ppb/K for an exposed solvent accessible (random coil) amide protons (Baxter and Williamson 1997).The values obtained in the case of S88A mutant and DLC8 monomer clearly indicate that the aa 88 is solvent exposed and not strongly hydrogen bonded.On the other hand, a large value of -19.8 ± 0.3 ppb/ o C suggests that the environment of Ser 88 in WT dimer is highly susceptible to perturbation.None of the other residues, either in WT monomer or in S88A mutant, showed such a huge temperature coefficient value (Baxter and Williamson 1997;Mohan and Hosur 2008).Williamson et al reported such a large value of temperature coefficient in the herpes simplex virus glycoprotein D-1 antigenic domain (Williamson et al 1986) and the experiments demonstrated by Andersen et al (Andersen et al 1992) suggested that this amide proton was in fact involved in a transient hydrogenbonded structure, and thus the large temperature coefficient could be attributed to a loss of secondary/tertiary structure on heating.If the large temperature coefficient of Ser 88 is a consequence of transient hydrogen-bonding and due to loss of secondary/tertiary structure, then Ser 88 should exhibit conformational fluctuations (alternative states).The presence of alternative states for Ser 88 has been tested on Ala 88 residue of S88A mutant and Ser 88 in DLC8 monomer and dimer (Fig. 8B).It is evident that Ser 88 in WT dimer does show a curved temperature dependence of amide proton chemical shifts.Thus, it can be concluded that the amide proton in Ser 88 in WT DLC8 dimer is transiently H-bonded; that it is not a stable H-bond was independently inferred from deuterium exchange studies (Mohan and Hosur 2008;Mohan et al 2008a).Moreover, the dimeric structure suggests that the amide group of Gly 89 is very close (~ 2.6 Ǻ) to the backbone nitrogen of Ser 88 suggesting a possibility of potential transient H-bonding.
The mechanism for the relay of perturbations from the Ser 88 site can be envisaged by understanding the close side chain packing.The side chain packing of perturbed residues and Ser 88 are shown in Fig. 8C.The crystal structure shows that Ser 88 OG atom is packed against the imidazole ring of His 55 and in addition forms a hydrogen bond with the backbone carbonyl of Ser 88' (Ser 88 of other monomer) (Liang et al 1999).From Fig. 8C it is evident that Ser 88 is buried inside and packed over side chains of crucial residues at the dimer interface.A closer look at Ser 88 environment in Fig. 8C depicts that Ser 88 is closely packed against the side chains of Thr 67, His 68 and Glu 69 of both the monomers in the dimer.Furthermore, the distance measurements between the back bone and side chain atoms of Ser 88 and those of Thr 67, His 68, Glu 69 and Thr 70 indicated that several atoms of Glu 69 are very close (~ 2 -4 Ǻ), whereas, for residues Thr 67, His 68, Thr 70 there is at least one atom in the distance range of 4 -6 Ǻ.All of these residues are perturbed by the S88A mutation as seen from the chemical shift data.The other perturbed residues are slightly farther (> 6 Ǻ).All these are shown in a color coded manner in Fig. 8C.This qualitative analysis provides a mechanistic insight into the relay of perturbation from the phopshorylation site; Glu 69 is most easily perturbed and the disturbance then runs on both sides at the dimer interface.Then, from Tyr 65 the relay spreads to Lys 44 which is engaged in a side chain H-bond.

Alternative conformations in small globular proteins: Sources of fluctuations and implications to function/folding
Experiments have been performed by various research groups to detect the alternative conformations on different monomeric proteins in order to throw light either on the functional implications or on the folding trajectories.Investigations by Kumar et al (Kumar et al 2007) on SUMO-1 suggested that the alternative conformations span the length of the protein chain but are located at particular regions on the protein structure.
The authors observed that several of the regions of the protein structure that exhibit such fluctuations coincide with the protein's binding surfaces with different substrate like GTPase effector domain (GED) of dynamin, SUMO binding motifs (SBM), E1 (activating enzyme, SAE1/SAE2) and E2 (conjugating enzyme, UBC9) enzymes of sumoylation machinery and speculated that these conformational fluctuations have significant implications for the binding of diversity of targets by SUMO-1.Another report by Srivastava et al (Srivastava and Chary 2011) on hahellin (a -crystallin domain) in its Ca 2+ -bound form depicted a large conformational heterogeneity with nearly 40% of the residues, some of which are part of Ca2+-binding loops.Further, they observed that out of the two Greek key motifs, the second Greek key motif is floppy as compared to its counterpart.
Extensive research investigations on theoretical and experimental aspects of different protein systems regarding low-energy excited states have been performed by Williamson and co-workers (Baxter et al 1998;Tunnicliffe et al 2005;Williamson 2003).Studies on conformational ensemble of cytochrome c revealed high structural entropy (Williamson 2003).The density of alternative states is particularly high near the heme ligand Met80, which is of interest because both redox change and the first identified stage in unfolding are associated with change in Met80 ligation.By combining theoretical and experimental approaches, it is concluded that the alternative states each comprise approximately five residues, have in general less structure than the native state and are therefore locally unfolded structures.The locations of the alternative states the global unfolding pathway of cytochrome c, hinted that they may determine the pathway.Similar experiments on B1 domains of streptococcal proteins G and L (Tunnicliffe et al 2005), which are structurally similar, but have different sequences and folding established that several of the residues have curved amide proton temperature and indicated approximately 4-6 local minima for each protein.Further, reports on N-terminal domain of phosphoglycerate kinase, hen eggwhite lysozyme, SUMO1 and BPTI (Baxter et al 1998;Kumar et al 2007) established that conformational heterogeneity arises from a number of independent sources such as, aromatic ring current effects, a minor conformer generated through disulphide bond isomerisation; an alternative hydrogen bond network associated with buried water molecules; alternative hydrogen bonds involving backbone amides and surface-exposed side-chain hydrogen bond acceptors; and the disruption of loops, ends of secondary structural elements and chain termini.
In conclusion, on one hand the ruggedness of the native energy landscape of the protein systems provide rationales for the adaptability of the protein structure to bind various target molecules in order to carry out the biological functions efficient manner.On the other hand, it throws light on many potential unfolding initiation sites in the protein.Furthermore, the origins of these conformational fluctuations provide mechanistic insights into the protein network of hydrophobic/H-bond interactions that dictate the protein stability.
Fig. 3. Illustrative examples for the residues showing nonlinear temperature dependence of backbone 1 H N chemical shifts in EhCaBP as measured in native state and at different concentrations of GdmCl.The measured chemical shifts were fitted to a linear equation.The residuals (observed value -calculated value according to the linear fit) have been plotted against temperature; total scale of y-axis is 0.06 ppm: +0.03 to -0.03 centered at zero, and the temperature range is 280 K -335 K.The error bars give an indication of the approximate error in measured chemical shifts (±0.004 ppm).
Fig. 4. Residues showing nonlinear temperature dependence of amide proton chemical shifts (black) in the native protein and at different concentrations of GdmCl were shown on the primary sequence of the polypeptide chain.The native secondary structures are shown by arrows (β strands) and cylinders (α helix).Residues accessing alternative conformations at least 3 out of 5 measured GdmCl concentrations are marked with asterisks along the polypeptide chain.

Fig. 5 .
Fig. 5. Residues exhibiting curved temperature dependence at least three out of five concentrations of GdmCl measured in EhCaBP are marked with red color on the 3D structure of the protein (PDB Id: 1JFK).

Fig. 6 .
Fig. 6.Residues showing non linear temperature dependence of amide proton chemical shifts (black) in the temperature range is 290 K -315 K along the polypeptide chain.The results are shown for pH 7.0 and 6.0 (A) and for pH 3.5 and 3.0 (B).The arrows (β strands) and cylinders (α helix) indicate native secondary structures.

Fig. 7 .
Fig. 7. Residues exhibiting curved temperature dependence in DLC8 dimer (A) pH 7.0, (B) pH 6.0 (PDB Id: 1f3c) and in monomer (C) pH 3.0, (D) pH 3.5 (PDB Id: 1hrw), are coloured red on the three dimensional structure of the protein.(E) Positions of all the titratable groups in the pH range 7.0 to 3.0 (Aspartates, Glutamates and Histidines) are marked with pink color on the monomer structure (PDB Id: 1rw).(F) Zooming in on a particular region surrounding β2 strand in the NMR structure of the monomer (PDB Id: 1rhw) to show the side chain interactions.Only a few residues in α1, α2 and β5 are shown for the sake of clarity.

Fig. 8 .
Fig. 8. (A) Graph depicting the temperature dependence of amide proton chemical shifts for Ser 88 in DLC8 WT-dimer (Circles, Red), Ala 88 in S88A mutant at pH 7 (Triangles, Green), and Ser 88 in DLC8 monomer at pH 3 (Diamonds, Blue).The solid lines line represents the best linear fit.(B) Comparison of non linear/linear temperature dependence of amide Mohan et al 2008;Liang et al 1999)t al 1999;Swietach and Vaughan-Jones 2004;Swietach et al 2005;Vaughan-Jones et al 2002;Willoughby and Schwiening 2002;Zaniboni et al 2003).It is evident from Figs. 7A and 7B that several of the residues that access low energy excited states are surrounding the dimer interface of the molecule which is also the cargo binding site (KrishnaMohan et al 2008;Liang et al 1999).It can be envisaged that the observed sensitivity of conformational dynamics at the dimer interface due to small environmental perturbations can significantly influence the cargo binding nature of the protein.Likewise, in the monomer (Figs.7C and 7D) (Krishna Mohan et al 2008;