Simulating protein motions with rigidity analysis.

Protein motions, ranging from molecular flexibility to large-scale conformational change, play an essential role in many biochemical processes. Despite the explosion in our knowledge of structural and functional data, our understanding of protein movement is still very limited. In previous work, we developed and validated a motion planning based method for mapping protein folding pathways from unstructured conformations to the native state. In this paper, we propose a novel method based on rigidity theory to sample conformation space more effectively, and we describe extensions of our framework to automate the process and to map transitions between specified conformations. Our results show that these additions both improve the accuracy of our maps and enable us to study a broader range of motions for larger proteins. For example, we show that rigidity-based sampling results in maps that capture subtle folding differences between protein G and its mutants, NuG1 and NuG2, and we illustrate how our technique can be used to study large-scale conformational changes in calmodulin, a 148 residue signaling protein known to undergo conformational changes when binding to Ca(2+). Finally, we announce our web-based protein folding server which includes a publicly available archive of protein motions: (http://parasol.tamu.edu/foldingserver/).     

A Correspondence Between Solution-State Dynamics of an Individual Protein and the Sequence and Conformational Diversity of its Family

Conformational ensembles are increasingly recognized as a useful representation to describe fundamental relationships between protein structure, dynamics and function. Here we present an ensemble of ubiquitin in solution that is created by sampling conformational space without experimental information using “Backrub” motions inspired by alternative conformations observed in sub-Angstrom resolution crystal structures. Backrub-generated structures are then selected to produce an ensemble that optimizes agreement with nuclear magnetic resonance (NMR) Residual Dipolar Couplings (RDCs). Using this ensemble, we probe two proposed relationships between properties of protein ensembles: (i) a link between native-state dynamics and the conformational heterogeneity observed in crystal structures, and (ii) a relation between dynamics of an individual protein and the conformational variability explored by its natural family. We show that the Backrub motional mechanism can simultaneously explore protein native-state dynamics measured by RDCs, encompass the conformational variability present in ubiquitin complex structures and facilitate sampling of conformational and sequence variability matching those occurring in the ubiquitin protein family. Our results thus support an overall relation between protein dynamics and conformational changes enabling sequence changes in evolution. More practically, the presented method can be applied to improve protein design predictions by accounting for intrinsic native-state dynamics.     

Local motions in a benchmark of allosteric proteins

Allosteric proteins have been studied extensively in the last 40 years, but so far, no systematic analysis of conformational changes between allosteric structures has been carried out. Here, we compile a set of 51 pairs of known inactive and active allosteric protein structures from the Protein Data Bank. We calculate local conformational differences between the two structures of each protein using simple metrics, such as backbone and side-chain Cartesian displacement, and torsion angle change and rearrangement in residue-residue contacts. Thresholds for each metric arise from distributions of motions in two control sets of pairs of protein structures in the same biochemical state. Statistical analysis of motions in allosteric proteins quantifies the magnitude of allosteric effects and reveals simple structural principles about allostery. For example, allosteric proteins exhibit substantial conformational changes comprising about 20% of the residues. In addition, motions in allosteric proteins show strong bias toward weakly constrained regions such as loops and the protein surface. Correlation functions show that motions communicate through protein structures over distances averaging 10-20 residues in sequence space and 10-20 A in Cartesian space. Comparison of motions in the allosteric set and a set of 21 nonallosteric ligand-binding proteins shows that nonallosteric proteins also exhibit bias of motion toward weakly constrained regions and local correlation of motion. However, allosteric proteins exhibit twice as much percent motion on average as nonallosteric proteins with ligand-induced motion. These observations may guide efforts to design flexibility and allostery into proteins.     

Conformational substates in enzyme mechanism: the 120 K structure of alpha-lytic protease at 1.5 A resolution.

Insight into the dynamic properties of alpha-lytic protease (alpha LP) has been obtained through the use of low-temperature X-ray crystallography and multiple-conformation refinement. Previous studies of alpha LP have shown that the residues around the active site are able to move significantly to accommodate substrates of different sizes. Here we show a link between the ability to accommodate ligands and the dynamics of the binding pocket. Although the structure of alpha LP at 120 K has B-factors with a uniformly low value of 4.8 A2 for the main chain, four regions stand out as having significantly higher B-factors. Because thermal motion should be suppressed at cryogenic temperatures, the high B-factors are interpreted as the result of trapped conformational substates. The active site residues that are perturbed during accommodation of different substrates are precisely those showing conformational substates, implying that substrate binding selects a subset of conformations from the ensemble of accessible states. To better characterize the precise nature of these substates, a protein model consisting of 16 structures has been refined and evaluated. The model reveals a number of features that could not be well-described by conventional B-factors: for example, 40% of the main-chain residue conformations are distributed asymmetrically or in discrete clusters. Furthermore, these data demonstrate an unexpected correlation between motions on either side of the binding pocket that we suggest is a consequence of "dynamic close packing." These results provide strong evidence for the role of protein dynamics in substrate binding and are consistent with the results of dynamic studies of ligand binding in myoglobin and ribonuclease A.     

RigidFinder: A fast and sensitive method to detect rigid blocks in large macromolecular complexes

Advances in structure determination have made possible the analysis of large macromolecular complexes (some with nearly 10,000 residues, such as GroEL). The large‐scale conformational changes associated with these complexes require new approaches. Historically, a crucial component of motion analysis has been the identification of moving rigid blocks from the comparison of different conformations. However, existing tools do not allow consistent block identification in very large structures. Here, we describe a novel method, RigidFinder, for such identification of rigid blocks from different conformations—across many scales, from large complexes to small loops. RigidFinder defines rigidity in terms of blocks, where inter‐residue distances are conserved across conformations. Distance conservation, unlike the averaged values (e.g., RMSD) used by many other methods, allows for sensitive identification of motions. A further distinguishing feature of our method, is that, it is capable of finding blocks made from nonconsecutive fragments of multiple polypeptide chains. In our implementation, we utilize an efficient quasi‐dynamic programming search algorithm that allows for real‐time application to very large structures. RigidFinder can be used at a dedicated web server ( http://rigidfinder.molmovdb.org ). The server also provides links to examples at various scales such as loop closure, domain motions, partial refolding, and subunit shifts. Moreover, here we describe the detailed application of RigidFinder to four large structures: Pyruvate Phosphate Dikinase, T7 RNA polymerase, RNA polymerase II, and GroEL. The results of the method are in excellent agreement with the expert‐described rigid blocks. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Normal mode analysis of macromolecular motions in a database framework: developing mode concentration as a useful classifying statistic

We investigated protein motions using normal modes within a database framework, determining on a large sample the degree to which normal modes anticipate the direction of the observed motion and were useful for motions classification. As a starting point for our analysis, we identified a large number of examples of protein flexibility from a comprehensive set of structural alignments of the proteins in the PDB. Each example consisted of a pair of proteins that were considerably different in structure given their sequence similarity. On each pair, we performed geometric comparisons and adiabatic-mapping interpolations in a high-throughput pipeline, arriving at a final list of 3,814 putative motions and standardized statistics for each. We then computed the normal modes of each motion in this list, determining the linear combination of modes that best approximated the direction of the observed motion. We integrated our new motions and normal mode calculations in the Macromolecular Motions Database, through a new ranking interface at http://molmovdb.org. Based on the normal mode calculations and the interpolations, we identified a new statistic, mode concentration, related to the mathematical concept of information content, which describes the degree to which the direction of the observed motion can be summarized by a few modes. Using this statistic, we were able to determine the fraction of the 3,814 motions where one could anticipate the direction of the actual motion from only a few modes. We also investigated mode concentration in comparison to related statistics on combinations of normal modes and correlated it with quantities characterizing protein flexibility (e.g., maximum backbone displacement or number of mobile atoms). Finally, we evaluated the ability of mode concentration to automatically classify motions into a variety of simple categories (e.g., whether or not they are "fragment-like"), in comparison to motion statistics. This involved the application of decision trees and feature selection (particular machine-learning techniques) to training and testing sets derived from merging the "list" of motions with manually classified ones.     

Frustration‐guided motion planning reveals conformational transitions in proteins

Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here, we present a new, robotics‐inspired motion planning procedure called dCC‐RRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non‐native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eight proteins determined in two conformations separated by, on average, 7.5 Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. We then applied dCC‐RRT to examine how collective, small‐scale motions of four side‐chains in the active site of cyclophilin A propagate through the protein. dCC‐RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non‐canonical capsid binding site 25 Å away, rationalizing NMR and multi‐temperature crystallography experiments. In all, dCC‐RRT can reveal detailed, all‐atom molecular mechanisms for small and large amplitude motions. Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/ .     

Predicting order of conformational changes during protein conformational transitions using an interpolated elastic network model

The decryption of sequence of structural events during protein conformational transitions is essential to a detailed understanding of molecular functions ofvarious biological nanomachines. Coarse‐grained models have proven useful by allowing highly efficient simulations of protein conformational dynamics. By combining two coarse‐grained elastic network models constructed based on the beginning and end conformations of a transition, we have developed an interpolated elastic network model to generate a transition pathway between the two protein conformations. For validation, we have predicted the order of local and global conformational changes during key ATP‐driven transitions in three important biological nanomachines (myosin, F₁ ATPase and chaperonin GroEL). We have found that the local conformational change associated with the closing of active site precedes the global conformational change leading to mechanical motions. Our finding is in good agreement with the distribution of intermediate experimental structures, and it supports the importance of local motions at active site to drive or gate various conformational transitions underlying the workings of a diverse range of biological nanomachines. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Opening and closing motions in the periplasmic vitamin B12 binding protein BtuF

BtuF is the periplasmic binding protein (PBP) in the vitamin B(12) uptake system in Escherichia coli where it is associated with the ABC transporter BtuCD. When the ligand binds, PBPs generally display large conformational changes, commonly termed the Venus flytrap mechanism. BtuF belongs to a group of PBPs that, on the basis of crystal structures, does not appear to display such behavior. Using 480 ns multicopy molecular dynamics simulations of apo and holo forms of the protein, we investigate the dynamics of BtuF. We find BtuF to be more flexible than previously assumed, displaying clear opening and closing motions which are more pronounced in the apo form. The protein behavior is compatible with a PBP functional model that postulates a closed conformation for the ligand-bound state, whereas the empty form fluctuates between open and closed conformations. Elastic network normal-mode analysis suggests that all BtuF-like PBPs are capable of similar opening and closing motions. It also makes the typical Venus flytrap domain motions a likely common means of how PBP-ABC transporter interaction could occur.     

Understanding protein flexibility through dimensionality reduction.

This work shows how to decrease the complexity of modeling flexibility in proteins by reducing the number of dimensions necessary to model important macromolecular motions such as the induced-fit process. Induced fit occurs during the binding of a protein to other proteins, nucleic acids, or small molecules (ligands) and is a critical part of protein function. It is now widely accepted that conformational changes of proteins can affect their ability to bind other molecules and that any progress in modeling protein motion and flexibility will contribute to the understanding of key biological functions. However, modeling protein flexibility has proven a very difficult task. Experimental laboratory methods, such as x-ray crystallography, produce rather limited information, while computational methods such as molecular dynamics are too slow for routine use with large systems. In this work, we show how to use the principal component analysis method, a dimensionality reduction technique, to transform the original high-dimensional representation of protein motion into a lower dimensional representation that captures the dominant modes of motions of proteins. For a medium-sized protein, this corresponds to reducing a problem with a few thousand degrees of freedom to one with less than fifty. Although there is inevitably some loss in accuracy, we show that we can obtain conformations that have been observed in laboratory experiments, starting from different initial conformations and working in a drastically reduced search space.     

Close correspondence between the motions from principal component analysis of multiple HIV-1 protease structures and elastic network modes

The large number of available HIV-1 protease structures provides a remarkable sampling of conformations of the different conformational states, which can be viewed as direct structural information about the dynamics of the HIV-1 protease. After structure matching, we apply principal component analysis (PCA) to obtain the important apparent motions for both bound and unbound structures. There are significant similarities between the first few key motions and the first few low-frequency normal modes calculated from a static representative structure with an elastic network model (ENM), strongly suggesting that the variations among the observed structures and the corresponding conformational changes are facilitated by the low-frequency, global motions intrinsic to the structure. Similarities are also found when the approach is applied to an NMR ensemble, as well as to molecular dynamics (MD) trajectories. Thus, a sufficiently large number of experimental structures can directly provide important information about protein dynamics, but ENM can also provide similar sampling of conformations.     

Discovering conformational sub-states relevant to protein function

Background

Internal motions enable proteins to explore a range of conformations, even in the vicinity of native state. The role of conformational fluctuations in the designated function of a protein is widely debated. Emerging evidence suggests that sub-groups within the range of conformations (or sub-states) contain properties that may be functionally relevant. However, low populations in these sub-states and the transient nature of conformational transitions between these sub-states present significant challenges for their identification and characterization.

Methods and Findings

To overcome these challenges we have developed a new computational technique, quasi-anharmonic analysis (QAA). QAA utilizes higher-order statistics of protein motions to identify sub-states in the conformational landscape. Further, the focus on anharmonicity allows identification of conformational fluctuations that enable transitions between sub-states. QAA applied to equilibrium simulations of human ubiquitin and T4 lysozyme reveals functionally relevant sub-states and protein motions involved in molecular recognition. In combination with a reaction pathway sampling method, QAA characterizes conformational sub-states associated with cis/trans peptidyl-prolyl isomerization catalyzed by the enzyme cyclophilin A. In these three proteins, QAA allows identification of conformational sub-states, with critical structural and dynamical features relevant to protein function.

Conclusions

Overall, QAA provides a novel framework to intuitively understand the biophysical basis of conformational diversity and its relevance to protein function.     

How environment supports a state: molecular dynamics simulations of two states in bacteriorhodopsin suggest lipid and water compensation

The light-driven proton pump bacteriorhodopsin (bR) is a transmembrane protein that uses large conformational changes for proton transfer from the cytoplasmic to the extracellular regions. Crystal structures, due to their solvent conditions, do not resolve the effect of lipid molecules on these protein conformational changes. To begin to understand the molecular details behind such large conformational changes, we simulated two conformations of wild-type bacteriorhodopsin, one of the dark-adapted state and the second of an intermediate (M(O)) state, each within an explicit dimyristoyl-phosphatidylcholine (DMPC) lipid bilayer. The simulations included all-hydrogen and all-atom representations of protein, lipid, and water and were performed for 20 ns. We investigate the equilibrium properties and the dynamic motions of the two conformations in the lipid setting. We note that the conformational state of the M(O) intermediate bR remains markedly different from the dark-adapted bR state in that the M(O) intermediate shows rearrangement of the cytoplasmic portions of helices C, F, and G, and nearby loops. This difference in the states remained throughout the simulations, and the results are stable on the molecular dynamics timescale and provide an illustration of the changes in both lipid and water that help to stabilize a particular state. Our analysis focuses on how the environment adjusts to these two states and on how the dynamics of the helices, loops, and water molecules can be related to the pump mechanism of bacteriorhodopsin. For example, water generally behaves in the same manner on the extracellular sides of both simulations but is decreased in the cytoplasmic region of the M(O) intermediate. We suspect that the different water behavior is closely related to the fluctuations of microcavities volume in the protein interior, which is strongly coupled to the collective motion of the protein. Our simulation result suggests that experimental observation can be useful to verify a decreased number of waters in the cytoplasmic regions of the late-intermediate stages by measuring the rate of water exchange with the interior of the protein.     

Dynamic transition associated with the thermal denaturation of a small Beta protein

We studied the temperature dependence of the picosecond internal dynamics of an all-beta protein, neocarzinostatin, by incoherent quasielastic neutron scattering. Measurements were made between 20 degrees C and 71 degrees C in heavy water solution. At 20 degrees C, only 33% of the nonexchanged hydrogen atoms show detectable dynamics, a number very close to the fraction of protons involved in the side chains of random coil structures, therefore suggesting a rigid structure in which the only detectable diffusive movements are those involving the side chains of random coil structures. At 61.8 degrees C, although the protein structure is still native, slight dynamic changes are detected that could reflect enhanced backbone and beta-sheet side-chain motions at this higher temperature. Conversely, all internal dynamics parameters (amplitude of diffusive motions, fraction of immobile scatterers, mean-squared vibration amplitude) rapidly change during heat-induced unfolding, indicating a major loss of rigidity of the beta-sandwich structure. The number of protons with diffusive motion increases markedly, whereas the volume occupied by the diffusive motion of protons is reduced. At the half-transition temperature (T = 71 degrees C) most of backbone and beta-sheet side-chain hydrogen atoms are involved in picosecond dynamics.     

Development and testing of an automated approach to protein docking

A new version of GRAMM was applied to Targets 14, 18, and 19 in CAPRI Round 5. The predictions were generated without manual intervention. Ten top-ranked matches for each target were submitted. The docking was performed by a rigid-body procedure with a smoothed potential function to accommodate conformational changes. The first stage was a global search on a fine grid with a projection of a smoothed Lennard-Jones potential. The top predictions from the first stage were subjected to the conjugate gradient minimization with the same smoothed potential. The resulting local minima were reranked according to the weighted sum of Lennard-Jones potential, pairwise residue-residue statistical preferences, cluster occupancy, and the degree of the evolutionary conservation of the predicted interface. For Targets 14 and 18, the conformation of the complex was predicted with root-mean-square deviation (RMSD) of the ligand interface atoms 0.68 A and 1.88 A correspondingly. For Target 19, the interface areas on both proteins were correctly predicted. The performance of the procedure was also analyzed on the benchmark of bound-unbound protein complexes. The results show that, on average, conformations of only 3 side-chains need to be optimized during docking of unbound structures before the backbone changes become a limiting factor. The GRAMM-X docking server is available for public use at http://www.bioinformatics.ku.edu.     

Conformational Transitions in Yeast Chorismate Mutase Important for Allosteric Regulation as Identified by Nuclear Magnetic Resonance Spectroscopy

Proteins fluctuate between different conformations in solution, and these conformational fluctuations can be important for protein function and allosteric regulation. The chorismate mutase from Saccharomyces cerevisiae (ScCM), a key enzyme in the biosynthesis of aromatic amino acids, is allosterically activated and inhibited by tryptophan and tyrosine, respectively. It was initially proposed that in the absence of effector, ScCM fluctuates between activated R and inhibited T conformations according to the Monod-Wyman-Changeux (MWC) model, although a more complex regulation pattern was later suggested by mutagenesis and kinetic data. Here we used NMR relaxation dispersion experiments to understand the conformational fluctuations on the microsecond-to-millisecond timescale that occur in ScCM. In the absence of allosteric effectors, ScCM did not exclusively exchange between T and R conformations, suggesting that the two-state MWC model is insufficient to explain conformational dynamics. Addition of tyrosine led to the quenching of much of the motion on this timescale, while new motions were identified in the presence of tryptophan. These new motions are consistent with conformational fluctuations into an alternative conformation that may be important for enzyme activity.     

Determining the invariant structure elements of the HIV-1 variable V3 loops: insight into the HIV-MN and HIV-Haiti isolates

The computer approaches that combined the 3D protein structure modeling with the mathematical statistics methods were used to compute the NMR-based 3D structures of the HIV-1 gp120 V3 loop for the HIV-MN and HIV-Haiti isolates in water as well as to compare their conformational characteristics with the purpose of determining the structure elements common for the two virus modifications. As a result, the variability of the amino acid sequence was found to stimulate the considerable structural rearrangements of the V3 loop. However, despite this fact, one functionally crucial stretch of V3 and a greater portion of its residues were shown to preserve the conformations in the viral strains of interest. To reveal the structural motifs and individual amino acids giving rise to the close conformations in the HIV-MN and HIV-Haiti V3 loops regardless of the sequence and environment variability, the simulated structures were collated with those deciphered previously in terms of NMR data in a water/trifluoroethanol mixed solvent. The structure elements and single residues of V3 residing in its biologically significant sites and keeping the conformations in all of the cases at question are considered to be the promising targets for anti-AIDS drugs studies. In this context, the structurally inflexible motifs of V3 presenting the weak units in the virus protection system may be utilized as the most convenient landing-places for molecular docking of the V3 loop and ligand structures followed by selecting chemical compounds suitable as a basis for the design of safe and effective antiviral agents.     

ATTRACT: protein-protein docking in CAPRI using a reduced protein model

Protein-protein complex structures have been predicted for CAPRI Rounds 3 and 5 using a reduced protein model. Proteins are represented by up to 3 pseudoatoms per amino acid. The docking approach termed ATTRACT is based on energy minimization in translational and rotational degrees of freedom of one protein with respect to another protein. The reduced protein model allows one to perform systematic docking minimization of many thousand start structures in reasonable computer time. Flexibility of critical surface side-chains can be accounted for by a multiple conformational copy approach. The multicopy approach allows simultaneous adjustment of side-chain conformations and optimization of translational and rotational degrees of freedom of one protein with respect to the partner during docking. For 3 (Targets 8, 14, and 19) out of 5 CAPRI targets, the approach resulted in predictions in close agreement with experiment [root-mean-square deviation (RMSD) of backbone atoms within 10 A of the protein-protein interface < 1.8 A]. The comparison of predicted and experimental structures of the CAPRI targets indicates that besides local conformational changes (e.g., changes in side-chain conformations), global conformational changes of the protein backbone can be critical for complex formation. These conformational changes not accounted for during docking are a likely reason for the unrealistic predictions in 2 cases (Targets 9 and 18).     

Folding funnels and conformational transitions via hinge-bending motions

In this article we focus on presenting a broad range of examples illustrating low-energy transitions via hinge-bending motions. The examples are divided according to the type of hinge-bending involved; namely, motions involving fragments of the protein chains, hinge-bending motions involving protein domains, and hinge-bending motions between the covalently unconnected subunits. We further make a distinction between allosterically and nonallosterically regulated proteins. These transitions are discussed within the general framework of folding and binding funnels. We propose that the conformers manifesting such swiveling motions are not the outcome of “induced fit” binding mechanism; instead, molecules exist in an ensemble of conformations that are in equilibrium in solution. These ensembles, which populate the bottoms of the funnels,a priori contain both the “open” and the “closed” conformational isomers. Furthermore, we argue that there are no fundamental differences among the physical principles behind the folding and binding funnels. Hence, there is no basic difference between funnels depicting ensembles of conformers of single molecules with fragment, or domain motions, as compared to subunits in multimeric quaternary structures, also showing such conformational transitions. The difference relates only to the size and complexity of the system. The larger the system, the more complex its corresponding fused funnel(s). In particular, funnels associated with allosterically regulated proteins are expected to be more complicated, because allostery is frequently involved with movements between subunits, and consequently is often observed in multichain and multimolecular complexes. This review centers on the critical role played by flexibility and conformational fluctuations in enzyme activity. Internal motions that extend over different time scales and with different amplitudes are known to be essential for the catalytic cycle. The conformational change observed in enzyme-substrate complexes as compared to the unbound enzyme state, and in particular the hinge-bending motions observed in enzymes with two domains, have a substantial effect on the enzymatic catalytic activity. The examples we review span the lipolytic enzymes that are particularly interesting, owing to their activation at the water-oil interface; an allosterically controlled dehydrogenase (lactate dehydrogenase); a DNA methyltransferase, with a covalently-bound intermediate; large-scale flexible loop motions in a glycolytic enzyme (TIM); domain motion in PGK, an enzyme which is essential in most cells, both for ATP generation in aerobes and for fermentation in anaerobes; adenylate kinase, showing large conformational changes, owing to their need to shield their catalytic centers from water; a calcium-binding protein (calmodulin), involved in a wide range of cellular calcium-dependent signaling; diphtheria toxin, whose large domain motion has been shown to yield “domain swapping” the hexameric glutamate dehydrogenase, which has been studied both in a thermophile and in a mesophile; an allosteric enzyme, showing subunit motion between the R and the T states (aspartate transcarbamoylase), and the historically well-studied lac represoor. Nonallosteric subunit transitions are also addressed with some examples (aspartate receptor andBamHI endonuclease). Hence, using this enzyme-catalysis-centered discussion, we address energy funnel landscapes of large-scale conformational transitions, rather than the faster, quasi-harmonic, thermal fluctuations.