Langevin model of the temperature and hydration dependence of protein vibrational dynamics

Analysis of Velocity Autocorrelation Functions from Molecular Dynamics Simulations of a Small Peptide by the Generalized Langevin Equation with a Power-Law Kernel

Internal motions play an essential role in the biological functions of proteins and have been the subject of numerous theoretical and spectroscopic studies. Such complex environments are associated with anomalous diffusion where, in contrast to the classical Brownian motion, the relevant correlation functions have power law decays with time. In this work, we investigate the presence of long memory stochastic processes through the analysis of atomic velocity autocorrelation functions. Analytical expressions of the velocity autocorrelation function spectrum obtained through a Mori-Zwanzig projection approach were shown to be compatible with molecular dynamics simulations of a small helical peptide (8-polyalanine).

Principal Component Analysis and Related Methods for Investigating the Dynamics of Biological Macromolecules

Principal component analysis (PCA) is used to reduce the dimensionalities of high-dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high-dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods and their applications for investigating protein dynamics.

Response of Terahertz Protein Vibrations to Ligand Binding: Calmodulin-Peptide Complexes as a Case Study

Terahertz vibrations are sensitive reporters of the structure and interactions of proteins. Ligand binding alters the nature and distribution of these collective vibrations. The ligand-induced changes in the terahertz protein vibrations contribute to the binding entropy and to the overall thermodynamic stability of the resultant protein-ligand complexes. Here, we have examined the response of the low-frequency (below 6 terahertz) collective vibrations of the calcium-loaded calmodulin (CaM) to binding to five different ligands, both in the presence and absence of water, using normal-mode analysis and molecular dynamics simulations. A comparison of the vibrational spectra of hydrated and dry systems reveals that protein-solvent interactions stiffen the terahertz protein vibrations and that these solvent-coupled collective vibrations contribute significantly to the hydration-sensitive variation in the vibrational entropy of CaM. In the absence of water, the low-frequency vibrations of CaM are stiffened by ligand binding. On the contrary, the number and the cumulative vibrational entropy of low-frequency vibrational modes (ω < 200 cm^-1) of the hydrated CaM are increased noticeably after binding to the peptides, indicating binding-induced softening of collective vibrations of the protein. Although the calculated and experimental binding affinities of the chosen complexes correlated reasonably well, no systematic correlation was observed between the protein vibrational entropy and the binding affinity. The results underscored the importance of the interplay of protein-ligand and solvent interactions in modulating the low-frequency vibrations of proteins.

Conformational dynamics of a multidomain protein by neutron scattering and computational analysis

The flexible conformations of a multidomain protein are responsible for its biological functions. Although MurD, a 47-kDa protein that consists of three domains, sequentially changes its domain conformation from an open form to a closed form through a semiclosed form in its enzymatic reaction, the domain dynamics in each conformation remains unclear. In this study, we verify the conformational dynamics of MurD in the corresponding three states (apo and ATP- and inhibitor-bound states) with a combination of small-angle x-ray and neutron scattering (SAXS and SANS), dynamic light scattering (DLS), neutron backscattering (NBS), neutron spin echo (NSE) spectroscopy, and molecular dynamics (MD) simulations. Applying principal component analysis of the MD trajectories, twisting and open-closed domain modes are identified as the major collective coordinates. The deviations of the experimental SAXS profiles from the theoretical calculations based on the known crystal structures become smaller in the ATP-bound state than in the apo state, and a further decrease is evident upon inhibitor binding. These results suggest that domain motions of the protein are suppressed step by step of each ligand binding. The DLS and NBS data yield collective and self-translational diffusion constants, respectively, and we used them to extract collective domain motions in nanometer and nanosecond scales from the NSE data. In the apo state, MurD shows both twisting and open-closed domain modes, whereas an ATP binding suppresses twisting domain motions, and a further reduction of open-closed mode is seen in the inhibitor-binding state. These observations are consistent with the structure modifications measured by the small-angle scattering as well as the MD simulations. Such changes in the domain dynamics associated with the sequential enzymatic reactions should be related to the affinity and reaction efficiency with a ligand that binds specifically to each reaction state.

Equilibrium Ensembles for Insulin Folding from Bias-Exchange Metadynamics

Earliest events in the aggregation process, such as single molecule reconfiguration, are extremely important and the most difficult to characterize in experiments. To this end, we have used well-tempered bias exchange metadynamics simulations to determine the equilibrium ensembles of an insulin molecule under amyloidogenic conditions of low pH and high temperature. A bin-based clustering method that uses statistics accumulated in bias exchange metadynamics trajectories was employed to construct a detailed thermodynamic and kinetic model of insulin folding. The highest lifetime, lowest free-energy ensemble identified consisted of native conformations adopted by a folded insulin monomer in solution, namely, the R-, the R^f-, and the T-states of insulin. The lowest free-energy structure had a root mean square deviation of only 0.15 nm from native x-ray structure. The second longest-lived metastable state was an unfolded, compact monomer with little similarity to the native structure. We have identified three additional long-lived, metastable states from the bin-based model. We then carried out an exhaustive structural characterization of metastable states on the basis of tertiary contact maps and per-residue accessible surface areas. We have also determined the lowest free-energy path between two longest-lived metastable states and confirm earlier findings of non-two-state folding for insulin through a folding intermediate. The ensemble containing the monomeric intermediate retained 58% of native hydrophobic contacts, however, accompanied by a complete loss of native secondary structure. We have discussed the relative importance of nativelike versus nonnative tertiary contacts for the folding transition. We also provide a simple measure to determine the importance of an individual residue for folding transition. Finally, we have compared and contrasted this intermediate with experimental data obtained in spectroscopic, crystallographic, and calorimetric measurements during early stages of insulin aggregation. We have also determined stability of monomeric insulin by incubation at a very low concentration to isolate protein-protein interaction effects.

Sub-THz specific relaxation times of hydrogen bond oscillations in E.coli thioredoxin. Molecular dynamics and statistical analysis

Hydrogen bonds (H-bonds) in biological macromolecules are important for the molecular structure and functions. Since interactions via hydrogen bonds are weaker than covalent bonds, it can be expected that atomic movements involving H-bonds have low frequency vibrational modes. Sub-Terahertz (sub-THz) vibrational spectroscopy that combines measurements with molecular dynamics (MD) computational prediction has been demonstrated as a promising approach for biological molecule characterization. Multiple resonance absorption lines have been reported. The knowledge of relaxation times of atomic oscillations is critical for the successful application of THz spectroscopy for hydrogen bond characterization. The purpose of this work is to use atomic oscillations in the 0.35-0.7 THz range, found from molecular dynamic (MD) simulations of E.coli thioredoxin (2TRX), to study relaxation dynamics of two intra-molecular H-bonds, OH-N and OH-C. Two different complimentary techniques are used in this study, one is the analysis of the statistical distribution of relaxation time and dissipation factor values relevant to low frequency oscillations, and the second is the analysis of the autocorrelation function of low frequency quasi-periodic movements. By studying hydrogen bond atomic displacements, it was found that the atoms are involved in a number of collective oscillations, which are characterized by different relaxation time scales ranging from 2-3 ps to more than 150 ps. The existence of long lasting relaxation processes opens the possibility to directly observe and study H-bond vibrational modes in sub-THz absorption spectra of bio-molecules if measured with an appropriate spectral resolution. The results of measurements using a recently developed frequency domain spectroscopic sensor with a spectral resolution of 1 GHz confirm the MD analysis.

Aligning experimental and theoretical anisotropic B-factors: water models, normal-mode analysis methods, and metrics

The strength of X-ray crystallography in providing the information for protein dynamics has been under appreciated. The anisotropic B-factors (ADPs) from high-resolution structures are invaluable in studying the relationship among structure, dynamics, and function. Here, starting from an in-depth evaluation of the metrics used for comparing the overlap between two ellipsoids, we applied normal-mode analysis (NMA) to predict the theoretical ADPs and then align them with experimental results. Adding an extra layer of explicitly treated water on protein surface significantly improved the energy minimization results and better reproduced the anisotropy of experimental ADPs. In comparing experimental and theoretical ADPs, we focused on the overlap in shape, the alignment of dominant directions, and the similarity in magnitude. The choices of water molecules, NMA methods, and the metrics for evaluating the overlap of ADPs determined final results. This study provides useful information for exploring the physical basis and the application potential of experimental ADPs.

Enzyme transient state kinetics in crystal and solution from the perspective of a time-resolved crystallographer

With recent technological advances at synchrotrons [Graber et al., J. Synchrotron Radiat. 18, 658-670 (2011)], it is feasible to rapidly collect time-resolved crystallographic data at multiple temperature settings [Schmidt et al., Acta Crystallogr. D 69, 2534-2542 (2013)], from which barriers of activation can be extracted. With the advent of fourth generation X-ray sources, new opportunities emerge to investigate structure and dynamics of biological macromolecules in real time [M. Schmidt, Adv. Condens. Matter Phys. 2013, 1-10] in crystals and potentially from single molecules in random orientation in solution [Poon et al., Adv. Condens. Matter Phys. 2013, 750371]. Kinetic data from time-resolved experiments on short time-scales must be interpreted in terms of chemical kinetics [Steinfeld et al., Chemical Kinetics and Dynamics, 2nd ed. (Prentience Hall, 1985)] and tied to existing time-resolved experiments on longer time-scales [Schmidt et al., Acta Crystallogr. D 69, 2534-2542 (2013); Jung et al., Nat. Chem. 5, 212-220 (2013)]. With this article, we will review and outline steps that are required to routinely determine the energetics of reactions in biomolecules in crystal and solution with newest X-ray sources. In eight sections, we aim to describe concepts and experimental details that may help to inspire new approaches to collect and interpret these data.

Elastic and conformational softness of a globular protein

Flexibility, or softness, is crucial for protein function and consists of a conformational component, involving jumps between potential wells, and an elastic component, involving fluctuations within the wells. Combining molecular dynamics simulation with incoherent neutron scattering and light scattering measurements on green fluorescent protein, we reveal a relationship between the intrawell fluctuations and elastic moduli of the protein. This finding leads to a simple means of experimentally separating the conformational from the elastic atomic displacements.

Normal-mode-analysis-guided investigation of crucial intersubunit contacts in the cAMP-dependent gating in HCN channels

Protein structures define a complex network of atomic interactions in three dimensions. Direct visualization of the structure and analysis of the interaction potential energy are not straightforward approaches to pinpoint the atomic contacts that are crucial for protein function. We used the tetrameric hyperpolarization-activated cAMP-regulated (HCN) channel as a model system to study the intersubunit contacts in cAMP-dependent gating. To obtain a systematic survey of the contacts between each pair of residues, we used normal-mode analysis, a computational approach for studying protein dynamics, and constructed the covariance matrix for C-α atoms. The significant contacts revealed by covariance analysis were further investigated by means of mutagenesis and functional assays. Among the mutant channels that show phenotypes different from those of the wild-type, we focused on two mutant channels that express opposite changes in cAMP-dependent gating. Subsequent biochemical assays on isolated C-terminal fragments, including the cAMP binding domain, revealed only minimal effects on cAMP binding, suggesting the necessity of interpreting the cAMP-dependent allosteric regulation at the whole-channel level. For this purpose, we applied the patch-clamp fluorometry technique and observed correlated changes in the dynamic, state-dependent cAMP binding in the mutant channels. This study not only provides further understanding of the intersubunit contacts in allosteric coupling in the HCN channel, it also illustrates an effective strategy for delineating important atomic contacts within a structure.

Functional domain motions in proteins on the ~1-100 ns timescale: comparison of neutron spin-echo spectroscopy of phosphoglycerate kinase with molecular-dynamics simulation

Protein function often requires large-scale domain motion. An exciting new development in the experimental characterization of domain motions in proteins is the application of neutron spin-echo spectroscopy (NSE). NSE directly probes coherent (i.e., pair correlated) scattering on the ~1-100 ns timescale. Here, we report on all-atom molecular-dynamics (MD) simulation of a protein, phosphoglycerate kinase, from which we calculate small-angle neutron scattering (SANS) and NSE scattering properties. The simulation-derived and experimental-solution SANS results are in excellent agreement. The contributions of translational and rotational whole-molecule diffusion to the simulation-derived NSE and potential problems in their estimation are examined. Principal component analysis identifies types of domain motion that dominate the internal motion's contribution to the NSE signal, with the largest being classic hinge bending. The associated free-energy profiles are quasiharmonic and the frictional properties correspond to highly overdamped motion. The amplitudes of the motions derived by MD are smaller than those derived from the experimental analysis, and possible reasons for this difference are discussed. The MD results confirm that a significant component of the NSE arises from internal dynamics. They also demonstrate that the combination of NSE with MD is potentially useful for determining the forms, potentials of mean force, and time dependence of functional domain motions in proteins.

Molecular dynamics modeling of the sub-THz vibrational absorption of thioredoxin from E. coli

Sub-terahertz (THz) vibrational modes of the protein thioredoxin in a water environment were simulated using molecular dynamics (MD) in order to find the conditions needed for simulation convergence, improve the correlation between experimental and simulated absorption frequencies, and ultimately enhance the predictive capabilities of computational modeling. Thioredoxin from E. coli was used as a model molecule for protocol development and to optimize the simulation parameters. The empirically parameterized software packages Amber 8 and 10 were used in this work. Using atomic trajectories from the constant energy and volume MD simulations, thioredoxin's sub-THz vibrational spectra and absorption coefficients were calculated in a quasi-harmonic approximation. An optimal production run length ~100 ps was found, in agreement with experimental data on thioredoxin relaxation dynamics. At the same time, a new procedure was developed for averaging correlation matrices of atomic coordinates in MD simulations. In particular, the open source package ptraj was edited to improve a matrix-analyzing function. Averaging only six matrices gave much more consistent results, with absorption peak intensities exceeding those from the individual spectra and a rather good correlation between simulated vibrational frequencies and experimental data.

Systematic multiscale parameterization of heterogeneous elastic network models of proteins

We present a method to parameterize heterogeneous elastic network models (heteroENMs) of proteins to reproduce the fluctuations observed in atomistic simulations. Because it is based on atomistic simulation, our method allows the development of elastic coarse-grained models of proteins under different conditions or in different environments. The method is simple and applicable to models at any level of coarse-graining. We validated the method in three systems. First, we computed the persistence length of ADP-bound F-actin, using a heteroENM model. The value of 6.1 +/- 1.6 microm is consistent with the experimentally measured value of 9.0 +/- 0.5 microm. We then compared our method to a uniform elastic network model and a realistic extension algorithm via covariance Hessian (REACH) model of carboxy myoglobin, and found that the heteroENM method more accurately predicted mean-square fluctuations of alpha-carbon atoms. Finally, we showed that the method captures critical differences in effective harmonic interactions for coarse-grained models of the N-terminal Bin/amphiphysin/Rvs (N-BAR) domain of amphiphysin, by building models of N-BAR both bound to a membrane and free in solution.

REACH coarse-grained biomolecular simulation: transferability between different protein structural classes

Coarse graining of protein interactions provides a means of simulating large biological systems. The REACH (Realistic Extension Algorithm via Covariance Hessian) coarse-graining method, in which the force constants of a residue-scale elastic network model are calculated from the variance-covariance matrix obtained from atomistic molecular dynamics (MD) simulation, involves direct mapping between scales without the need for iterative optimization. Here, the transferability of the REACH force field is examined between protein molecules of different structural classes. As test cases, myoglobin (all alpha), plastocyanin (all beta), and dihydrofolate reductase (alpha/beta) are taken. The force constants derived are found to be closely similar in all three proteins. An MD version of REACH is presented, and low-temperature coarse-grained (CG) REACH MD simulations of the three proteins are compared with atomistic MD results. The mean-square fluctuations of the atomistic MD are well reproduced by the CGMD. Model functions for the CG interactions, derived by averaging over the three proteins, are also shown to produce fluctuations in good agreement with the atomistic MD. The results indicate that, similarly to the use of atomistic force fields, it is now possible to use a single, generic REACH force field for all protein studies, without having first to derive parameters from atomistic MD simulation for each individual system studied. The REACH method is thus likely to be a reliable way of determining spatiotemporal motion of a variety of proteins without the need for expensive computation of long atomistic MD simulations.

Effects of surface water on protein dynamics studied by a novel coarse-grained normal mode approach

Normal mode analysis (NMA) has received much attention as a direct approach to extract the collective motions of macromolecules. However, the stringent requirement of computational resources by classical all-atom NMA limits the size of the macromolecules to which the method is normally applied. We implemented a novel coarse-grained normal mode approach based on partitioning the all-atom Hessian matrix into relevant and nonrelevant parts. It is interesting to note that, using classical all-atom NMA results as a reference, we found that this method generates more accurate results than do other coarse-grained approaches, including elastic network model and block normal mode approaches. Moreover, this new method is effective in incorporating the energetic contributions from the nonrelevant atoms, including surface water molecules, into the coarse-grained protein motions. The importance of such improvements is demonstrated by the effect of surface water to shift vibrational modes to higher frequencies and by an increase in overlap of the coarse-grained eigenvector space (the motion directions) with that obtained from molecular dynamics simulations of solvated protein in a water box. These results not only confirm the quality of our method but also point out the importance of incorporating surface structural water in studying protein dynamics.

Coarse-grained biomolecular simulation with REACH: realistic extension algorithm via covariance Hessian

Coarse-graining of protein interactions provides a means of simulating large biological systems. Here, a coarse-graining method, REACH, is introduced, in which the force constants of a residue-scale elastic network model are calculated from the variance-covariance matrix obtained from atomistic molecular dynamics (MD) simulation. In test calculations, the C(alpha)-atoms variance-covariance matrices are calculated from the ensembles of 1-ns atomistic MD trajectories in monomeric and dimeric myoglobin, and used to derive coarse-grained force constants for the local and nonbonded interactions. Construction of analytical model functions of the distance-dependence of the interresidue force constants allows rapid calculation of the REACH normal modes. The model force constants from monomeric and dimeric myoglobin are found to be similar in magnitude to each other. The MD intra- and intermolecular mean-square fluctuations and the vibrational density of states are well reproduced by the residue-scale REACH normal modes without requiring rescaling of the force constant parameters. The temperature-dependence of the myoglobin REACH force constants reveals that the dynamical transition in protein internal fluctuations arises principally from softening of the elasticity in the nonlocal interactions. The REACH method is found to be a reliable way of determining spatiotemporal protein motion without the need for expensive computations of long atomistic MD simulations.

Temperature-dependent protein dynamics: a simulation-based probabilistic diffusion-vibration Langevin description

An enduring challenge in the understanding of internal protein motions is the effective separation and characterization of diffusive and vibrational dynamical components. To address this problem, here nanosecond molecular dynamics trajectories of myoglobin in aqueous solution, performed over a range of temperatures between 120 and 300 K, are subjected to principal component analysis, and the coordinate autocorrelation functions of the resulting principal modes are interpreted using a model combining damped Langevin vibration within potential wells and barrier-crossing diffusion between them. Both the vibrational frequency and the fraction of the mean-square fluctuation arising from vibrational motion undergo transitions with temperature at about 180 K. In contrast, the vibrational friction remains linear with temperature. The diffusional component of the mean-square fluctuation increases dramatically at the dynamical transition. The heights of the energy barriers between the potential wells are estimated, and the associated diffusion constants are calculated using Kramers' rate theory. Model functions of the frequency dependence of the frictional and diffusional quantities are obtained. The dynamic structure factor from the full molecular dynamics trajectory is well reproduced by the model. Overall, the results indicate that a global description of nanosecond temperature-dependent diffusion and vibrational internal protein dynamics can be obtained by applying the results of the present diffusion-vibration model to the vibrational motions obtained from a normal-mode analysis.

Protein dynamics from X-ray crystallography: Anisotropic, global motion in diffuse scattering patterns

Understanding X-ray crystallographic diffuse scattering is likely to improve our comprehension of equilibrium collective protein dynamics. Here, using molecular dynamics (MD) simulation, a detailed analysis is performed of the origins of diffuse scattering in crystalline Staphylococcal nuclease, for which the complete diffuse scattering pattern has been determined experimentally. The hydrogen-atom contribution and the scattering range over which the scattering can be considered to be a sum of solvent and protein scattering are determined. Two models of correlated protein motion are investigated by calculating the model-derived diffuse scattering and comparing with the scattering calculated directly from MD trajectories. In one model, previously used in diffuse scattering interpretation, the atomic displacement correlations decay isotropically with increasing separation. Model correlation lengths are obtained by refining the model scattering against the simulation-derived scattering pattern, and are found to be significantly different from those correlation lengths derived directly from the MD trajectories. Furthermore, the convergence between the model-derived and MD-derived scattering is poor. The second model, in which the displacement correlations are calculated from the principal components of the MD trajectories, is capable of fully reproducing the MD-derived diffuse scattering if the approximately 50% lowest-frequency modes are included. However, a small number ( approximately 10) of lowest-frequency and largest-amplitude modes dominates the diffuse scattering and thus the correlated protein motions. A detailed analysis of the principal components is performed. In particular, the effective free energy profile associated with each principle mode is analyzed and the eigenfrequency and damping coefficient computed using a model of Brownian dynamics. Those collective modes with effective frequencies below approximately 0.5 THz, including those that determine the diffuse scattering, are overdamped.