Application of replica exchange umbrella sampling to protein structure refinement of nontemplate models

We provide an assessment of a computational strategy for protein structure refinement that combines self‐guided Langevin dynamics with umbrella‐potential biasing replica exchange using the radius of gyration as a coordinate (R_g‐ReX). Eight structurally nonredundant proteins and their decoys were examined by sampling conformational space at room temperature using the CHARMM22/GBMV2 force field to generate the ensemble of structures. Two atomic statistical potentials (RWplus and DFIRE) were analyzed for structure identification and compared to the simulation force‐field potential. The results show that, while the R_g‐ReX simulations were able to sample conformational basins that were more structurally similar to the X‐ray crystallographic structures than the starting first‐order ranked decoys, the potentials failed to detect these basins from refinement. Of the three potential functions, RWplus yielded the highest accuracy for recognition of structures that refined to an average of nearly 20% increase in native contacts relative to the starting decoys. The overall performance of R_g‐ReX is compared to an earlier study of applying temperature‐based replica exchange to refine the same decoy sets and highlights the general challenge of achieving consistently the sampling and detection threshold of 70% fraction of native contacts. © 2013 Wiley Periodicals, Inc.     

A new soft‐core potential function for molecular dynamics applied to the prediction of protein loop conformations

We have developed a new soft‐core potential function for the conformational search of complex systems with molecular dynamics. The potential function was designed to maintain the main equilibrium properties of the original force field, which means that the soft‐core potential gives physically realistic performance also without additional restraints, different from most of the previous soft‐core potential functions. The performance of the method was demonstrated by applying it to the problem of finding native conformations for protein loops. Short loops from neocarzinostatin and parvalbumin were used as the first test cases. The use of the new soft‐core potential function was shown to improve significantly the performance of molecular dynamics in the search of the native conformation of protein loops. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 388–397, 2000     

Application of torsion angle molecular dynamics for efficient sampling of protein conformations

We investigate the application of torsion angle molecular dynamics (TAMD) to augment conformational sampling of peptides and proteins. Interesting conformational changes in proteins mainly involve torsional degrees of freedom. Carrying out molecular dynamics in torsion space does not only explicitly sample the most relevant degrees of freedom, but also allows larger integration time steps with elimination of the bond and angle degrees of freedom. However, the covalent geometry needs to be fixed during internal coordinate dynamics, which can introduce severe distortions to the underlying potential surface in the extensively parameterized modern Cartesian-based protein force fields. A "projection" approach (Katritch et al. J Comput Chem 2003, 24, 254-265) is extended to construct an accurate internal coordinate force field (ICFF) from a source Cartesian force field. Torsion crossterm corrections constructed from local molecular fragments, together with softened van der Waals and electrostatic interactions, are used to recover the potential surface and incorporate implicit bond and angle flexibility. MD simulations of dipeptide models demonstrate that full flexibility in both the backbone phi/psi and side chain chi1 angles are virtually restored. The efficacy of TAMD in enhancing conformational sampling is then further examined by folding simulations of small peptides and refinement experiments of protein NMR structures. The results show that an increase of several fold in conformational sampling efficiency can be reliably achieved. The current study also reveals some complicated intrinsic properties of internal coordinate dynamics, beyond energy conservation, that can limit the maximum size of the integration time step and thus the achievable gain in sampling efficiency.     

Efficacy of independence sampling in replica exchange simulations of ordered and disordered proteins

Recasting temperature replica exchange (T‐RE) as a special case of Gibbs sampling has led to a simple and efficient scheme for enhanced mixing (Chodera and Shirts, J. Chem. Phys., 2011, 135, 194110). To critically examine if T‐RE with independence sampling (T‐REis) improves conformational sampling, we performed T‐RE and T‐REis simulations of ordered and disordered proteins using coarse‐grained and atomistic models. The results demonstrate that T‐REis effectively increase the replica mobility in temperatures space with minimal computational overhead, especially for folded proteins. However, enhanced mixing does not translate well into improved conformational sampling. The convergences of thermodynamic properties interested are similar, with slight improvements for T‐REis of ordered systems. The study re‐affirms the efficiency of T‐RE does not appear to be limited by temperature diffusion, but by the inherent rates of spontaneous large‐scale conformational re‐arrangements. Due to its simplicity and efficacy of enhanced mixing, T‐REis is expected to be more effective when incorporated with various Hamiltonian‐RE protocols. © 2017 Wiley Periodicals, Inc.     

Accelerated molecular dynamics simulations of protein folding

Folding of four fast‐folding proteins, including chignolin, Trp‐cage, villin headpiece and WW domain, was simulated via accelerated molecular dynamics (aMD). In comparison with hundred‐of‐microsecond timescale conventional molecular dynamics (cMD) simulations performed on the Anton supercomputer, aMD captured complete folding of the four proteins in significantly shorter simulation time. The folded protein conformations were found within 0.2–2.1 Å of the native NMR or X‐ray crystal structures. Free energy profiles calculated through improved reweighting of the aMD simulations using cumulant expansion to the second‐order are in good agreement with those obtained from cMD simulations. This allows us to identify distinct conformational states (e.g., unfolded and intermediate) other than the native structure and the protein folding energy barriers. Detailed analysis of protein secondary structures and local key residue interactions provided important insights into the protein folding pathways. Furthermore, the selections of force fields and aMD simulation parameters are discussed in detail. Our work shows usefulness and accuracy of aMD in studying protein folding, providing basic references in using aMD in future protein‐folding studies. © 2015 Wiley Periodicals, Inc.     

A method for predicting protein conformational pathways by using molecular dynamics simulations guided by difference distance matrices

Here, an efficient method that predicts natural transition pathways between two endpoint states of an allosteric protein has been proposed. This method helps create structures that bridge these endpoints through multiple iterative and unbiased molecular dynamics simulations with explicit water. Difference distance matrices provide an approach for identifying states involving concerted slow motion. A series of structures are readily generated along the transition pathways of adenylate kinase. Predicted structures may be useful for an initial pathway to evaluate free energy landscapes via umbrella sampling and chain‐of‐states methods. © 2016 Wiley Periodicals, Inc.     

Characterization of conformational equilibria through Hamiltonian and temperature replica-exchange simulations: assessing entropic and environmental effects

Molecular dynamics simulations based on the replica-exchange framework (REMD) are emerging as a useful tool to characterize the conformational variability that is intrinsic to most chemical and biological systems. In this work, it is shown that a simple extension of the replica-exchange method, known as Hamiltonian REMD, greatly facilitates the characterization of conformational equilibria across large energetic barriers, or in the presence of substantial entropic effects, overcoming some of the difficulties of REMD based on temperature alone. In particular, a comparative assessment of the HREMD and TREMD approaches was made, through computation of the gas-phase free-energy difference between the so-called D(2d) and S(4) states of tetrabutylammonium (TBA), an ionic compound of frequently used in biophysical studies of ion channels. Taking advantage of the greater efficiency of the HREMD scheme, the conformational equilibrium of TBA was characterized in a variety of conditions. Simulation of the gas-phase equilibrium in the 100-300 K range allowed us to compute the entropy difference between these states as well as to describe its temperature dependence. Through HREMD simulations of TBA in a water droplet, the effect of solvation on the conformational equilibrium was determined. Finally, the equilibrium of TBA in the context of a simplified model of the binding cavity of the KcsA potassium channel was simulated, and density maps for D(2d) and S(4) states analogous to those derived from X-ray crystallography were constructed. Overall, this work illustrates the potential of the HREMD approach in the context of computational drug design, ligand-receptor structural prediction and more generally, molecular recognition, where one of the most challenging issues remains to account for conformational flexibility as well for the solvation and entropic effects thereon.     

Ergodicity and model quality in template‐restrained canonical and temperature/Hamiltonian replica exchange coarse‐grained molecular dynamics simulations of proteins

Molecular simulations restrained to single or multiple templates are commonly used in protein‐structure modeling. However, the restraints introduce additional barriers, thus impairing the ergodicity of simulations, which can affect the quality of the resulting models. In this work, the effect of restraint types and simulation schemes on ergodicity and model quality was investigated by performing template‐restrained canonical molecular dynamics (MD), multiplexed replica‐exchange molecular dynamics, and Hamiltonian replica exchange molecular dynamics (HREMD) simulations with the coarse‐grained UNRES force field on nine selected proteins, with pseudo‐harmonic log‐Gaussian (unbounded) or Lorentzian (bounded) restraint functions. The best ergodicity was exhibited by HREMD. It has been found that non‐ergodicity does not affect model quality if good templates are used to generate restraints. However, when poor‐quality restraints not covering the entire protein are used, the improved ergodicity of HREMD can lead to significantly improved protein models. © 2017 Wiley Periodicals, Inc.     

Hierarchical parallelization of divide-and-conquer density functional tight-binding molecular dynamics and metadynamics simulations

Massively parallel divide-and-conquer density functional tight-binding (DC-DFTB) molecular dynamics and metadynamics simulations are efficient approaches for describing various chemical reactions and dynamic processes of large complex systems via quantum mechanics. In this study, DC-DFTB simulations were combined with multi-replica techniques. Specifically, multiple walkers metadynamics, replica exchange molecular dynamics, and parallel tempering metadynamics methods were implemented hierarchically into the in-house Dcdftbmd program. Test simulations in an aqueous phase of the internal rotation of formamide and conformational changes of dialanine showed that the newly developed extensions increase the sampling efficiency and the exploration capabilities in DC-DFTB configuration space.     

Replica sub-permutation method for molecular dynamics and monte carlo simulations

We propose an improvement of the replica-exchange and replica-permutation methods, which we call the replica sub-permutation method (RSPM). Instead of considering all permutations, this method uses a new algorithm referred to as sub-permutation to perform parameter transition. The RSPM succeeds in reducing the number of combinations between replicas and parameters without the loss of sampling efficiency. For comparison, we applied the replica sub-permutation, replica-permutation, and replica-exchange methods to a β-hairpin mini protein, chignolin, in explicit water. We calculated the transition ratio and number of tunneling events in the parameter space, the number of folding–unfolding events, the autocorrelation function, and the autocorrelation time as measures of sampling efficiency. The results indicate that among the three methods, the proposed RSPM is the most efficient in both parameter and conformational spaces. © 2019 Wiley Periodicals, Inc.     

PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure

We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force‐fields are available within the framework: PROFASI and OPLS‐AA/L, the latter including the generalized Born surface area solvent model. A flexible command‐line and configuration‐file interface allows users quickly to set up simulations with the desired configuration. PHAISTOS is released under the GNU General Public License v3.0. Source code and documentation are freely available from http://phaistos.sourceforge.net . The software is implemented in C++ and has been tested on Linux and OSX platforms. © 2013 Wiley Periodicals, Inc.     

The temperature intervals with global exchange of replicas empirical accelerated sampling method: parameter sensitivity and extension to a complex molecular system

The recently developed "temperature intervals with global exchange of replicas" (TIGER2) algorithm is an efficient replica-exchange sampling algorithm that provides the freedom to specify the number of replicas and temperature levels independently of the size of the system and temperature range to be spanned, thus making it particularly well suited for sampling molecular systems that are considered to be too large to be sampled using conventional replica exchange methods. Although the TIGER2 method is empirical in nature, when appropriately applied it is able to provide sampling that satisfies the balance condition and closely approximates a Boltzmann-weighted ensemble of states. In this work, we evaluated the influence of factors such as temperature range, temperature spacing, replica number, and sampling cycle design on the accuracy of a TIGER2 simulation based on molecular dynamics simulations of alanine dipeptide in implicit solvent. The influence of these factors is further examined by calculating the properties of a complex system composed of the B1 immunoglobulin-binding domain of streptococcal protein G (protein G) in aqueous solution. The accuracy of a TIGER2 simulation is particularly sensitive to the maximum temperature level selected for the simulation. A method to determine the appropriate maximum temperature level to be used in a TIGER2 simulation is presented.     

A comparison of different initialization protocols to obtain statistically independent molecular dynamics simulations

We study how the results of molecular dynamics (MD) simulations are affected by various choices during the setup, e.g., the starting velocities, the solvation, the location of protons, the conformation of His, Asn, and Gln residues, the protonation and titration of His residues, and the treatment of alternative conformations. We estimate the binding affinity of ligands to four proteins calculated with the MM/GBSA method (molecular mechanics combined with a generalized Born and surface area solvation energy). For avidin and T4 lysozyme, all variations gave similar results within 2 kJ/mol. For factor Xa, differences in the solvation or in the selection of alternative conformations gave results that are significantly different from those of the other approaches by 4-6 kJ/mol, whereas for galectin-3, changes in the conformations, rotations, and protonation gave results that differed by 10 kJ/mol, but only if residues close to the binding site were modified. This shows that the results of MM/GBSA calculations are reasonably reproducible even if the MD simulations are set up with different software. Moreover, we show that the sampling of phase space can be enhanced by solvating the systems with different equilibrated water boxes, in addition to the common use of different starting velocities. If different conformations are available in the crystal structure, they should also be employed to enhance the sampling. Protonation, ionization, and conformations of Asn, Gln, and His may also be used to enhance sampling, but great effort should be spent to obtain as reliable predictions as possible close to the active site.     

Efficient evaluation of sampling quality of molecular dynamics simulations by clustering of dihedral torsion angles and Sammon mapping

A direct conformational clustering and mapping approach for peptide conformations based on backbone dihedral angles has been developed and applied to compare conformational sampling of Met-enkephalin using two molecular dynamics (MD) methods. Efficient clustering in dihedrals has been achieved by evaluating all combinations resulting from independent clustering of each dihedral angle distribution, thus resolving all conformational substates. In contrast, Cartesian clustering was unable to accurately distinguish between all substates. Projection of clusters on dihedral principal component (PCA) subspaces did not result in efficient separation of highly populated clusters. However, representation in a nonlinear metric by Sammon mapping was able to separate well the 48 highest populated clusters in just two dimensions. In addition, this approach also allowed us to visualize the transition frequencies between clusters efficiently. Significantly, higher transition frequencies between more distinct conformational substates were found for a recently developed biasing-potential replica exchange MD simulation method allowing faster sampling of possible substates compared to conventional MD simulations. Although the number of theoretically possible clusters grows exponentially with peptide length, in practice, the number of clusters is only limited by the sampling size (typically much smaller), and therefore the method is well suited also for large systems. The approach could be useful to rapidly and accurately evaluate conformational sampling during MD simulations, to compare different sampling strategies and eventually to detect kinetic bottlenecks in folding pathways.     

Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers

All‐atom sampling is a critical and compute‐intensive end stage to protein structural modeling. Because of the vast size and extreme ruggedness of conformational space, even close to the native structure, the high‐resolution sampling problem is almost as difficult as predicting the rough fold of a protein. Here, we present a combination of new algorithms that considerably speed up the exploration of very rugged conformational landscapes and are capable of finding heretofore hidden low‐energy states. The algorithm is based on a hierarchical workflow and can be parallelized on supercomputers with up to 128,000 compute cores with near perfect efficiency. Such scaling behavior is notable, as with Moore's law continuing only in the number of cores per chip, parallelizability is a critical property of new algorithms. Using the enhanced sampling power, we have uncovered previously invisible deficiencies in the Rosetta force field and created an extensive decoy training set for optimizing and testing force fields. © 2012 Wiley Periodicals, Inc.     

Assessment of biomolecular force fields for molecular dynamics simulations in a protein crystal

Different biomolecular force fields (OPLS‐AA, AMBER03, and GROMOS96) in conjunction with SPC, SPC/E and TIP3P water models are assessed for molecular dynamics simulations in a tetragonal lysozyme crystal. The root mean square deviations for the C_a atoms of lysozymes are about 0.1 to 0.2 nm from OPLS‐AA and AMBER03, smaller than 0.4 nm from GROMOS96. All force fields exhibit similar pattern in B‐factors, whereas OPLS‐AA and AMBER03 accurately reproduce experimental measurements. Despite slight variations, the primary secondary structures are well conserved using different force fields. Water diffusion in the crystal is approximately ten‐fold slower than in bulk phase. The directional and average water diffusivities from OPLS‐AA and AMBER03 along with SPC/E model match fairly well with experimental data. Compared to GROMOS96, OPLS‐AA and AMBER03 predict larger hydrophilic solvent‐accessible surface area of lysozyme, more hydrogen bonds between lysozyme and water, and higher percentage of water in hydration shell. SPC, SPC/E and TIP3P water models have similar performance in most energetic and structural properties, but SPC/E outperforms in water diffusion. While all force fields overestimate the mobility and electrical conductivity of NaCl, a combination of OPLS‐AA for lysozyme and the Kirkwood‐Buff model for ions is superior to others. As attributed to the steric restraints and surface interactions, the mobility and conductivity in the crystal are reduced by one to two orders of magnitude from aqueous solution. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Exhaustive search of the configurational space of heat-shock protein 90 with its inhibitor by multicanonical molecular dynamics based dynamic docking

Multicanonical molecular dynamics based dynamic docking was used to exhaustively search the configurational space of an inhibitor binding to the N-terminal domain of heat-shock protein 90 (Hsp90). The obtained structures at 300 K cover a wide structural ensemble, with the top two clusters ranked by their free energy coinciding with the native binding site. The representative structure of the most stable cluster reproduced the experimental binding configuration, but an interesting conformational change in Hsp90 could be observed. The combined effects of solvation and ligand binding shift the equilibrium from a preferred loop-in conformation in the unbound state to an α-helical one in the bound state for the flexible lid region of Hsp90. Thus, our dynamic docking method is effective at predicting the native binding site while exhaustively sampling a wide configurational space, modulating the protein structure upon binding.     

The NMR structure of [Xd(C2)]4 investigated by molecular dynamics simulations

The i‐motif tetrameric structure is built up from two parallel duplexes intercalated in a head‐to‐tail orientation, and held together by hemiprotonated cytosine pairs. Two topologies exist for the i‐motif structure, one with outermost 3′ extremities and the other with outermost 5′ extremities, called the 3′E and 5′E topology, respectively. Since the comparison of sugar and phosphate group interactions between the two topologies is independent of the length of the intercalation motif, the relative stability of the 3′E and 5′E topologies therefore should not depend on this length. Nevertheless, it has been shown that the 3′E topology of the [d(C2)]4 is much more stable than the 5′E topology, and that the former is the only species observed in solution. In order to understand the reason for this atypical behavior, the NMR structure of the [Xd(C2)]4 was determined and analyzed by molecular dynamics simulations. In the NMR structure, the width of the narrow groove is slightly smaller than in previously determined i‐motif structures, which supports the importance of phosphodiester backbone interactions in the structure stability. The simulations show that the stacking of cytosines, essential for the i‐motif stability, is produced by a similar and non‐negative twisting of the phosphodiester backbones. The twisting is induced by an interaction between the backbones; the [Xd(C2)]4 in 5′E topology, exhibiting very limited interaction between the phosphodiester backbones, is thus unstable. Copyright © 2002 John Wiley & Sons, Ltd.