Advances in enhanced sampling molecular dynamics simulations for biomolecules

Molecular dynamics simulation has emerged as a powerful computational tool for studying biomolecules as it can provide atomic insights into the conformational transitions involved in biological functions. However, when applied to complex biological macromolecules, the conformational sampling ability of conventional molecular dynamics is limited by the rugged free energy landscapes, leading to inherent timescale gaps between molecular dynamics simulations and real biological processes. To address this issue, several advanced enhanced sampling methods have been proposed to improve the sampling efficiency in molecular dynamics. In this review, the theoretical basis, practical applications, and recent improvements of both constraint and unconstrained enhanced sampling methods are summarized. Furthermore, the combined utilizations of different enhanced sampling methods that take advantage of both approaches are also briefly discussed.

[1]  A. Laio,et al.  Free-energy landscape for beta hairpin folding from combined parallel tempering and metadynamics. , 2006, Journal of the American Chemical Society.

[2]  Yuji Nagata,et al.  Redesigning dehalogenase access tunnels as a strategy for degrading an anthropogenic substrate. , 2009, Nature chemical biology.

[3]  J. Kästner Umbrella sampling , 2011 .

[4]  Yinglong Miao,et al.  Accelerated molecular dynamics simulations of protein folding , 2015, J. Comput. Chem..

[5]  Weihua Li,et al.  Exploring coumarin egress channels in human cytochrome p450 2a6 by random acceleration and steered molecular dynamics simulations , 2011, Proteins.

[6]  Massimiliano Bonomi,et al.  PLUMED 2: New feathers for an old bird , 2013, Comput. Phys. Commun..

[7]  A. Laio,et al.  Escaping free-energy minima , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[8]  M. Parrinello,et al.  From metadynamics to dynamics. , 2013, Physical review letters.

[9]  Guillaume Lamoureux,et al.  Ammonium transporters achieve charge transfer by fragmenting their substrate. , 2012, Journal of the American Chemical Society.

[10]  Yi Isaac Yang,et al.  Combining Metadynamics and Integrated Tempering Sampling. , 2018, The journal of physical chemistry letters.

[11]  Pengfei Li,et al.  Comparison of Accuracy and Convergence Rate between Equilibrium and Nonequilibrium Alchemical Transformations for Calculation of Relative Binding Free Energy , 2017 .

[12]  Y. Sugita,et al.  MOLECULAR DYNAMICS SIMULATIONS OF DNA DIMERS BASED ON REPLICA-EXCHANGE UMBRELLA SAMPLING I: TEST OF SAMPLING EFFICIENCY , 2005 .

[13]  Alessandra Magistrato,et al.  Influence of the Membrane Lipophilic Environment on the Structure and on the Substrate Access/Egress Routes of the Human Aromatase Enzyme. A Computational Study , 2012, J. Chem. Inf. Model..

[14]  A. Kidera,et al.  Multiscale enhanced sampling driven by multiple coarse-grained models , 2014 .

[15]  Wonpil Im,et al.  Theory of Adaptive Optimization for Umbrella Sampling , 2014, Journal of chemical theory and computation.

[16]  Michael R. Shirts,et al.  Statistically optimal analysis of samples from multiple equilibrium states. , 2008, The Journal of chemical physics.

[17]  D. Karandur,et al.  Intramolecular Interactions Overcome Hydration to Drive the Collapse Transition of Gly15. , 2017, The journal of physical chemistry. B.

[18]  Alessandro Laio,et al.  A Kinetic Model of Trp-Cage Folding from Multiple Biased Molecular Dynamics Simulations , 2009, PLoS Comput. Biol..

[19]  B. Berne,et al.  Replica exchange with solute scaling: a more efficient version of replica exchange with solute tempering (REST2). , 2011, The journal of physical chemistry. B.

[20]  Hong Zhang,et al.  Zooming across the Free-Energy Landscape: Shaving Barriers, and Flooding Valleys. , 2018, The journal of physical chemistry letters.

[21]  Jacob I. Monroe,et al.  Unraveling Hydrophobic Interactions at the Molecular Scale Using Force Spectroscopy and Molecular Dynamics Simulations. , 2017, ACS nano.

[22]  Y. Sugita,et al.  Ab initio replica-exchange Monte Carlo method for cluster studies , 2001 .

[23]  Yi Wang,et al.  Simulation-Based Approaches for Determining Membrane Permeability of Small Compounds , 2016, J. Chem. Inf. Model..

[24]  Paul A Bates,et al.  Refinement of protein‐protein complexes in contact map space with metadynamics simulations , 2018, Proteins.

[25]  Levi C. T. Pierce,et al.  Adaptive Accelerated Molecular Dynamics (Ad-AMD) Revealing the Molecular Plasticity of P450cam , 2011, The journal of physical chemistry letters.

[26]  Chuangye Yan,et al.  Structure of a yeast step II catalytically activated spliceosome , 2017, Science.

[27]  Martin Zacharias,et al.  Adaptive Biasing Combined with Hamiltonian Replica Exchange to Improve Umbrella Sampling Free Energy Simulations. , 2014, Journal of chemical theory and computation.

[28]  R. Nussinov,et al.  The Role of Protein Loops and Linkers in Conformational Dynamics and Allostery. , 2016, Chemical reviews.

[29]  Wenjuan Wu,et al.  Binding Mechanism and Molecular Design of Benzimidazole/Benzothiazole Derivatives as Potent Abl T315I Mutant Inhibitors , 2017 .

[30]  Feixiong Cheng,et al.  Investigation of Indazole Unbinding Pathways in CYP2E1 by Molecular Dynamics Simulations , 2012, PloS one.

[31]  Carlo Camilloni,et al.  Replica-Averaged Metadynamics. , 2013, Journal of chemical theory and computation.

[32]  Wei Wang,et al.  Clustering algorithms to analyze molecular dynamics simulation trajectories for complex chemical and biological systems , 2018, Chinese Journal of Chemical Physics.

[33]  W. Catterall,et al.  Structural Basis for Gating Pore Current in Periodic Paralysis , 2018, Nature.

[34]  Vojtech Spiwok,et al.  Enhanced sampling techniques in biomolecular simulations. , 2015, Biotechnology advances.

[35]  M. Elstner,et al.  Coupled-perturbed DFTB-QM/MM metadynamics: Application to proton-coupled electron transfer. , 2018, The Journal of chemical physics.

[36]  Song Hu,et al.  Steered molecular dynamics for studying ligand unbinding of ecdysone receptor , 2018, Journal of biomolecular structure & dynamics.

[37]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[38]  R. Kar,et al.  Accelerated molecular dynamics simulation analysis of MSI-594 in a lipid bilayer. , 2017, Physical chemistry chemical physics : PCCP.

[39]  E. Novellino,et al.  From a Helix to a Small Cycle: Metadynamics-Inspired αvβ6 Integrin Selective Ligands. , 2018, Angewandte Chemie.

[40]  G. Hummer,et al.  Peptide dimerization-dissociation rates from replica exchange molecular dynamics. , 2017, The Journal of chemical physics.

[41]  Ross C. Walker,et al.  An overview of the Amber biomolecular simulation package , 2013 .

[42]  Christophe Chipot,et al.  Enhanced Sampling of Multidimensional Free-Energy Landscapes Using Adaptive Biasing Forces , 2010, SIAM Journal on Applied Mathematics.

[43]  William Sinko,et al.  Improved Reweighting of Accelerated Molecular Dynamics Simulations for Free Energy Calculation , 2014, Journal of chemical theory and computation.

[44]  M. Parrinello,et al.  Metadynamics with Adaptive Gaussians. , 2012, Journal of chemical theory and computation.

[45]  A. Tarakanova,et al.  Tropoelastin is a Flexible Molecule that Retains its Canonical Shape. , 2018, Macromolecular bioscience.

[46]  Michele Parrinello,et al.  Well-tempered metadynamics converges asymptotically. , 2014, Physical review letters.

[47]  C. Clementi,et al.  Discovering mountain passes via torchlight: methods for the definition of reaction coordinates and pathways in complex macromolecular reactions. , 2013, Annual review of physical chemistry.

[48]  Zbynek Prokop,et al.  Pathways and mechanisms for product release in the engineered haloalkane dehalogenases explored using classical and random acceleration molecular dynamics simulations. , 2009, Journal of molecular biology.

[49]  R. Murarka,et al.  Activation of corticotropin-releasing factor 1 receptor: insights from molecular dynamics simulations. , 2015, The journal of physical chemistry. B.

[50]  Daniel S Moore,et al.  Steered molecular dynamics simulations reveal critical residues for (un)binding of substrates, inhibitors and a product to the malarial M1 aminopeptidase , 2018, PLoS Comput. Biol..

[51]  W. Nowak,et al.  Memetic algorithms for ligand expulsion from protein cavities. , 2015, The Journal of chemical physics.

[52]  Subha Kalyaanamoorthy,et al.  Modelling and enhanced molecular dynamics to steer structure-based drug discovery. , 2014, Progress in biophysics and molecular biology.

[53]  Levi C. T. Pierce,et al.  Routine Access to Millisecond Time Scale Events with Accelerated Molecular Dynamics , 2012, Journal of chemical theory and computation.

[54]  J. Onuchic,et al.  Theory of protein folding: the energy landscape perspective. , 1997, Annual review of physical chemistry.

[55]  Mai Suan Li,et al.  A New Method for Navigating Optimal Direction for Pulling Ligand from Binding Pocket: Application to Ranking Binding Affinity by Steered Molecular Dynamics , 2015, J. Chem. Inf. Model..

[56]  Adrian E Roitberg,et al.  Constant pH replica exchange molecular dynamics in biomolecules using a discrete protonation model. , 2010, Journal of chemical theory and computation.

[57]  H. Gaub,et al.  Adhesion forces between individual ligand-receptor pairs. , 1994, Science.

[58]  Michael R. Shirts,et al.  Equilibrium free energies from nonequilibrium measurements using maximum-likelihood methods. , 2003, Physical review letters.

[59]  J. Andrew McCammon,et al.  Accelerated Adaptive Integration Method , 2014, The journal of physical chemistry. B.

[60]  M. Zacharias,et al.  Enhanced conformational sampling of nucleic acids by a new Hamiltonian replica exchange molecular dynamics approach. , 2009, The Journal of chemical physics.

[61]  Vijay S. Pande,et al.  OpenMM 7: Rapid development of high performance algorithms for molecular dynamics , 2016, bioRxiv.

[62]  Yi Xiao,et al.  Enhanced sampling of molecular dynamics simulation of peptides and proteins by double coupling to thermal bath , 2013, Journal of biomolecular structure & dynamics.

[63]  Yigong Shi,et al.  Structure of a human catalytic step I spliceosome , 2018, Science.

[64]  A. Laio,et al.  Optimizing the performance of bias-exchange metadynamics: folding a 48-residue LysM domain using a coarse-grained model. , 2010, The journal of physical chemistry. B.

[65]  B. Berne,et al.  Replica exchange with solute tempering: a method for sampling biological systems in explicit water. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[66]  G. Colombo,et al.  A Hamiltonian Replica Exchange Molecular Dynamics (MD) Method for the Study of Folding, Based on the Analysis of the Stabilization Determinants of Proteins , 2013, International journal of molecular sciences.

[67]  J. Pelletier,et al.  Substrate-Specific Screening for Mutational Hotspots Using Biased Molecular Dynamics Simulations , 2017 .

[68]  Yaoqi Zhou,et al.  Bias-Exchange Metadynamics Simulation of Membrane Permeation of 20 Amino Acids , 2018, International journal of molecular sciences.

[69]  J. Andrew McCammon,et al.  Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation , 2015, Journal of chemical theory and computation.

[70]  Chia-en A. Chang,et al.  Mechanism of the Association Pathways for a Pair of Fast and Slow Binding Ligands of HIV-1 Protease. , 2017, Biochemistry.

[71]  Y. Sugita,et al.  Flexible selection of the solute region in replica exchange with solute tempering: Application to protein-folding simulations. , 2018, The Journal of chemical physics.

[72]  Timothy Clark,et al.  An Efficient Metadynamics-Based Protocol To Model the Binding Affinity and the Transition State Ensemble of G-Protein-Coupled Receptor Ligands , 2017, J. Chem. Inf. Model..

[73]  J Andrew McCammon,et al.  CRISPR-Cas9 conformational activation as elucidated from enhanced molecular simulations , 2017, Proceedings of the National Academy of Sciences.

[74]  Yi-Ping Phoebe Chen,et al.  Exploring Inhibitor Release Pathways in Histone Deacetylases Using Random Acceleration Molecular Dynamics Simulations , 2012, J. Chem. Inf. Model..

[75]  Mark E Tuckerman,et al.  Molecular dynamics simulations of site point mutations in the TPR domain of cyclophilin 40 identify conformational states with distinct dynamic and enzymatic properties , 2018, The Journal of chemical physics.

[76]  H. Urbassek,et al.  Insulin adsorption on crystalline SiO 2 : Comparison between polar and nonpolar surfaces using accelerated molecular-dynamics simulations , 2017 .

[77]  Walter Thiel,et al.  Bridging the gap between thermodynamic integration and umbrella sampling provides a novel analysis method: "Umbrella integration". , 2005, The Journal of chemical physics.

[78]  J. D. de Pablo,et al.  Early-stage human islet amyloid polypeptide aggregation: Mechanisms behind dimer formation. , 2018, The Journal of chemical physics.

[79]  M. Parrinello,et al.  Well-tempered metadynamics: a smoothly converging and tunable free-energy method. , 2008, Physical review letters.

[80]  J. Snyder,et al.  The GluN2B‐Glu413Gly NMDA receptor variant arising from a de novo GRIN2B mutation promotes ligand‐unbinding and domain opening , 2018, Proteins.

[81]  Eric F Darve,et al.  Calculating free energies using average force , 2001 .

[82]  Haruki Nakamura,et al.  Virtual‐system‐coupled adaptive umbrella sampling to compute free‐energy landscape for flexible molecular docking , 2015, J. Comput. Chem..

[83]  Pratyush Tiwary,et al.  Prediction of Protein-Ligand Binding Poses via a Combination of Induced Fit Docking and Metadynamics Simulations. , 2016, Journal of chemical theory and computation.

[84]  M. Vandichel,et al.  First principle chemical kinetics in zeolites: the methanol-to-olefin process as a case study. , 2014, Chemical Society reviews.

[85]  Y. Sugita,et al.  Replica-exchange molecular dynamics method for protein folding , 1999 .

[86]  Olgun Guvench,et al.  Rigidity and flexibility in the tetrasaccharide linker of proteoglycans from atomic‐resolution molecular simulation , 2017, J. Comput. Chem..

[87]  Front , 2020, 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4).

[88]  M. Bonomi,et al.  Biasing Smarter, Not Harder, by Partitioning Collective Variables into Families in Parallel Bias Metadynamics. , 2018, Journal of chemical theory and computation.

[89]  Haruki Nakamura,et al.  Enhancement of canonical sampling by virtual-state transitions. , 2017, The Journal of chemical physics.

[90]  Guohui Li,et al.  Accurate Evaluation of Ion Conductivity of the Gramicidin A Channel Using a Polarizable Force Field without Any Corrections. , 2016, Journal of chemical theory and computation.

[91]  Donald Hamelberg,et al.  Towards fast, rigorous and efficient conformational sampling of biomolecules: Advances in accelerated molecular dynamics. , 2015, Biochimica et biophysica acta.

[92]  A. Tarakanova,et al.  Molecular model of human tropoelastin and implications of associated mutations , 2018, Proceedings of the National Academy of Sciences.

[93]  A. Cavalli,et al.  Role of Molecular Dynamics and Related Methods in Drug Discovery. , 2016, Journal of medicinal chemistry.

[94]  Levi C. T. Pierce,et al.  On the Use of Accelerated Molecular Dynamics to Enhance Configurational Sampling in Ab Initio Simulations , 2011, Journal of chemical theory and computation.

[95]  W. Cai,et al.  Free-energy landscapes of the coupled conformational transition and inclusion processes of altro-cyclodextrins , 2017 .

[96]  Yong Wang,et al.  Frequency adaptive metadynamics for the calculation of rare-event kinetics. , 2018, The Journal of chemical physics.

[97]  C. Ramseyer,et al.  Targeted molecular dynamics of an open-state KcsA channel. , 2005, The Journal of chemical physics.

[98]  Michele Parrinello,et al.  A variational conformational dynamics approach to the selection of collective variables in metadynamics. , 2017, The Journal of chemical physics.

[99]  A. Suenaga,et al.  Evaluation of protein–ligand affinity prediction using steered molecular dynamics simulations , 2017, Journal of biomolecular structure & dynamics.

[100]  A. Laio,et al.  A bias-exchange approach to protein folding. , 2007, The journal of physical chemistry. B.

[101]  Chao-yie Yang,et al.  Conformational Sampling and Binding Site Assessment of Suppression of Tumorigenicity 2 Ectodomain , 2016, PloS one.

[102]  Danfeng Shi,et al.  Revealing inhibition difference between PFI-2 enantiomers against SETD7 by molecular dynamics simulations, binding free energy calculations and unbinding pathway analysis , 2017, Scientific Reports.

[103]  Daniel R. Roe,et al.  Evaluation of Enhanced Sampling Provided by Accelerated Molecular Dynamics with Hamiltonian Replica Exchange Methods , 2014, The journal of physical chemistry. B.

[104]  Klaus Schulten,et al.  Implementation of Accelerated Molecular Dynamics in NAMD. , 2011, Computational science & discovery.

[105]  V. Pande,et al.  Multiplexed-replica exchange molecular dynamics method for protein folding simulation. , 2003, Biophysical journal.

[106]  Samia M. Hamed,et al.  Exploiting Chromophore-Protein Interactions through Linker Engineering To Tune Photoinduced Dynamics in a Biomimetic Light-Harvesting Platform. , 2018, Journal of the American Chemical Society.

[107]  Siewert J. Marrink,et al.  Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments , 2018, Chemical Society reviews.

[108]  Gabriel Stoltz,et al.  Smoothed Biasing Forces Yield Unbiased Free Energies with the Extended-System Adaptive Biasing Force Method , 2016, The journal of physical chemistry. B.

[109]  M. Lei,et al.  Structural insight into precursor tRNA processing by yeast ribonuclease P , 2018, Science.

[110]  Yigong Shi,et al.  Structures of the fully assembled Saccharomyces cerevisiae spliceosome before activation , 2018, Science.

[111]  D. Kern,et al.  Dynamic personalities of proteins , 2007, Nature.

[112]  Benoît Roux,et al.  Computation of Absolute Hydration and Binding Free Energy with Free Energy Perturbation Distributed Replica-Exchange Molecular Dynamics (FEP/REMD). , 2009, Journal of chemical theory and computation.

[113]  Massimiliano Bonomi,et al.  Efficient Sampling of High-Dimensional Free-Energy Landscapes with Parallel Bias Metadynamics. , 2015, Journal of chemical theory and computation.

[114]  J. Andrew McCammon,et al.  Unconstrained enhanced sampling for free energy calculations of biomolecules: a review , 2016, Molecular simulation.

[115]  Vijay S Pande,et al.  tICA-Metadynamics: Accelerating Metadynamics by Using Kinetically Selected Collective Variables. , 2017, Journal of chemical theory and computation.

[116]  William Sinko,et al.  w-REXAMD: A Hamiltonian Replica Exchange Approach to Improve Free Energy Calculations for Systems with Kinetically Trapped Conformations , 2013, Journal of chemical theory and computation.

[117]  J. Mongan,et al.  Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules. , 2004, The Journal of chemical physics.

[118]  Guohui Li,et al.  Validation of polarizable force field parameters for nucleic acids by inter-molecular interactions , 2016, Frontiers of Chemical Science and Engineering.

[119]  Dong Xu,et al.  Understanding the differences of the ligand binding/unbinding pathways between phosphorylated and non-phosphorylated ARH1 using molecular dynamics simulations , 2017, Scientific Reports.

[120]  Paul Robustelli,et al.  Developing a molecular dynamics force field for both folded and disordered protein states , 2018, Proceedings of the National Academy of Sciences.

[121]  Guoquan Zhou,et al.  Comparison of Adsorption of Proteins at Different Sizes on Pristine Graphene and Graphene Oxide , 2018 .

[122]  Christophe Chipot,et al.  The Adaptive Biasing Force Method: Everything You Always Wanted To Know but Were Afraid To Ask , 2014, The journal of physical chemistry. B.

[123]  Weihong Zhang,et al.  Accelerate Sampling in Atomistic Energy Landscapes Using Topology-Based Coarse-Grained Models. , 2014, Journal of chemical theory and computation.

[124]  Richard A. Cunha,et al.  RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview , 2018, Chemical reviews.

[125]  D. Pompon,et al.  Ligand Access Channels in Cytochrome P450 Enzymes: A Review , 2018, International journal of molecular sciences.

[126]  Marc R. Knecht,et al.  Biointerface Structural Effects on the Properties and Applications of Bioinspired Peptide-Based Nanomaterials. , 2017, Chemical reviews.

[127]  J. Mccammon,et al.  Accelerated molecular dynamics simulations of ligand binding to a muscarinic G-protein-coupled receptor , 2015, Quarterly Reviews of Biophysics.

[128]  Haruki Nakamura,et al.  Flexible binding simulation by a novel and improved version of virtual-system coupled adaptive umbrella sampling , 2016 .

[129]  Wei Yang,et al.  Practically Efficient and Robust Free Energy Calculations: Double-Integration Orthogonal Space Tempering. , 2012, Journal of chemical theory and computation.

[130]  B. M. Fulk MATH , 1992 .

[131]  W. Marsden I and J , 2012 .

[132]  Gerhard Hummer,et al.  Kinetics from Replica Exchange Molecular Dynamics Simulations. , 2017, Journal of chemical theory and computation.

[133]  Giovanni Bussi,et al.  Enhanced Sampling in Molecular Dynamics Using Metadynamics, Replica-Exchange, and Temperature-Acceleration , 2013, Entropy.

[134]  Eric Darve,et al.  Adaptive biasing force method for scalar and vector free energy calculations. , 2008, The Journal of chemical physics.

[135]  R. Wade,et al.  How do substrates enter and products exit the buried active site of cytochrome P450cam? 1. Random expulsion molecular dynamics investigation of ligand access channels and mechanisms. , 2000, Journal of molecular biology.

[136]  R. Swendsen,et al.  THE weighted histogram analysis method for free‐energy calculations on biomolecules. I. The method , 1992 .

[137]  Bernard R. Brooks,et al.  Self‐guided Langevin dynamics via generalized Langevin equation , 2016, J. Comput. Chem..

[138]  Youyong Li,et al.  Characterizing Drug-Target Residence Time with Metadynamics: How To Achieve Dissociation Rate Efficiently without Losing Accuracy against Time-Consuming Approaches , 2017, J. Chem. Inf. Model..

[139]  Jianyong Liu,et al.  GPCR A2AAR Agonist Binding and Induced Conformation Changes of Functional Switches , 2014 .

[140]  Guohui Li,et al.  Higher Accuracy Achieved in the Simulations of Protein Structure Refinement, Protein Folding, and Intrinsically Disordered Proteins Using Polarizable Force Fields. , 2018, The journal of physical chemistry letters.

[141]  Guo-Hui Li,et al.  Recent Developments in Using Molecular Dynamics Simulation Techniques to Study Biomolecules , 2017 .

[142]  Berk Hess,et al.  GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers , 2015 .

[143]  Xuliang Zhao,et al.  7. , 2020, The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians.

[144]  F. Tama,et al.  Computational investigation of the conformational dynamics in Tom20‐mitochondrial presequence tethered complexes , 2018, Proteins.

[145]  M. Parrinello,et al.  Unbinding Kinetics of a p38 MAP Kinase Type II Inhibitor from Metadynamics Simulations. , 2017, Journal of the American Chemical Society.

[146]  George C Schatz,et al.  Steered molecular dynamics studies of the potential of mean force for peptide amphiphile self-assembly into cylindrical nanofibers. , 2013, The journal of physical chemistry. A.

[147]  A. Cavalli,et al.  Single-molecule pulling simulations can discern active from inactive enzyme inhibitors. , 2010, Journal of the American Chemical Society.

[148]  H. Urbassek,et al.  Accelerated Molecular Dynamics Study of the Effects of Surface Hydrophilicity on Protein Adsorption. , 2016, Langmuir : the ACS journal of surfaces and colloids.

[149]  K. Schulten,et al.  Unbinding of retinoic acid from its receptor studied by steered molecular dynamics. , 1999, Biophysical journal.

[150]  Giovanni Bussi,et al.  Enhanced Conformational Sampling Using Replica Exchange with Collective-Variable Tempering , 2015, Journal of chemical theory and computation.

[151]  Yigong Shi,et al.  Structure of a yeast spliceosome at 3.6-angstrom resolution , 2015, Science.

[152]  Eric F Darve,et al.  Investigating the role of non-covalent interactions in conformation and assembly of triazine-based sequence-defined polymers. , 2018, The Journal of chemical physics.

[153]  A. Laio,et al.  Equilibrium free energies from nonequilibrium metadynamics. , 2006, Physical Review Letters.

[154]  Yuji Sugita,et al.  Surface-Tension Replica-Exchange Molecular Dynamics Method for Enhanced Sampling of Biological Membrane Systems. , 2013, Journal of chemical theory and computation.

[155]  William Sinko,et al.  Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations , 2011, Journal of chemical theory and computation.

[156]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[157]  Fangqiang Zhu,et al.  Thermodynamics of Protein Folding Studied by Umbrella Sampling along a Reaction Coordinate of Native Contacts. , 2017, Journal of chemical theory and computation.

[158]  Wang,et al.  Replica Monte Carlo simulation of spin glasses. , 1986, Physical review letters.