Open AccessJournal Article
Finding Transition Pathways Using the String Method with Swarms of Trajectories
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An approach to find transition pathways in complex systems is presented and the committor distribution is found to be peaked around 1/2 near the free energy maximum between the two stable states, confirming that a genuine transition state has been localized in this complex multidimensional system.Abstract:
An approach to find transition pathways in complex systems is presented. The method, which is related to the string method in collective variables of Maragliano et al. (J. Chem. Phys. 2006, 125, 024106), is conceptually simple and straightforward to implement. It consists of refining a putative transition path in the multidimensional space supported by a set of collective variables using the average dynamic drift of those variables. This drift is estimated on-the-fly via swarms of short unbiased trajectories started at different points along the path. Successive iterations of this algorithm, which can be naturally distributed over many computer nodes with negligible interprocessor communication, refine an initial trial path toward the most probable transition path (MPTP) between two stable basins. The method is first tested by determining the pathway for the C7eq to C7ax transition in an all-atom model of the alanine dipeptide in vacuum, which has been studied previously with the string method in collective variables. A transition path is found with a committor distribution peaked at 1/2 near the free energy maximum, in accord with previous results. Last, the method is applied to the allosteric conformational change in the nitrogen regulatory protein C (NtrC), represented here with a two-state elastic network model. Even though more than 550 collective variables are used to describe the conformational change, the path converges rapidly. Again, the committor distribution is found to be peaked around 1/2 near the free energy maximum between the two stable states, confirming that a genuine transition state has been localized in this complex multidimensional system.read more
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CHARMM: the biomolecular simulation program.
Bernard R. Brooks,Charles L. Brooks,Alexander D. MacKerell,Lennart Nilsson,Robert J. Petrella,Benoît Roux,Youngdo Won,Georgios Archontis,Christian Bartels,Stefan Boresch,Amedeo Caflisch,Leo S. D. Caves,Qiang Cui,Aaron R. Dinner,Michael Feig,Stefan Fischer,Jiali Gao,Milan Hodošček,Wonpil Im,K. Kuczera,Themis Lazaridis,Jianpeng Ma,V. Ovchinnikov,Emanuele Paci,Richard W. Pastor,Carol Beth Post,Jingzhi Pu,M. Schaefer,Bruce Tidor,Richard M. Venable,H. L. Woodcock,Xiongwu Wu,Wei Yang,Darrin M. York,Martin Karplus,Martin Karplus +35 more
TL;DR: An overview of the CHARMM program as it exists today is provided with an emphasis on developments since the publication of the original CHARMM article in 1983.
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Scalable molecular dynamics on CPU and GPU architectures with NAMD.
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References
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Journal ArticleDOI
CHARMM: the biomolecular simulation program.
Bernard R. Brooks,Charles L. Brooks,Alexander D. MacKerell,Lennart Nilsson,Robert J. Petrella,Benoît Roux,Youngdo Won,Georgios Archontis,Christian Bartels,Stefan Boresch,Amedeo Caflisch,Leo S. D. Caves,Qiang Cui,Aaron R. Dinner,Michael Feig,Stefan Fischer,Jiali Gao,Milan Hodošček,Wonpil Im,K. Kuczera,Themis Lazaridis,Jianpeng Ma,V. Ovchinnikov,Emanuele Paci,Richard W. Pastor,Carol Beth Post,Jingzhi Pu,M. Schaefer,Bruce Tidor,Richard M. Venable,H. L. Woodcock,Xiongwu Wu,Wei Yang,Darrin M. York,Martin Karplus,Martin Karplus +35 more
TL;DR: An overview of the CHARMM program as it exists today is provided with an emphasis on developments since the publication of the original CHARMM article in 1983.
Journal ArticleDOI
Scalable molecular dynamics on CPU and GPU architectures with NAMD.
James C. Phillips,David J. Hardy,Julio D.C. Maia,John E. Stone,João V. Ribeiro,Rafael C. Bernardi,Ronak Buch,Giacomo Fiorin,Jérôme Hénin,Wei Jiang,Ryan McGreevy,Marcelo C. R. Melo,Brian K. Radak,Robert D. Skeel,Abhishek Singharoy,Yi Wang,Benoît Roux,Aleksei Aksimentiev,Zaida Luthey-Schulten,Laxmikant V. Kale,Klaus Schulten,Christophe Chipot,Emad Tajkhorshid +22 more
TL;DR: The main features of NAMD are reviewed, including the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and their applicability to specific problems.
Journal ArticleDOI
Using collective variables to drive molecular dynamics simulations
TL;DR: The modular framework presented enables one to combine existing collective variables into new ones, and combine any chosen collective variable with available biasing methods, and is extensible, and portable between commonly used MD simulation engines.
Journal ArticleDOI
Transition-Path Theory and Path-Finding Algorithms for the Study of Rare Events
Weinan E,Eric Vanden-Eijnden +1 more
TL;DR: The basic components of transition-path theory and path-finding algorithms are reviewed and connections with the classical transition-state theory are discussed.