Literature DB >> 27054809

A Stochastic, Resonance-Free Multiple Time-Step Algorithm for Polarizable Models That Permits Very Large Time Steps.

Daniel T Margul1, Mark E Tuckerman1,2,3.   

Abstract

Molecular dynamics remains one of the most widely used computational tools in the theoretical molecular sciences to sample an equilibrium ensemble distribution and/or to study the dynamical properties of a system. The efficiency of a molecular dynamics calculation is limited by the size of the time step that can be employed, which is dictated by the highest frequencies in the system. However, many properties of interest are connected to low-frequency, long time-scale phenomena, requiring many small time steps to capture. This ubiquitous problem can be ameliorated by employing multiple time-step algorithms, which assign different time steps to forces acting on different time scales. In such a scheme, fast forces are evaluated more frequently than slow forces, and as the former are often computationally much cheaper to evaluate, the savings can be significant. Standard multiple time-step approaches are limited, however, by resonance phenomena, wherein motion on the fastest time scales limits the step sizes that can be chosen for the slower time scales. In atomistic models of biomolecular systems, for example, the largest time step is typically limited to around 5 fs. Previously, we introduced an isokinetic extended phase-space algorithm (Minary et al. Phys. Rev. Lett. 2004, 93, 150201) and its stochastic analog (Leimkuhler et al. Mol. Phys. 2013, 111, 3579) that eliminate resonance phenomena through a set of kinetic energy constraints. In simulations of a fixed-charge flexible model of liquid water, for example, the time step that could be assigned to the slow forces approached 100 fs. In this paper, we develop a stochastic isokinetic algorithm for multiple time-step molecular dynamics calculations using a polarizable model based on fluctuating dipoles. The scheme developed here employs two sets of induced dipole moments, specifically, those associated with short-range interactions and those associated with a full set of interactions. The scheme is demonstrated on the polarizable AMOEBA water model. As was seen with fixed-charge models, we are able to obtain large time steps exceeding 100 fs, allowing calculations to be performed 10 to 20 times faster than standard thermostated molecular dynamics.

Entities:  

Year:  2016        PMID: 27054809     DOI: 10.1021/acs.jctc.6b00188

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  5 in total

1.  Artificial Intelligence for Accelerating Time Integrations in Multiscale Modeling.

Authors:  Changnian Han; Peng Zhang; Danny Bluestein; Guojing Cong; Yuefan Deng
Journal:  J Comput Phys       Date:  2020-12-07       Impact factor: 4.645

2.  Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions.

Authors:  Xiaoliang Pan; Junjie Yang; Richard Van; Evgeny Epifanovsky; Junming Ho; Jing Huang; Jingzhi Pu; Ye Mei; Kwangho Nam; Yihan Shao
Journal:  J Chem Theory Comput       Date:  2021-09-01       Impact factor: 6.578

Review 3.  Advanced Potential Energy Surfaces for Molecular Simulation.

Authors:  Alex Albaugh; Henry A Boateng; Richard T Bradshaw; Omar N Demerdash; Jacek Dziedzic; Yuezhi Mao; Daniel T Margul; Jason Swails; Qiao Zeng; David A Case; Peter Eastman; Lee-Ping Wang; Jonathan W Essex; Martin Head-Gordon; Vijay S Pande; Jay W Ponder; Yihan Shao; Chris-Kriton Skylaris; Ilian T Todorov; Mark E Tuckerman; Teresa Head-Gordon
Journal:  J Phys Chem B       Date:  2016-09-22       Impact factor: 3.466

4.  Ab initio molecular dynamics simulations of liquid water using high quality meta-GGA functionals.

Authors:  Luis Ruiz Pestana; Narbe Mardirossian; Martin Head-Gordon; Teresa Head-Gordon
Journal:  Chem Sci       Date:  2017-02-27       Impact factor: 9.825

5.  Density artefacts at interfaces caused by multiple time-step effects in molecular dynamics simulations.

Authors:  Dominik Sidler; Marc Lehner; Simon Frasch; Michael Cristófol-Clough; Sereina Riniker
Journal:  F1000Res       Date:  2018-11-05
  5 in total

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