Force Field-Driven Backmapping for Multiscale Molecular Dynamics.

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation Pub Date : 2025-10-20 DOI:10.1021/acs.jctc.5c00677

Xu Guo,Andrew Abi-Mansour,Peter Ortoleva

引用次数: 0

Abstract

Molecular Dynamics (MD) is a powerful simulation technique for capturing the dynamics and equilibrium properties of molecular and macromolecular systems at atomic resolution. However, MD faces significant practical challenges due to the limited time and spatial scales it can reach. To address these challenges, various coarse-grained (CG) and multiscale methods have been developed. In particular, Multiscale Factorization (MF) is a promising multiscale framework that provides a self-consistent and efficient way of coevolving the atomistic and CG states without requiring calibration of the CG model. MF achieves this coevolution by backmapping the CG state to an ensemble of all-atom microstates consistent with the latter. In this study, we introduce a force field-driven backmapping method that yields improved accuracy and numerical stability over existing methods, enabling the use of larger CG timesteps in the course of a multiscale simulation.

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多尺度分子动力学的力场驱动反向映射。

分子动力学（MD）是一种强大的模拟技术，用于在原子分辨率上捕捉分子和大分子系统的动力学和平衡特性。然而，由于时间和空间尺度的限制，MD在实践中面临着巨大的挑战。为了应对这些挑战，人们开发了各种粗粒度（CG）和多尺度方法。特别是，多尺度分解（MF）是一个很有前途的多尺度框架，它提供了一种自洽和有效的方式来共同进化原子状态和CG状态，而无需校准CG模型。MF通过将CG状态反向映射到与后者一致的全原子微观状态的集合来实现这种协同进化。在本研究中，我们引入了一种力场驱动的反向映射方法，该方法比现有方法具有更高的精度和数值稳定性，能够在多尺度模拟过程中使用更大的CG时间步长。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Chemical Theory and Computation 化学-物理：原子、分子和化学物理

CiteScore

9.90

自引率

16.40%

发文量

568

审稿时长

1 months

期刊介绍： The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.