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混合级联型分子动力学与马尔可夫状态模型在高效自由能计算中的应用。

Hybrid Cascade-Type Molecular Dynamics with a Markov State Model for Efficient Free Energy Calculations.

机构信息

Center for Computational Sciences , University of Tsukuba , 1-1-1 Tennodai , Tsukuba , Ibaraki 305-8577 , Japan.

出版信息

J Chem Theory Comput. 2019 Jan 8;15(1):680-687. doi: 10.1021/acs.jctc.8b00802. Epub 2018 Dec 7.

Abstract

A protocol for calculating free energy landscapes (FELs) is proposed based on a combination of two cascade-type molecular dynamics (MD) methods, parallel cascade selection MD (PaCS-MD) and outlier flooding method (OFLOOD), with the help of a Markov state model (MSM). The former rapidly generates approximated transition paths directly connecting reactants with products, and the latter complementary resamples marginal conformational subspaces. Trajectories obtained by them give reliable microstates in MSM providing accurate FEL with low computational costs. As a demonstration, the present method was applied to a miniprotein (Chignolin and Trp-cage) in explicit water and successfully elucidated multiple folding paths on their free energy landscapes. Our method could be applicable to a wide variety of biological systems to estimate their free energy profiles.

摘要

提出了一种基于两种级联式分子动力学(MD)方法——平行级联选择 MD(PaCS-MD)和异常值洪水法(OFLOOD)相结合的自由能景观(FEL)计算方案,并借助马尔可夫状态模型(MSM)。前者可快速生成直接连接反应物和产物的近似过渡路径,后者则对边缘构象子空间进行补充重采样。通过它们获得的轨迹在 MSM 中提供可靠的微观状态,以较低的计算成本获得准确的 FEL。作为一个示例,该方法应用于明胶(Chignolin 和 Trp-cage)在显式水中的情况,成功地阐明了其自由能景观上的多种折叠路径。我们的方法可适用于广泛的生物体系来估算它们的自由能分布。

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