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WESTPA 2.0 稀有事件采样软件教程套件 [文章 v2.0]

A Suite of Tutorials for the WESTPA 2.0 Rare-Events Sampling Software [Article v2.0].

作者信息

Bogetti Anthony T, Leung Jeremy M G, Russo John D, Zhang She, Thompson Jeff P, Saglam Ali S, Ray Dhiman, Mostofian Barmak, Pratt A J, Abraham Rhea C, Harrison Page O, Dudek Max, Torrillo Paul A, DeGrave Alex J, Adhikari Upendra, Faeder James R, Andricioaei Ioan, Adelman Joshua L, Zwier Matthew C, LeBard David N, Zuckerman Daniel M, Chong Lillian T

机构信息

Department of Chemistry, University of Pittsburgh, Pittsburgh, PA.

Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR.

出版信息

Living J Comput Mol Sci. 2023;5(1). doi: 10.33011/livecoms.5.1.1655.

Abstract

The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in generating pathways and rate constants for rare events such as protein folding and protein binding using atomistic molecular dynamics simulations. Here we present two sets of tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. The first set of more basic tutorials describes a range of simulation types, from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding. The second set ecompasses six advanced tutorials instructing users in the best practices of using key new features and plugins/extensions of the WESTPA 2.0 software package, which consists of major upgrades for larger systems and/or slower processes. The advanced tutorials demonstrate the use of the following key features: (i) a generalized resampler module for the creation of "binless" schemes, (ii) a minimal adaptive binning scheme for more efficient surmounting of free energy barriers, (iii) streamlined handling of large simulation datasets using an HDF5 framework, (iv) two different schemes for more efficient rate-constant estimation, (v) a Python API for simplified analysis of WE simulations, and (vi) plugins/extensions for Markovian Weighted Ensemble Milestoning and WE rule-based modeling for systems biology models. Applications of the advanced tutorials include atomistic and non-spatial models, and consist of complex processes such as protein folding and the membrane permeability of a drug-like molecule. Users are expected to already have significant experience with running conventional molecular dynamics or systems biology simulations.

摘要

加权系综(WE)策略已被证明在使用原子分子动力学模拟为蛋白质折叠和蛋白质结合等罕见事件生成路径和速率常数方面非常高效。在此,我们提供两组教程,指导用户使用WESTPA软件针对各种应用进行WE模拟的最佳实践,包括准备、执行和分析。第一组更基础的教程描述了一系列模拟类型,从明确溶剂中的分子缔合过程到更复杂的过程,如主客体缔合、肽构象采样和蛋白质折叠。第二组包含六个高级教程,指导用户使用WESTPA 2.0软件包的关键新功能和插件/扩展的最佳实践,该软件包对更大系统和/或更慢过程进行了重大升级。高级教程展示了以下关键功能的使用:(i)用于创建“无箱”方案的广义重采样器模块;(ii)用于更有效地跨越自由能垒的最小自适应装箱方案;(iii)使用HDF5框架简化处理大型模拟数据集;(iv)两种用于更有效估计速率常数的不同方案;(v)用于简化WE模拟分析的Python API;以及(vi)用于马尔可夫加权系综里程碑法和用于系统生物学模型的基于WE规则建模的插件/扩展。高级教程的应用包括原子模型和非空间模型,涵盖蛋白质折叠和类药物分子的膜通透性等复杂过程。预计用户已经具备运行传统分子动力学或系统生物学模拟的丰富经验。

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