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

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

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WESTPA 2.0 罕见事件采样软件教程套件 [Article v2.0]。
在利用原子分子动力学模拟生成蛋白质折叠和蛋白质结合等罕见事件的路径和速率常数方面,加权合集(WE)策略已被证明具有很高的效率。我们在此介绍两套教程,指导用户使用 WESTPA 软件为各种应用准备、执行和分析 WE 仿真的最佳实践。第一套较为基础的教程介绍了一系列模拟类型,从显式溶剂中的分子结合过程到更复杂的过程,如主-客结合、肽构象取样和蛋白质折叠。第二套教程包括六个高级教程,指导用户如何使用 WESTPA 2.0 软件包的主要新功能和插件/扩展程序,其中包括针对大型系统和/或较慢过程的重大升级。高级教程演示了以下关键功能的使用:(i) 用于创建 "无二进制 "方案的通用重采样器模块,(ii) 用于更有效地克服自由能障碍的最小自适应二进制方案,(iii) 使用 HDF5 框架简化大型模拟数据集的处理,(iv) 用于更有效地估计速率常数的两种不同方案,(v) 用于简化 WE 模拟分析的 Python API,以及 (vi) 用于马尔可夫加权集合 Milestoning 和基于 WE 规则的系统生物学模型建模的插件/扩展。高级教程的应用包括原子模型和非空间模型,以及蛋白质折叠和类药物分子的膜渗透性等复杂过程。希望用户在运行常规分子动力学或系统生物学模拟方面已经有了丰富的经验。
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