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Best Practices for Foundations in Molecular Simulations [Article v1.0].分子模拟基础的最佳实践 [文章v1.0]
Living J Comput Mol Sci. 2019;1(1). doi: 10.33011/livecoms.1.1.5957. Epub 2018 Nov 29.
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REVO: Resampling of ensembles by variation optimization.REVO:通过变异优化对集成进行重采样。
J Chem Phys. 2019 Jun 28;150(24):244112. doi: 10.1063/1.5100521.
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Statistical Uncertainty Analysis for Small-Sample, High Log-Variance Data: Cautions for Bootstrapping and Bayesian Bootstrapping.小样本、高对数方差数据的统计不确定性分析:自助法和贝叶斯自助法的注意事项
J Chem Theory Comput. 2019 Jun 11;15(6):3499-3509. doi: 10.1021/acs.jctc.9b00015. Epub 2019 May 7.
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Computational Estimation of Microsecond to Second Atomistic Folding Times.微秒到秒尺度的原子折叠时间的计算估计。
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Protein-protein binding pathways and calculations of rate constants using fully-continuous, explicit-solvent simulations.蛋白质-蛋白质结合途径及使用全连续显式溶剂模拟计算速率常数
Chem Sci. 2018 Dec 27;10(8):2360-2372. doi: 10.1039/c8sc04811h. eCollection 2019 Feb 28.
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Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0].分子模拟中不确定性量化与采样质量的最佳实践 [文章v1.0]
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Mapping the Ligand Binding Landscape.配体结合景观的绘制。
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Predicting ligand binding affinity using on- and off-rates for the SAMPL6 SAMPLing challenge.使用 SAMPL6 SAMPLing 挑战的结合和解离速率预测配体结合亲和力。
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Rare-event sampling of epigenetic landscapes and phenotype transitions.表观遗传景观和表型转变的稀有事件采样。
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Large enhancement of response times of a protein conformational switch by computational design.通过计算设计大幅提高蛋白质构象开关的响应时间。
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WESTPA稀有事件采样软件教程套件[文章版本1.0]

A Suite of Tutorials for the WESTPA Rare-Events Sampling Software [Article v1.0].

作者信息

Bogetti Anthony T, Mostofian Barmak, Dickson Alex, Pratt A J, Saglam Ali S, Harrison Page O, Adelman Joshua L, Dudek Max, Torrillo Paul A, DeGrave Alex J, Adhikari Upendra, Zwier Matthew C, 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. 2019;1(2). doi: 10.33011/livecoms.1.2.10607. Epub 2019 Oct 4.

DOI:10.33011/livecoms.1.2.10607
PMID:32395705
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7213600/
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 five tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. Users are expected to already have significant experience with running standard molecular dynamics simulations using the underlying dynamics engine of interest (e.g. Amber, Gromacs, OpenMM). The tutorials range from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding.

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。在这里,我们提供五个教程,指导用户使用WESTPA软件为各种应用准备、进行和分析WE模拟的最佳实践。预计用户已经在使用感兴趣的基础动力学引擎(如Amber、Gromacs、OpenMM)运行标准分子动力学模拟方面有丰富经验。这些教程涵盖了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。