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使用MSMBuilder构建马尔可夫状态模型并使用BACE对其进行粗粒化的教程。

A tutorial on building markov state models with MSMBuilder and coarse-graining them with BACE.

作者信息

Bowman Gregory R

机构信息

Departments of Molecular & Cell Biology and Chemistry, University of California, Berkeley, Berkeley, CA, USA.

出版信息

Methods Mol Biol. 2014;1084:141-58. doi: 10.1007/978-1-62703-658-0_8.

Abstract

Markov state models (MSMs) are a powerful means of (1) making sense of molecular simulations, (2) making a quantitative connection between simulation and experiment, and (3) driving efficient simulations. A Markov model can be thought of as a map of the conformational space a molecule explores. Instead of having towns and cities connected with roads labeled with speed limits, a Markov model has conformational states and probabilities of transitioning between pairs of these states. This tutorial describes how to build Markov models and a few of the basic analyses that can be performed with the MSMBuilder software package.

摘要

马尔可夫状态模型(MSMs)是一种强大的方法,用于(1)理解分子模拟,(2)在模拟和实验之间建立定量联系,以及(3)驱动高效模拟。马尔可夫模型可以被认为是分子探索的构象空间的地图。与用限速标记道路连接的城镇不同,马尔可夫模型具有构象状态以及这些状态对之间转换的概率。本教程描述了如何构建马尔可夫模型以及可以使用MSMBuilder软件包执行的一些基本分析。

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