使用广义系综模拟和马尔可夫状态模型来识别构象状态。
Using generalized ensemble simulations and Markov state models to identify conformational states.
作者信息
Bowman Gregory R, Huang Xuhui, Pande Vijay S
机构信息
Biophysics Program, Stanford University, Stanford, CA 94305, USA.
出版信息
Methods. 2009 Oct;49(2):197-201. doi: 10.1016/j.ymeth.2009.04.013. Epub 2009 May 4.
Abstract
Part of understanding a molecule's conformational dynamics is mapping out the dominant metastable, or long lived, states that it occupies. Once identified, the rates for transitioning between these states may then be determined in order to create a complete model of the system's conformational dynamics. Here we describe the use of the MSMBuilder package (now available at http://simtk.org/home/msmbuilder/) to build Markov State Models (MSMs) to identify the metastable states from Generalized Ensemble (GE) simulations, as well as other simulation datasets. Besides building MSMs, the code also includes tools for model evaluation and visualization.
摘要
理解分子构象动力学的一部分是描绘出它所占据的主要亚稳态或长寿命状态。一旦确定这些状态，就可以确定它们之间的转换速率，以便创建系统构象动力学的完整模型。在这里，我们描述了使用MSMBuilder软件包（现在可从http://simtk.org/home/msmbuilder/获取）来构建马尔可夫状态模型（MSM），以便从广义系综（GE）模拟以及其他模拟数据集中识别亚稳态。除了构建MSM，该代码还包括用于模型评估和可视化的工具。
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