Using generalized ensemble simulations and Markov state models to identify conformational states

被引:238
作者
Bowman, Gregory R. [2 ]
Huang, Xuhui [3 ]
Pande, Vijay S. [1 ,2 ]
机构
[1] Stanford Univ, Dept Chem, Stanford, CA 94305 USA
[2] Stanford Univ, Biophys Program, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA
基金
美国国家卫生研究院;
关键词
Clustering; Molecular dynamics; Thermodynamics; Kinetics; MOLECULAR-DYNAMICS TRAJECTORIES; FREE-ENERGY; BETA-HAIRPIN; KINETICS; PERFORMANCE; ALGORITHMS; LANDSCAPE;
D O I
10.1016/j.ymeth.2009.04.013
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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. (c) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:197 / 201
页数:5
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