Optimized Markov state models for metastable systems
Optimized Markov state models for metastable systems
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DOI：
10.1063/1.4954769
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发表时间：
2016-07-14
影响因子：
4.4
通讯作者：
Vanden-Eijnden, Eric
中科院分区：
文献类型：
--
作者：
Guarnera, Enrico;Vanden-Eijnden, Eric
提出了一种在一组试验状态中识别优化亚稳定指数的目标状态，并将这些目标状态作为里程碑(或核心集)来构建马尔可夫状态模型(MSM)的方法。如果优化的亚稳性指数很小，这就自动保证了MSM的准确性，因为目标里程碑之间的过渡确实是近似马尔可夫的。该方法易于实现和使用，它不要求试验里程碑上的动态是马尔可夫的，它还提供了通过将每个试验里程碑分配给它最有可能接下来访问的目标里程碑来划分系统的状态空间并识别过渡状态区域的可能性。在这里，该方法在Gly-Ala-Gly多肽上进行了测试，在没有关于这些状态的先验信息的情况下，它被证明正确地识别了分子的二面角空间中的预期亚稳态。它还被应用于分析Beta3S迷你蛋白的折叠景观，其中它被证明是折叠盆地的连接枢纽，在富含螺旋的区域和富含β的区域之间，富含螺旋的区域是熵稳定的，富含β的区域是能量稳定的，起到动力学陷阱的作用。(C)2016年作者(S)。
A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones ( or core sets) to build Markov State Models ( MSMs). If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM, in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space by assigning every trial milestone to the target milestones it is most likely to visit next and to identify transition state regions. Here the method is tested on the Gly-Ala-Gly peptide, where it is shown to correctly identify the expected metastable states in the dihedral angle space of the molecule without a priori information about these states. It is also applied to analyze the folding landscape of the Beta3s mini-protein, where it is shown to identify the folded basin as a connecting hub between an helix-rich region, which is entropically stabilized, and a beta-rich region, which is energetically stabilized and acts as a kinetic trap. (C) 2016 Author(s).