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Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics

机译:状态和速率缺失的马尔可夫状态模型的不确定性:应用于使用高温分子动力学获得的室温动力学模型

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Several studies in the past have generated Markov State Models (MSMs), i.e., kinetic models, of biomolecular systems by post-analyzing long standard molecular dynamics (MD) calculations at the temperature of interest and focusing on the maximally ergodic subset of states. Questions related to goodness of these models, namely, importance of the missing states and kinetic pathways, and the time for which the kinetic model is valid, are generally left unanswered. We show that similar questions arise when we generate a room-temperature MSM (denoted MSM-A) for solvated alanine dipeptide using state-constrained MD calculations at higher temperatures and Arrhenius relation - the main advantage of such a procedure being a speed-up of several thousand times over standard MD-based MSM building procedures. Bounds for rate constants calculated using probability theory from state-constrained MD at room temperature help validate MSM-A. However, bounds for pathways possibly missing in MSM-A show that alternate kinetic models exist that produce the same dynamical behaviour at short time scales as MSM-A but diverge later. Even in the worst case scenario, MSM-A is found to be valid longer than the time required to generate it. Concepts introduced here can be straightforwardly extended to other MSM building techniques. (C) 2015 AIP Publishing LLC.
机译:过去的几项研究通过在感兴趣的温度下对长标准分子动力学(MD)计算进行后分析并关注状态的最大遍历子集来生成生物分子系统的马尔可夫状态模型(MSM),即动力学模型。与这些模型的优劣有关的问题,即缺失状态和动力学路径的重要性,以及动力学模型有效的时间,通常都无法回答。我们展示了当我们在较高温度和Arrhenius关系下使用状态约束的MD计算生成溶剂化的丙氨酸二肽的室温MSM(表示为MSM-A)时,会出现类似的问题-这种方法的主要优点是可以加速相对于基于MD的标准MSM构建过程要高出数千倍。在室温下使用概率论从状态受限的MD计算出的速率常数的界线有助于验证MSM-A。但是,MSM-A中可能缺少的途径的边界表明,存在替代的动力学模型,这些模型在短时间尺度上产生与MSM-A相同的动力学行为,但后来却有所分歧。即使在最坏的情况下,MSM-A的有效期也比生成它所需的时间更长。此处介绍的概念可以直接扩展到其他MSM构建技术。 (C)2015 AIP Publishing LLC。

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