基于马尔可夫模型的分子结构数据分析中不同设计决策的系统研究:扩展摘要

S. Roychoudhury, Amarda Shehu
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引用次数: 0

摘要

建模和仿真软件现在为我们提供了在生理条件下肽和蛋白质导航的结构空间视图。这样的软件,如分子动力学,产生由动态分子访问的连续结构的轨迹,但不容易暴露结构状态下的潜在组织,以便总结当前结构状态上的平衡动力学。在本文中,我们研究了马尔可夫状态模型在这方面的能力。当我们使用一个已建立的软件来这样做时,我们在其中分析不同的设计决策,并测量它们对获得的结果的影响。我们提出了我们的研究结果在优化设计决策,揭示在过程中的动态的met -脑啡肽。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Molecular Structure Data]{Systematic Study of Different Design Decisions in Markov Model-based Analysis of Molecular Structure Data: Extended Abstract
Modeling and simulation software now provide us with a view of the structure space navigated by peptides and proteins under physiological conditions. Such software, such as Molecular Dynamics, yields trajectories of consecutive structures accessed by a dynamic molecule, but does not readily expose the underlying organization in the structure state so as to summarize the equilibrium dynamics over the present structural states. In this paper we investigate Markov State Models on their ability to do so. While we make use of an established software to do so, we analyze within it different design decisions and measure their impact on the obtained results. We present our findings on optimal design decisions, revealing in the process the dynamics of the Met-enkephaline peptide.
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