马尔科夫国家模型:从艺术到科学
Brooke E Husic1, Vijay S Pande1
1Department of Chemistry, Stanford University , Stanford, California 94305, United States.
Journal of the American Chemical Society
|January 12, 2018
概括
马尔科夫状态模型 (MSM) 为分析复杂的分子动力学 (MD) 模拟提供了强大的框架. 最近的进步, 特别是变异性方法, 简化了MSM的构造,
科学领域:
- 计算化学
- 生物物理
- 统计力学
背景情况:
- 马尔科夫状态模型 (MSM) 广泛用于分析分子动力学 (MD) 模拟.
- 这一领域在几十年内发生了显著的发展,主要是方法和软件的发展.
- 早期的工作集中在基础概念上,而后来的研究建立了MD分析的MSM.
研究的目的:
- 为广大受众提供马尔科夫状态模型 (MSM) 的历史概述.
- 突出MSM方法和应用中的关键发展和转折点.
- 展示MSM在理解生物过程和促进药物发现方面的影响.
主要方法:
- 一份关于MSM的开创性论文和方法的时间表.
- 重点是开发一个客观的MSM构建的变量原则.
- 在模型选择和开源软件利用方面整合最佳实践.
主要成果:
- 2013年推出变量原则标志着对系统和客观的MSM建设的转变.
- 进步使MSM在蛋白质折叠,化和联结等领域的广泛应用成为可能.
- 开源软件使得MSM分析变得更加民主,
结论:
- MSM是分析复杂动态系统的强大且越来越容易使用的工具.
- 目前的研究前沿集中在进一步的方法改进和新应用上.
- 在实验设计和加速药物发现工作中发挥重要作用.
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