通过系统地绘制时间社区的地图,构建多层次的马尔科夫状态模型.
Nir Nitskansky1, Kessem Clein1, Barak Raveh1
1School of Computer Science and Engineering, The Hebrew University of Jerusalem, The Edmond J. Safra Campus, 9190401, Israel.
我们开发了多尺度马尔科夫状态模型 (mMSMs),以捕捉跨多个时间尺度的生物分子动态. 这种方法有效地绘制复杂的能源景观,并揭示了不同规模的动态如何对生物功能产生影响.
科学领域:
- 计算生物学 计算生物学
- 生物物理学的生物物理.
- 分子动力学分子动力学
背景情况:
- 生物分子通过元稳定状态之间的动态过渡来起作用.
- 马尔科夫状态模型 (MSM) 在单个时间尺度上分析这些转变.
- 生物过程涉及广泛的时间尺度的动态.
研究的目的:
- 引入一种方法,同时在多个时间尺度上分析生物分子动力学.
- 开发一个算法来生成这些多尺度模型.
- 证明该方法在绘制复杂系统中的能力.
主要方法:
- 使用MSMs的层次结构开发多层次马尔科夫状态模型 (mMSMs).
- 实施mMSM-explore,这是一个无监督的算法,用于自适应采样.
- 在飞行时识别暂时转移稳定的状态.
- 玩具系统的基准测试,二和一个小蛋白质.
主要成果:
- 能效地绘制能源景观和多层次层次结构.
- 准确地表示过渡状态和动力学.
- 缓慢,中等和快速反应坐标的 De novo 识别.
- 展示多层次动态的集体贡献,以发挥作用.
结论:
- mMSM提供了一个全面的框架,用于理解跨时间尺度的生物分子动力学.
- mMSM-explore算法使这些模型的有效生成和分析成为可能.
- 这种方法提高了我们对生物分子机器的功能机制的理解.
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