Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania.
Computational Science and Engineering Division, Health Data Sciences Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee.
Biophys J. 2018 May 8;114(9):2040-2043. doi: 10.1016/j.bpj.2018.03.021.
Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates.
在依赖时间的构象波动中，非谐性是生物分子功能动力学的一个关键特征。虽然非谐事件很少见，但长时间尺度（微秒到毫秒以上）的模拟有助于探测此类事件。我们之前开发了准非谐分析来解析更高阶的空间相关，并在生物分子模拟中描述非谐性。在本文中，我们将该工具包扩展到解析更高阶的时间相关，并构建了一个名为非谐构象分析（ANCA）的可扩展 Python 包。ANCA 有模块来：1）以更高阶统计量的形式测量非谐性及其随时间的变化，2）输出模拟的故事板表示，以识别关键的非谐构象事件，3）识别可能的非谐构象亚稳态，并可视化这些亚稳态之间的转变。
