Recent advances in maximum entropy biasing techniques for molecular dynamics
Recent advances in maximum entropy biasing techniques for molecular dynamics
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DOI：
10.1080/08927022.2019.1608988
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发表时间：
2019-10-13
影响因子：
2.1
通讯作者：
White, A. D.
中科院分区：
文献类型：
--
作者：
Amirkulova, D. B.;White, A. D.
本文综述了作者和其他人通过最大熵方法将实验数据纳入分子模拟的最新进展。结合实验数据的方法通过最小限度地修改热力学系综来提高分子模拟的准确性。这在力场近似的情况下尤其重要，例如当采用粗粒度模型时，或者在需要高精度的情况下，例如当试图模拟多尺度自组装过程时。本文综述了实验导向模拟（EDS）和实验导向元动力学（EDM）两种方法，它们分别允许在模拟中匹配平均值和分布。讨论了重要的系统特定考虑事项，例如同时使用增强采样，压力的作用，处理不确定性以及这些方法的实现。本文回顾了EDS和EDM的最新应用，包括从头计算水的分子动力学，结合大分子蛋白质复合物内部的环境波动，改善RNA力场，以及增强采样与最小偏向模型肽的组合
This review describes recent advances by the authors and others on the topic of incorporating experimental data into molecular simulations through maximum entropy methods. Methods which incorporate experimental data improve accuracy in molecular simulation by minimally modifying the thermodynamic ensemble. This is especially important where force fields are approximate, such as when employing coarse-grain models, or where high accuracy is required, such as when attempting to mimic a multiscale self-assembly process. The authors review here the experiment directed simulation (EDS) and experiment directed metadynamics (EDM) methods that allow matching averages and distributions in simulations, respectively. Important system-specific considerations are discussed such as using enhanced sampling simultaneously, the role of pressure, treating uncertainty, and implementations of these methods. Recent examples of EDS and EDM are reviewed including applications to ab initio molecular dynamics of water, incorporating environmental fluctuations inside of a macromolecular protein complex, improving RNA force fields, and the combination of enhanced sampling with minimal biasing to model peptides