Recent developments in multiscale free energy simulations
Recent developments in multiscale free energy simulations
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DOI：
10.1016/j.sbi.2021.08.003
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发表时间：
2022-02-01
影响因子：
6.8
通讯作者：
Riniker, Sereina
中科院分区：
文献类型：
--
作者：
Barros, Emilia P.;Ries, Benjamin;Riniker, Sereina
基于物理学的自由能模拟能够严格计算性质，如构象平衡、溶剂化或结合自由能。虽然历史上大多数应用都发生在原子级的分辨率上，但过去几年的一系列进步使得现在有可能可靠地跨越时间，空间和理论尺度，用于复杂系统的建模或在昂贵的量子力学计算的精度水平上有效预测结果。在这篇小型综述中，我们讨论了最近的方法学进展以及引入机器学习方法所带来的机遇，这些方法可以解决不同尺度的各种挑战，提高准确性和可行性，并推动多尺度自由能模拟的边界。
Physics-based free energy simulations enable the rigorous calculation of properties, such as conformational equilibria, solvation or binding free energies. While historically most applications have occurred at the atomistic level of resolution, a range of advances in the past years make it possible now to reliably cross the temporal, spatial and theory scales for the modeling of complex systems or the efficient prediction of results at the accuracy level of expensive quantum-mechanical calculations. In this mini-review, we discuss recent methodological advances as well as opportunities opened up by the introduction of machine learning approaches, which tackle the diverse challenges across the different scales, improve the accuracy and feasibility, and push the boundaries of multiscale free energy simulations.