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多尺度自由能模拟的最新进展。

Recent developments in multiscale free energy simulations.

机构信息

Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland.

Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093, Zurich, Switzerland.

出版信息

Curr Opin Struct Biol. 2022 Feb;72:55-62. doi: 10.1016/j.sbi.2021.08.003. Epub 2021 Sep 14.

Abstract

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.

摘要

基于物理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分辨率水平,但近年来的一系列进展使得现在有可能可靠地跨越时间、空间和理论尺度,对复杂系统进行建模或高效地预测昂贵量子力学计算的准确性水平的结果。在这篇综述中,我们讨论了最近的方法进展以及引入机器学习方法所带来的机会,这些方法解决了不同尺度上的各种挑战,提高了准确性和可行性,并推动了多尺度自由能模拟的发展。

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