Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, United States.
J Phys Chem Lett. 2023 Feb 16;14(6):1354-1362. doi: 10.1021/acs.jpclett.2c03844. Epub 2023 Feb 2.
Systematic bottom-up coarse-graining (CG) of molecular systems provides a means to explore different coupled length and time scales while treating the molecular-scale physics at a reduced level. However, the configuration dependence of CG interactions often results in CG models with limited applicability for exploring the parametrized configurations. We propose a statistical mechanical theory to design CG interactions across different configurations and conditions. In order to span wide ranges of conformational space, distinct classical CG free energy surfaces for characteristic configurations are identified using molecular collective variables. The coupling interaction between different CG free energy surfaces can then be systematically determined by analogy to quantum mechanical approaches describing coupled states. The present theory can accurately capture the underlying many-body potentials of mean force in the CG variables for various order parameters applied to liquids, interfaces, and in principle proteins, uncovering the complex nature underlying the coupling interaction and imparting a new protocol for the design of predictive multiscale models.
系统的自下而上的粗粒化(CG)分子系统提供了一种方法来探索不同的耦合长度和时间尺度,同时以降低的水平处理分子尺度的物理。然而,CG 相互作用的构象依赖性通常导致 CG 模型在探索参数化构象方面的应用有限。我们提出了一种统计力学理论来设计跨越不同构象和条件的 CG 相互作用。为了跨越广泛的构象空间,使用分子集体变量识别特征构象的不同经典 CG 自由能表面。然后,可以通过类比描述耦合态的量子力学方法系统地确定不同 CG 自由能表面之间的耦合相互作用。本理论可以准确地捕捉 CG 变量中各种序参量下的平均力势的潜在多体势,揭示耦合相互作用的复杂本质,并为预测多尺度模型的设计提供新的方案。