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切片与切块:保留分子动力学的最优粗粒度表示

Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics.

作者信息

Yang Wangfei, Templeton Clark, Rosenberger David, Bittracher Andreas, Nüske Feliks, Noé Frank, Clementi Cecilia

机构信息

Center for Theoretical Biological Physics, Rice University, Houston, Texas77005, United States.

Graduate Program in Systems, Synthetic and Physical Biology, Rice University, Houston, Texas77005, United States.

出版信息

ACS Cent Sci. 2023 Jan 17;9(2):186-196. doi: 10.1021/acscentsci.2c01200. eCollection 2023 Feb 22.

Abstract

The aim of molecular coarse-graining approaches is to recover relevant physical properties of the molecular system via a lower-resolution model that can be more efficiently simulated. Ideally, the lower resolution still accounts for the degrees of freedom necessary to recover the correct physical behavior. The selection of these degrees of freedom has often relied on the scientist's chemical and physical intuition. In this article, we make the argument that in soft matter contexts desirable coarse-grained models accurately reproduce the long-time dynamics of a system by correctly capturing the rare-event transitions. We propose a bottom-up coarse-graining scheme that correctly preserves the relevant slow degrees of freedom, and we test this idea for three systems of increasing complexity. We show that in contrast to this method existing coarse-graining schemes such as those from information theory or structure-based approaches are not able to recapitulate the slow time scales of the system.

摘要

分子粗粒化方法的目的是通过一个能够更高效模拟的低分辨率模型来恢复分子系统的相关物理性质。理想情况下,较低分辨率仍能考虑到恢复正确物理行为所需的自由度。这些自由度的选择通常依赖于科学家的化学和物理直觉。在本文中,我们认为在软物质环境中,理想的粗粒化模型通过正确捕捉罕见事件转变来准确再现系统的长时间动力学。我们提出了一种自下而上的粗粒化方案,该方案能正确保留相关的慢自由度,并针对三个复杂度不断增加的系统测试了这一想法。我们表明,与这种方法相比,现有的粗粒化方案,如来自信息论或基于结构的方法,无法概括系统的慢时间尺度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85e4/9951291/63e67b2efd1f/oc2c01200_0001.jpg

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