Cao Zhen, Voth Gregory A
Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, 5735 S Ellis Ave., Chicago, Illinois 60637, USA.
J Chem Phys. 2015 Dec 28;143(24):243116. doi: 10.1063/1.4933249.
It is essential to be able to systematically construct coarse-grained (CG) models that can efficiently and accurately reproduce key properties of higher-resolution models such as all-atom. To fulfill this goal, a mapping operator is needed to transform the higher-resolution configuration to a CG configuration. Certain mapping operators, however, may lose information related to the underlying electrostatic properties. In this paper, a new mapping operator based on the centers of charge of CG sites is proposed to address this issue. Four example systems are chosen to demonstrate this concept. Within the multiscale coarse-graining framework, CG models that use this mapping operator are found to better reproduce the structural correlations of atomistic models. The present work also demonstrates the flexibility of the mapping operator and the robustness of the force matching method. For instance, important functional groups can be isolated and emphasized in the CG model.
能够系统地构建粗粒度（CG）模型至关重要，这些模型要能高效且准确地重现高分辨率模型（如全原子模型）的关键属性。为实现这一目标，需要一个映射算子将高分辨率构型转换为CG构型。然而，某些映射算子可能会丢失与潜在静电特性相关的信息。本文提出了一种基于CG位点电荷中心的新映射算子来解决这一问题。选择了四个示例系统来证明这一概念。在多尺度粗粒化框架内，发现使用此映射算子的CG模型能更好地重现原子模型的结构相关性。本研究还展示了映射算子的灵活性和力匹配方法的稳健性。例如，重要的官能团可以在CG模型中被分离并突出显示。
