Energetic and entropic considerations for coarse-graining
Energetic and entropic considerations for coarse-graining
复制标题
DOI：
10.1140/epjb/s10051-021-00153-4
复制
发表时间：
2021-07
期刊：
影响因子：
--
通讯作者：
Katherine M. Kidder;R. Szukalo;W. Noid
中科院分区：
文献类型：
--
作者：
Katherine M. Kidder;R. Szukalo;W. Noid
分子动力学模拟通常采用粗粒度(CG)模型来研究用原子细节模型无法有效处理的长度和时间尺度。然而，支配CG模型的有效势是组态相关的自由能，具有显著的熵贡献，这对CG模型的可转移性和热力学性质有重要的影响。这篇综述总结了最近研究这些熵贡献的基本来源和实际分支，以及它们对CG映射的敏感性的工作。我们首先分析了平均力多体势的能量分量和熵分量。通过采用一个简单的蛋白质波动模型，我们研究了这些成分如何随CG表示而变化。然后，我们介绍了一个“双势”的方法，以解决更复杂的体系，如邻三苯基(OTP)的这些考虑。我们证明，这种对偶方法不仅准确地描述了原子模型的结构和能量性质，而且准确地预测了CG势的温度依赖性。此外，通过考虑OTP的两种不同的CG表示，我们解释了这些贡献如何随分辨率的变化而变化。总之，我们希望这项工作将有助于提高软材料CG模型的可转移性和热力学性质。
Molecular dynamics simulations often adopt coarse-grained (CG) models to investigate length- and time-scales that cannot be effectively addressed with atomically detailed models. However, the effective potentials that govern CG models are configuration-dependent free energies with significant entropic contributions that have important consequences for the transferability and thermodynamic properties of CG models. This review summarizes recent work investigating the fundamental origin and practical ramifications of these entropic contributions, as well as their sensitivity to the CG mapping. We first analyze the energetic and entropic components of the many-body potential of mean force. By adopting a simple model for protein fluctuations, we examine how these components vary with the CG representation. We then introduce a “dual potential” approach for addressing these entropic considerations in more complex systems, such as ortho-terphenyl (OTP). We demonstrate that this dual approach not only accurately describes the structure and energetic properties of the underlying atomic model, but also accurately predicts the temperature-dependence of the CG potentials. Furthermore, by considering two different CG representations of OTP, we elucidate how these contributions vary with resolution. In sum, we hope this work will prove useful for improving the transferability and thermodynamic properties of CG models for soft materials.