Song Junjie, Ma Ming, Dong Yi, Wan Mingwei, Fang Weihai, Gao Lianghui
Key Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.
Key Laboratory of Organic Optoelectronics & Molecular Engineering of the Ministry of Education, Department of Chemistry, Tsinghua University, Beijing 100084, China.
J Chem Theory Comput. 2023 Mar 28;19(6):1864-1874. doi: 10.1021/acs.jctc.2c01151. Epub 2023 Mar 7.
A new, accurate and transferable coarse-grained (CG) force field (FF) for polyethylene oxide (PEO) and polyethylene glycol (PEG) aqueous solutions based on a polarizable CG water (PCGW) model is developed in this work. A PCGW bead, which represents four water molecules, is modeled as two charged dummy particles connected by two constrained bonds to a central neutral particle; a PEO or PEG oligomer is modeled as a chain with repeated middle beads (PEOM) representing diether groups and two terminal beads (PEOT or PEGT) of a different type compared to PEOM. To describe nonbonded van der Waals interactions, a piecewise Morse potential with four tunable parameters is used. The force parameters are automatically and rigorously optimized by a meta-multilinear interpolation parameterization (meta-MIP) algorithm to simultaneously match multiple thermodynamic properties, including the density, heat of vaporization, vapor-liquid interfacial tension, and solvation free energy of the pure PEO or PEG oligomer bulk system as well as the mixing density and hydration free energy of the oligomer/water binary mixture. Additional thermodynamic and structural properties for longer PEO and PEG polymer aqueous solutions, such as the self-diffusion coefficient, radius of gyration, and end-to-end distance, are predicted to test the accuracy and transferability of this new CG FF. Based on the PCGW model, the presented FF optimization algorithm and strategy can be extended to more complex polyelectrolytes and surfactants.
本文开发了一种基于可极化粗粒度水（PCGW）模型的新型、准确且可转移的聚环氧乙烷（PEO）和聚乙二醇（PEG）水溶液粗粒度（CG）力场（FF）。一个代表四个水分子的PCGW珠子被建模为两个带电虚拟粒子，它们通过两个约束键连接到一个中心中性粒子；一个PEO或PEG低聚物被建模为一条链，其中重复的中间珠子（PEOM）代表二醚基团，以及两个与PEOM不同类型的末端珠子（PEOT或PEGT）。为了描述非键合范德华相互作用，使用了具有四个可调参数的分段莫尔斯势。通过元多线性插值参数化（meta-MIP）算法自动且严格地优化力参数，以同时匹配多种热力学性质，包括纯PEO或PEG低聚物本体系统的密度、汽化热、气液界面张力和溶剂化自由能，以及低聚物/水二元混合物的混合密度和水合自由能。预测了更长的PEO和PEG聚合物水溶液的其他热力学和结构性质，如自扩散系数、回转半径和端到端距离，以测试这种新型CG FF的准确性和可转移性。基于PCGW模型，所提出的FF优化算法和策略可以扩展到更复杂的聚电解质和表面活性剂。
