ABEEM Polarizable Force Field for PC Lipids: Parameterization and Molecular Dynamics Simulations

力场(虚构) 分子动力学 领域(数学) 动力学(音乐) 极化率 统计物理学 化学物理 物理 计算机科学 计算化学 化学 分子 人工智能 数学 量子力学 声学 纯数学
作者
Xiaoyu Wang,Linlin Liu,Peiran Meng,Jian Zhao,Lei Wang,Cui Liu,Lidong Gong,Zhong‐Zhi Yang
出处
期刊:Journal of Chemical Theory and Computation [American Chemical Society]
卷期号:21 (14): 6933-6949 被引量:2
标识
DOI:10.1021/acs.jctc.4c01704
摘要

In additive force fields, the charge is a tunable parameter designed to represent average polarization effects through a mean-field average, which could not accurately respond to different environments. The polarizable force field (PFF) offers enhanced accuracy in representing intermolecular interactions by dynamically capturing electronic polarization effects. The ABEEM PFF for lipids, built on the fluctuating charge model, offers reasonable charge distributions and specific characterization of the hydrogen bonding interaction to improve the electrostatic interactions. The hierarchical parameterization strategy requires optimizing parameters for small molecules of lipid functional groups and subsequently applying these parameters to seven PC lipids, including 1,2-dipalmitoyl- sn -glycero-3-phosphocholine (DPPC), dimyristoylphosphatidylcholine (DMPC), dilauroylphosphatidylcholine (DLPC), 1,2-dioleoyl- sn -glycero-3-phosphocholine (DOPC), 1-palmitoyl-2-oleoyl- sn -glycero-3-phosphocholine (POPC), 1,2-distearoyl- sn -glycero-3-phosphocholine (DSPC), and 1-stearoyl-2-oleoyl-phosphatidylcholine (SOPC). The ABEEM-DBSS method was refined for the specific characteristics of lipid bilayers by charge partitioning calculations for solutes, thereby enhancing the computational efficiency in molecular dynamics (MD) simulations. Results show that the ABEEM PFF can reproduce the quantum mechanical (QM) data of model compounds representing phospholipids as well as the experimental condensed-phase properties of lipid bilayers. In particular, the optimization of dihedral parameters for hydrocarbons has improved the accuracy of the NMR deuterium order parameters of carbon atoms. Based on the advantages of ABEEM PFF, unsupervised machine learning methods were employed to reveal the correlation, which showed the regular impact between the fluctuating charge of phosphorus (P) atoms in lipids and the tilt of the vector between the P and nitrogen (N) atoms in the PC group with respect to the interface plane, as well as the dynamic behavior of water molecules. This work may lay the foundation for further investigations on the structures and properties of membrane proteins in terms of the ABEEM PFF.
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