A Coarse-Grained Model for Small Organic Molecules with Optimized Lennard-Jones Parameters

IF 3.2 2区 化学 Q3 CHEMISTRY, PHYSICAL
The Journal of Physical Chemistry B Pub Date : 2026-09-24 Epub Date: 2026-09-15 DOI:10.1021/acs.jpcb.6c05069
Renjie Zhu, Tong Zhu, Ruibo Wu, Fei Xia
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引用次数: 0

Abstract

Developing accurate coarse-grained (CG) molecular models is crucial for constructing databases of complex chemical molecules and enabling data-driven research. Here we present the OLJCG model for small organic molecules, with Lennard-Jones (LJ) parameters optimized via the Lennard-Jones Static Potential Matching method based on the GAFF2 force field. The OLJCG model is systematically evaluated on two datasets (DS58 and DS29) for densities, vaporization enthalpies, nonaqueous solvation free energies, hydration free energies, and transfer free energies. The results demonstrate that the optimized LJ parameters effectively preserve the description of nonbonded interactions from the all-atom force field. The primary sources of error are identified as the neglect of electrostatic interactions and the use of a nonoptimized water model, providing clear directions for future refinement. The optimization strategy proposed here provides a systematic route for developing CG small-molecule databases.

具有优化Lennard-Jones参数的有机小分子粗粒度模型
开发精确的粗粒度(CG)分子模型对于构建复杂化学分子数据库和实现数据驱动研究至关重要。本文提出了有机小分子的OLJCG模型,并利用基于GAFF2力场的Lennard-Jones静态电位匹配方法优化了LJ参数。oljcg模型在两个数据集(DS58和ds29)上系统地评估了密度、蒸发焓、非水溶剂化自由能、水化自由能和传递自由能。结果表明,优化后的LJ参数有效地保留了全原子力场对非键相互作用的描述。误差的主要来源被确定为忽略静电相互作用和使用非优化的水模型,为未来的改进提供了明确的方向。本文提出的优化策略为开发cg小分子数据库提供了系统的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.80
自引率
9.10%
发文量
965
审稿时长
1.6 months
期刊介绍: An essential criterion for acceptance of research articles in the journal is that they provide new physical insight. Please refer to the New Physical Insights virtual issue on what constitutes new physical insight. Manuscripts that are essentially reporting data or applications of data are, in general, not suitable for publication in JPC B.
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