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Protein C-GeM: A Coarse-Grained Electron Model for Fast and Accurate Protein Electrostatics Prediction
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2021-09-07 , DOI: 10.1021/acs.jcim.1c00388
Xingyi Guan 1, 2 , Itai Leven 1, 2 , Farnaz Heidar-Zadeh 1, 3 , Teresa Head-Gordon 1, 2, 4
Affiliation  

The electrostatic potential (ESP) is a powerful property for understanding and predicting electrostatic charge distributions that drive interactions between molecules. In this study, we compare various charge partitioning schemes including fitted charges, density-based quantum mechanical (QM) partitioning schemes, charge equilibration methods, and our recently introduced coarse-grained electron model, C-GeM, to describe the ESP for protein systems. When benchmarked against high quality density functional theory calculations of the ESP for tripeptides and the crambin protein, we find that the C-GeM model is of comparable accuracy to ab initio charge partitioning methods, but with orders of magnitude improvement in computational efficiency since it does not require either the electron density or the electrostatic potential as input.

中文翻译:

蛋白质 C-GeM:一种用于快速准确蛋白质静电预测的粗粒度电子模型

静电势 (ESP) 是一种强大的特性,可用于理解和预测驱动分子间相互作用的静电荷分布。在这项研究中,我们比较了各种电荷分配方案,包括拟合电荷、基于密度的量子力学 (QM) 分配方案、电荷平衡方法,以及我们最近推出的粗粒电子模型 C-GeM,以描述蛋白质系统的 ESP . 当以三肽和海藻蛋白的 ESP 的高质量密度泛函理论计算为基准时,我们发现 C-GeM 模型与ab initio具有可比的准确性 电荷分配方法,但由于不需要电子密度或静电势作为输入,因此计算效率提高了几个数量级。
更新日期:2021-09-27
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