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Bind3P:基于主客体结合数据的水模型优化。

Bind3P: Optimization of a Water Model Based on Host-Guest Binding Data.

机构信息

Skaggs School of Pharmacy and Pharmaceutical Sciences , University of California San Diego , La Jolla , California 92093 , United States.

OpenEye Scientific Software , 9 Bisbee Court , Santa Fe , New Mexico 87508 , United States.

出版信息

J Chem Theory Comput. 2018 Jul 10;14(7):3621-3632. doi: 10.1021/acs.jctc.8b00318. Epub 2018 Jun 22.

Abstract

We report a water model, Bind3P (Version 0.1), which was obtained by using sensitivity analysis to readjust the Lennard-Jones parameters of the TIP3P model against experimental binding free energies for six host-guest systems, along with pure liquid properties. Tests of Bind3P against >100 experimental binding free energies and enthalpies for host-guest systems distinct from the training set show a consistent drop in the mean signed error, relative to matched calculations with TIP3P. Importantly, Bind3P also yields some improvement in the hydration free energies of small organic molecules and preserves the accuracy of bulk water properties, such as density and the heat of vaporization. The same approach can be applied to more sophisticated water models that can better represent pure water properties. These results lend further support to the concept of integrating host-guest binding data into force field parametrization.

摘要

我们报告了一个水模型,Bind3P(版本 0.1),该模型是通过使用敏感性分析来重新调整 TIP3P 模型的 Lennard-Jones 参数,以适应六个主体-客体系统的实验结合自由能,以及纯液体性质。Bind3P 对超过 100 个主体-客体系统的实验结合自由能和焓的测试表明,与使用 TIP3P 进行的匹配计算相比,平均符号误差明显下降。重要的是,Bind3P 还改善了小分子的水合自由能,同时保持了诸如密度和汽化热等大量水性质的准确性。这种方法可以应用于更复杂的水模型,以更好地表示纯水性质。这些结果进一步支持了将主体-客体结合数据纳入力场参数化的概念。

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