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基于分子中原子的电子密度分割的生物分子力场参数化。

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

机构信息

Department of Chemistry, Yale University , New Haven, Connecticut 06520-8107, United States.

TCM Group, Cavendish Laboratory, 19 JJ Thomson Avenue, Cambridge CB3 0HE, United Kingdom.

出版信息

J Chem Theory Comput. 2016 May 10;12(5):2312-23. doi: 10.1021/acs.jctc.6b00027. Epub 2016 Apr 21.

Abstract

Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme.

摘要

分子力学力场常用于生物分子建模和计算机辅助药物设计,通常使用针对小分子开发的有限经验参数库来处理非键相互作用。这种方法无法解释较大分子或蛋白质中的极化现象,而且参数化过程非常繁琐。本文使用线性标度密度泛函理论和分子内电子密度划分方法,直接从量子力学计算中推导出有机和生物分子体系中生物分子建模所需的环境特定电荷和 Lennard-Jones 参数。所提出的方法大大减少了构建分子力学力场所需的经验参数数量,自然包含了电荷和 Lennard-Jones 参数中的极化效应,并且能够很好地扩展到包含数千个原子的体系,包括蛋白质。通过计算水合自由能、纯液体性质以及吲哚和苯并呋喃与 T4 溶菌酶 L99A 突变体的相对结合自由能,验证了该方法的可行性和优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4afb/4864407/f09dfd4bbadf/ct-2016-00027q_0001.jpg

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