GPU4PySCF周期系统的精确QM/MM分子动力学及其在酶催化中的应用。

IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL
Journal of Chemical Theory and Computation Pub Date : 2025-01-28 Epub Date: 2025-01-15 DOI:10.1021/acs.jctc.4c01698
Chenghan Li, Garnet Kin-Lic Chan
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引用次数: 0

摘要

我们提出了一个使用GPU加速QM方法的周期系统量子力学/分子力学(QM/MM)方法的实现,一个分布式多极静电公式,以及QM/MM边界的伪键处理。结果表明,该方法具有良好的误差控制、稳定的自洽QM收敛性和节能特性。我们进一步描述了在氯酸盐突变酶催化动力学中的应用。使用精确的混合泛函重新参数化耦合簇能量学,我们的QM/MM模拟突出了计算速率对量子方法选择,量子区域选择和局部蛋白质构象的敏感性。我们的工作是通过开源的PySCF包提供的,使用GPU4PySCF模块的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accurate QM/MM Molecular Dynamics for Periodic Systems in GPU4PySCF with Applications to Enzyme Catalysis.

We present an implementation of the quantum mechanics/molecular mechanics (QM/MM) method for periodic systems using GPU accelerated QM methods, a distributed multipole formulation of the electrostatics, and a pseudobond treatment of the QM/MM boundary. We demonstrate that our method has well-controlled errors, stable self-consistent QM convergence, and energy-conserving dynamics. We further describe an application to the catalytic kinetics of chorismate mutase. Using an accurate hybrid functional reparametrized to coupled cluster energetics, our QM/MM simulations highlight the sensitivity in the calculated rate to the choice of quantum method, quantum region selection, and local protein conformation. Our work is provided through the open-source PySCF package using acceleration from the GPU4PySCF module.

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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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