Kurnikov Igor V, Pereyaslavets Leonid, Kamath Ganesh, Sakipov Serzhan N, Voronina Ekaterina, Butin Oleg, Illarionov Alexey, Leontyev Igor, Nawrocki Grzegorz, Darkhovskiy Mikhail, Olevanov Michael, Ivahnenko Ilya, Chen YuChun, Lock Christopher B, Levitt Michael, Kornberg Roger D, Fain Boris
InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States.
Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, California 94304, United States.
J Chem Theory Comput. 2024 Feb 13;20(3):1347-1357. doi: 10.1021/acs.jctc.3c00921. Epub 2024 Jan 19.
We incorporate nuclear quantum effects (NQE) in condensed matter simulations by introducing short-range neural network (NN) corrections to the ab initio fitted molecular force field ARROW. Force field NN corrections are fitted to average interaction energies and forces of molecular dimers, which are simulated using the Path Integral Molecular Dynamics (PIMD) technique with restrained centroid positions. The NN-corrected force field allows reproduction of the NQE for computed liquid water and methane properties such as density, radial distribution function (RDF), heat of evaporation (HVAP), and solvation free energy. Accounting for NQE through molecular force field corrections circumvents the need for explicit computationally expensive PIMD simulations in accurate calculations of the properties of chemical and biological systems. The accuracy and locality of pairwise NN NQE corrections indicate that this approach could be applicable to complex heterogeneous systems, such as proteins.
我们通过对从头算拟合分子力场ARROW引入短程神经网络(NN)校正,将核量子效应(NQE)纳入凝聚态模拟中。力场NN校正拟合至分子二聚体的平均相互作用能和力,这些二聚体使用具有受限质心位置的路径积分分子动力学(PIMD)技术进行模拟。经NN校正的力场能够再现计算得到的液态水和甲烷性质的NQE,如密度、径向分布函数(RDF)、蒸发焓(HVAP)和溶剂化自由能。通过分子力场校正来考虑NQE,避免了在化学和生物系统性质的精确计算中进行明确的计算成本高昂的PIMD模拟。成对NN NQE校正的准确性和局部性表明,这种方法可能适用于复杂的异质系统,如蛋白质。