OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.
复制标题
OpenMM 8:具有机器学习潜力的分子动力学模拟。
DOI:
10.1021/acs.jpcb.3c06662
复制
发表时间:
2024
期刊:
影响因子:
--
通讯作者:
Eastman P
中科院分区:
文献类型:
--
作者:
Eastman P
Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features in simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations with only a modest increase in cost.
登录
查看更多内容
影响因子:
5.5
作者:
Lopes, Pedro E. M.;Huang, Jing;Shim, Jihyun;Luo, Yun;Li, Hui;Roux, Benoit;MacKerell, Alexander D., Jr.
通讯作者:
MacKerell, Alexander D., Jr.
DOI:
--
发表时间:
2019
期刊:
影响因子:
--
作者:
中村賀美;竹内孝江
通讯作者:
竹内孝江
影响因子:
9.8
作者:
Eastman, Peter;Behara, Pavan Kumar;Dotson, David L.;Galvelis, Raimondas;Herr, John E.;Horton, Josh T.;Mao, Yuezhi;Chodera, John D.;Pritchard, Benjamin P.;Wang, Yuanqing;De Fabritiis, Gianni;Markland, Thomas E.
通讯作者:
Markland, Thomas E.
影响因子:
5.5
作者:
Maier JA;Martinez C;Kasavajhala K;Wickstrom L;Hauser KE;Simmerling C
通讯作者:
Simmerling C
影响因子:
4.4
作者:
Christensen, Anders S.;Sirumalla, Sai Krishna;Miller, Thomas F., III
通讯作者:
Miller, Thomas F., III