OpenMM

From WikiProjectMed
Jump to navigation Jump to search
OpenMM
Original author(s)Peter Eastman
Developer(s)Stanford University
Memorial Sloan Kettering Cancer Center
Pompeu Fabra University
National Heart, Lung, and Blood Institute
Initial releaseJanuary 20, 2010; 14 years ago (January 20, 2010)[1]
Stable release
8.0.0 / 30 January 2023; 14 months ago (2023-01-30)[2]
Written inC++, C, CUDA, Python
Operating systemLinux, macOS, Windows
PlatformMany
Available inEnglish
TypeMolecular dynamics
LicenseMIT License
LGPL
Websitewww.openmm.org

OpenMM is a library for performing molecular dynamics simulations on a wide variety of hardware architectures. First released in January 2010,[1] it was written by Peter Eastman at the Vijay S. Pande lab at Stanford University. It is notable for its implementation in the Folding@home project's core22 kernel. Core22, also developed at the Pande lab, uses OpenMM to perform protein dynamics simulations on GPUs via CUDA and OpenCL. During the COVID-19 pandemic, a peak of 280,000 GPUs were estimated to be running OpenMM via core22.[3]

Features

OpenMM has a C++ API as well as a Python wrapper. Developers are able to customize force fields as well as integrators for low-level simulation control. Users who only require high-level control of their simulations can use built-in force fields (consisting of many commonly used force fields) and built in integrators like Langevin, Verlet, Nosé–Hoover, and Brownian.

See also

References

  1. ^ a b "SimTK: OpenMM: Downloads". SimTK. 2020-12-10. Retrieved 2022-09-09.
  2. ^ "Release OpenMM 8.0.0 · openmm/openmm". GitHub. 2023-01-31. Retrieved 2023-02-08.
  3. ^ Zimmerman, Maxwell I.; Porter, Justin R.; Ward, Michael D.; Singh, Sukrit; Vithani, Neha; Meller, Artur; Mallimadugula, Upasana L.; Kuhn, Catherine E.; Borowsky, Jonathan H.; Wiewiora, Rafal P.; Hurley, Matthew F. D.; Harbison, Aoife M.; Fogarty, Carl A.; Coffland, Joseph E.; Fadda, Elisa; Voelz, Vincent A.; Chodera, John D.; Bowman, Gregory R. (2021-05-24). "SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome". Nature Chemistry. 13 (7). Springer Science and Business Media LLC: 651–659. doi:10.1038/s41557-021-00707-0. ISSN 1755-4330. PMC 8249329.