OpenMM

Last updated
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;22 months ago (2023-01-30) [2]
Written in C++, C, CUDA, Python
Operating system Linux, macOS, Windows
Platform Many
Available inEnglish
Type Molecular dynamics
License MIT License
LGPL
Website 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]

Contents

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

Related Research Articles

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References

  1. 1 2 "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. Bibcode:2021NatCh..13..651Z. doi: 10.1038/s41557-021-00707-0 . ISSN   1755-4330. PMC   8249329 . PMID   34031561.