OpenMM

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OpenMM
[[Programmer|Original authorTemplate:Pluralize from text]]Peter Eastman
[[Programmer|DeveloperTemplate:Pluralize from text]]Stanford University
Memorial Sloan Kettering Cancer Center
Pompeu Fabra University
National Heart, Lung, and Blood Institute
Initial releaseJanuary 20, 2010; 16 years ago (January 20, 2010)[1]
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Written inC++, C, CUDA, Python
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Operating systemLinux, macOS, Windows
PlatformMany
Available inEnglish
TypeMolecular dynamics
LicenseMIT License
LGPL
Websiteopenmm.org
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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

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References

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  1. ^ a b Page Module:Citation/CS1/styles.css has no content."SimTK: OpenMM: Downloads". SimTK. 2020-12-10. Retrieved 2022-09-09.
  2. ^ Page Module:Citation/CS1/styles.css has no content."Release OpenMM 8.2.0 · openmm/openmm". GitHub. 2024-11-08. Retrieved 2025-02-27.
  3. ^ Page Module:Citation/CS1/styles.css has no content.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.

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