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PLoS Comput Biol. 2017 Jul 26;13(7):e1005659. doi: 10.1371/journal.pcbi.1005659. eCollection 2017 Jul.

OpenMM 7: Rapid development of high performance algorithms for molecular dynamics.

Author information

1
Department of Chemistry, Stanford University, Stanford, California, United States of America.
2
Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University, Piscataway, New Jersey, United States of America.
3
Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.
4
Department of Chemistry, University of California, Davis, Davis, California, United States of America.
5
Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
6
Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.
7
Department of Computer Science, Stanford University, Stanford, California, United States of America.

Abstract

OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM. This makes it an ideal tool for researchers developing new simulation methods, and also allows those new methods to be immediately available to the larger community.

PMID:
28746339
PMCID:
PMC5549999
DOI:
10.1371/journal.pcbi.1005659
[Indexed for MEDLINE]
Free PMC Article

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