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

PLoS Computational Biology · 2017 · Vol. 13(7) · pp. e1005659–e1005659
Peter EastmanJason SwailsJohn D. ChoderaRobert T. McGibbonYutong ZhaoKyle A. BeauchampLee‐Ping WangAndrew C. SimmonettMatthew P. HarriganChaya SternRafal WiewioraBernard R. BrooksVijay S. Pande

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.

Protein Structure and DynamicsQuantum, superfluid, helium dynamicsAdvanced NMR Techniques and ApplicationsComputer scienceExtensibilityCoding (social sciences)Focus (optics)AlgorithmDevelopment (topology)Theoretical computer scienceFunction (biology)Ideal (ethics)Computational science

MeSH terms

AlgorithmsSoftwareComputational BiologyMolecular Dynamics Simulation

Funding

  • National Science Foundation
  • Memorial Sloan-Kettering Cancer Center
  • National Institutes of Health
Citations
2,677
FWCI
45.56
field-weighted impact
References
39
Percentile
100%
vs. same field & year
Citations per year
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