Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics

Peter Eastman, Jason Swails, John D. Chodera, Robert T. McGibbon, Yutong Zhao, Kyle A. Beauchamp, Lee-Ping Wang, Andrew C. Simmonett, Matthew P. Harrigan, Chaya D. Stern, Rafal P. Wiewiora, Bernard R. Brooks, Vijay S. Pande
doi: https://doi.org/10.1101/091801
Peter Eastman
1Department of Chemistry, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jason Swails
2Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University, Piscataway, NJ 08854
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John D. Chodera
3Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Robert T. McGibbon
1Department of Chemistry, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yutong Zhao
1Department of Chemistry, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kyle A. Beauchamp
3Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
4Current address: Counsyl Research, South San Francisco, CA 94080
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lee-Ping Wang
5Department of Chemistry, University of California, Davis, CA 95616
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrew C. Simmonett
6Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthew P. Harrigan
6Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chaya D. Stern
3Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
6Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rafal P. Wiewiora
3Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065
6Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bernard R. Brooks
7Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda MD 20892
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vijay S. Pande
1Department of Chemistry, Stanford University, Stanford, CA 94305
8Department of Computer Science, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

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.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted June 28, 2017.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics
Peter Eastman, Jason Swails, John D. Chodera, Robert T. McGibbon, Yutong Zhao, Kyle A. Beauchamp, Lee-Ping Wang, Andrew C. Simmonett, Matthew P. Harrigan, Chaya D. Stern, Rafal P. Wiewiora, Bernard R. Brooks, Vijay S. Pande
bioRxiv 091801; doi: https://doi.org/10.1101/091801
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics
Peter Eastman, Jason Swails, John D. Chodera, Robert T. McGibbon, Yutong Zhao, Kyle A. Beauchamp, Lee-Ping Wang, Andrew C. Simmonett, Matthew P. Harrigan, Chaya D. Stern, Rafal P. Wiewiora, Bernard R. Brooks, Vijay S. Pande
bioRxiv 091801; doi: https://doi.org/10.1101/091801

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Biophysics
Subject Areas
All Articles
  • Animal Behavior and Cognition (2434)
  • Biochemistry (4796)
  • Bioengineering (3335)
  • Bioinformatics (14704)
  • Biophysics (6649)
  • Cancer Biology (5180)
  • Cell Biology (7440)
  • Clinical Trials (138)
  • Developmental Biology (4374)
  • Ecology (6890)
  • Epidemiology (2057)
  • Evolutionary Biology (9930)
  • Genetics (7351)
  • Genomics (9542)
  • Immunology (4570)
  • Microbiology (12702)
  • Molecular Biology (4954)
  • Neuroscience (28382)
  • Paleontology (199)
  • Pathology (809)
  • Pharmacology and Toxicology (1394)
  • Physiology (2025)
  • Plant Biology (4516)
  • Scientific Communication and Education (978)
  • Synthetic Biology (1302)
  • Systems Biology (3919)
  • Zoology (729)