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MDAnalysis: A toolkit for the analysis of molecular dynamics simulations

  1. Naveen Michaud-Agrawal1,
  2. Elizabeth J. Denning1,2,
  3. Thomas B. Woolf1,3,*,
  4. Oliver Beckstein3,4,*

Article first published online: 15 APR 2011

DOI: 10.1002/jcc.21787

Issue

Journal of Computational Chemistry

Journal of Computational Chemistry

Volume 32, Issue 10, pages 2319–2327, 30 July 2011

Additional Information

How to Cite

Michaud-Agrawal, N., Denning, E. J., Woolf, T. B. and Beckstein, O. (2011), MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem., 32: 2319–2327. doi: 10.1002/jcc.21787

Author Information

  1. 1

    Department of Biophysics, Johns Hopkins School of Medicine, Baltimore, Maryland 21205

  2. 2

    Department of Pharmaceutical Chemistry, University of Maryland, Baltimore, School of Pharmacy, Baltimore, Maryland 21201

  3. 3

    Department of Physiology, Johns Hopkins School of Medicine, Baltimore, Maryland 21205

  4. 4

    Department of Biochemistry, University of Oxford, Oxford OX1 3QU, United Kingdom

*Department of Biophysics, Johns Hopkins School of Medicine, Baltimore, Maryland 21205

Publication History

  1. Issue published online: 19 MAY 2011
  2. Article first published online: 15 APR 2011
  3. Manuscript Accepted: 12 FEB 2011
  4. Manuscript Revised: 6 FEB 2011
  5. Manuscript Received: 23 OCT 2010

Funded by

  • Burroughs Wellcome Fund
  • National Institutes of Health. Grant Number: GM064746
  • European Union (EDICT Project). Grant Number: 201924
  • Junior Research Fellowship at Merton College, Oxford

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Keywords:

  • molecular dynamics simulations;
  • analysis;
  • proteins;
  • object-oriented design;
  • software;
  • membrane systems;
  • Python programming language

Abstract

MDAnalysis is an object-oriented library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. It is written in the Python language with some performance-critical code in C. It uses the powerful NumPy package to expose trajectory data as fast and efficient NumPy arrays. It has been tested on systems of millions of particles. Many common file formats of simulation packages including CHARMM, Gromacs, Amber, and NAMD and the Protein Data Bank format can be read and written. Atoms can be selected with a syntax similar to CHARMM's powerful selection commands. MDAnalysis enables both novice and experienced programmers to rapidly write their own analytical tools and access data stored in trajectories in an easily accessible manner that facilitates interactive explorative analysis. MDAnalysis has been tested on and works for most Unix-based platforms such as Linux and Mac OS X. It is freely available under the GNU General Public License from http://mdanalysis.googlecode.com. © 2011 Wiley Periodicals, Inc. J Comput Chem 2011

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