Article

CHARMM: A program for macromolecular energy, minimization, and dynamics calculations†

  1. Bernard R. Brooks§,
  2. Robert E. Bruccoleri,
  3. Barry D. Olafson‡,‖,
  4. David J. States††,
  5. S. Swaminathan,
  6. Martin Karplus

Article first published online: 7 SEP 2004

DOI: 10.1002/jcc.540040211

Issue

Journal of Computational Chemistry

Journal of Computational Chemistry

Volume 4, Issue 2, pages 187–217, Summer 1983

Additional Information

How to Cite

Brooks, B. R., Bruccoleri, R. E., Olafson, B. D., States, D. J., Swaminathan, S. and Karplus, M. (1983), CHARMM: A program for macromolecular energy, minimization, and dynamics calculations. J. Comput. Chem., 4: 187–217. doi: 10.1002/jcc.540040211

Author Information

  1. Department of Chemistry, Harvard University, Cambridge, Massachusetts 02138

  1. ‡

    Noyes Laboratory of Chemical Physics, California Institute of Technology, Pasadena, California 91125

  1. §

    National Science Foundation Postdoctoral Fellow.

  2. National Science Foundation Predoctoral Fellow (1977–1980).

  3. ‖

    National Institutes of Health Postdoctoral Fellow.

  4. ††

    Supported by the National Institutes of Health Medical Science Training Program, grant No. GMO-7753.

  1. †

    Supported in part by grants from the National Science Foundation and the National Institutes of Health.

Publication History

  1. Issue published online: 7 SEP 2004
  2. Article first published online: 7 SEP 2004
  3. Manuscript Accepted: 14 OCT 1982
  4. Manuscript Received: 6 JUL 1982

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Abstract

CHARMM (Chemistry at HARvard Macromolecular Mechanics) is a highly flexible computer program which uses empirical energy functions to model macromolecular systems. The program can read or model build structures, energy minimize them by first- or second-derivative techniques, perform a normal mode or molecular dynamics simulation, and analyze the structural, equilibrium, and dynamic properties determined in these calculations. The operations that CHARMM can perform are described, and some implementation details are given. A set of parameters for the empirical energy function and a sample run are included.

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