Scalable molecular dynamics with NAMD

Abstract

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.

DOI: 10.1002/jcc.20289
View Slides

Extracted Key Phrases

13 Figures and Tables

050010001500'04'06'08'10'12'14'16
Citations per Year

13,700 Citations

Semantic Scholar estimates that this publication has 13,700 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Phillips2005ScalableMD, title={Scalable molecular dynamics with NAMD}, author={James C. Phillips and Rosemary Braun and Wei Wang and James C. Gumbart and Emad Tajkhorshid and Elizabeth Villa and Christophe Chipot and Robert D. Skeel and Laxmikant V. Kal{\'e} and Klaus Schulten}, journal={Journal of computational chemistry}, year={2005}, volume={26 16}, pages={1781-802} }