The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
CHARMM: A program for macromolecular energy, minimization, and dynamics calculations
Abstract
CHARMM (C hemistry at HAR vard M acromolecular M echanics) 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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Citations
Cites
An algorithm for the machine calculation of complex Fourier series
Cooley, J. W., & Tukey, J. W. (1965) · Mathematics of Computation · doi:10.1090/s0025-5718-1965-0178586-1 · Cited by 13,154
Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
A relational model of data for large shared data banks
Codd, E. F. (1970) · Communications of the ACM · doi:10.1145/362384.362685 · Cited by 5,547
Cited by
VMD: visual molecular dynamics
Humphrey, W., Dalke, A., & Schulten, K. (1996) · Journal of Molecular Graphics · doi:10.1016/0263-7855(96)00018-5 · Cited by 66,952
Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., & Lindahl, E. (2015) · SoftwareX · doi:10.1016/j.softx.2015.06.001 · Cited by 27,190
CHARMM‐GUI: A web‐based graphical user interface for CHARMM
Jo, S., Kim, T., Iyer, V. G., & Im, W. (2008) · Journal of Computational Chemistry · doi:10.1002/jcc.20945 · Cited by 9,284
Kühne, T. D., Iannuzzi, M., Del Ben, M., Rybkin, V. V., Seewald, P., Stein, F., Laino, T., Khaliullin, R. Z., Schütt, O., Schiffmann, F., et al. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0007045 · Cited by 4,468
Molecular Docking: A Powerful Approach for Structure-Based Drug Discovery
Meng, X.-Y., Zhang, H.-X., Mezei, M., & Cui, M. (2011) · Current Computer Aided-Drug Design · doi:10.2174/157340911795677602 · Cited by 3,771
Metadata
- Authors
- Brooks, B. R., Bruccoleri, R. E., Olafson, B. D., States, D. J., Swaminathan, S., & Karplus, M.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 1983-06
- Volume
- 4
- Issue
- 2
- Pages
- 187-217
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- OpenAlex
- W2162166182
- Cited by
- 14,944
- References
- 3
- FWCI
- 11.50
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
