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A combined quantum mechanical and molecular mechanical potential for molecular dynamics simulations
Abstract
A combined quantum mechanical (QM) and molecular mechanical (MM) potential has been developed for the study of reactions in condensed phases. For the quantum mechanical calculations semiempirical methods of the MNDO and AM1 type are used, while the molecular mechanics part is treated with the CHARMM force field. Specific prescriptions are given for the interactions between the QM and MM portions of the system; cases in which the QM and MM methodology is applied to parts of the same molecule or to different molecules are considered. The details of the method and a range of test calculations, including comparisons with ab initio and experimental results, are given. It is found that in many cases satisfactory results are obtained. However, there are limitations to this type of approach, some of which arise from the AM1 or MNDO methods themselves and others from the present QM/MM implementation. This suggests that it is important to test the applicability of the method to each particular case prior to its use. Possible areas of improvement in the methodology are discussed.
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Cites
Warshel, A., & Huler, E. (1974) · Chemical Physics · doi:10.1016/0301-0104(74)85030-5 · Cited by 88
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Metadata
- Authors
- Field, M. J., Bash, P. A., & Karplus, M.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 1990-07
- Volume
- 11
- Issue
- 6
- Pages
- 700-733
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- OpenAlex
- W2027815611
- Cited by
- 2,466
- References
- 1
- FWCI
- 7.51
- Type
- journal article
- Language
- en
- Open access
- closed
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- Field, M. J., Bash, P. A., & Karplus, M. (1990). A combined quantum mechanical and molecular mechanical potential for molecular dynamics simulations. Journal of Computational Chemistry. https://doi.org/10.1002/jcc.540110605
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.