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Linear-scaling semiempirical quantum calculations for macromolecules
Abstract
A linear-scaling method to carry out semiempirical quantum mechanical calculations for large systems has been developed based on the density matrix version of the divide-and-conquer approach. The method has been tested and demonstrated to be accurate and efficient. With this implementation, semiempirical quantum mechanical calculations are made possible for large molecules over 9000 atoms on a typical workstation. For biological macromolecules, solvent effects are included with a dielectric continuum model.
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Citations
Cited by
Cossi, M., Rega, N., Scalmani, G., & Barone, V. (2003) · Journal of Computational Chemistry · doi:10.1002/jcc.10189 · Cited by 8,056
Q UANTUM M ECHANICAL M ETHODS FOR E NZYME K INETICS
Gao, J., & Truhlar, D. G. (2002) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.53.091301.150114 · Cited by 733
Brunk, E., & Rothlisberger, U. (2015) · Chemical Reviews · doi:10.1021/cr500628b · Cited by 494
Semiempirical quantum–chemical methods
Thiel, W. (2014) · WIREs Computational Molecular Science · doi:10.1002/wcms.1161 · Cited by 353
Dahlke, E. E., & Truhlar, D. G. (2007) · Journal of Chemical Theory and Computation · doi:10.1021/ct600253j · Cited by 287
Metadata
- Authors
- Lee, T.-S., York, D. M., & Yang, W.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 1996-08-15
- Volume
- 105
- Issue
- 7
- Pages
- 2744-2750
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2006588722
- Cited by
- 175
- References
- 0
- FWCI
- 7.44
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Linear-scaling semiempirical quantum calculations for macromolecules. https://app.cochat.ai/papers/10.1063/1.472136
- The paper
- Lee, T.-S., York, D. M., & Yang, W. (1996). Linear-scaling semiempirical quantum calculations for macromolecules. The Journal of Chemical Physics. https://doi.org/10.1063/1.472136
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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.
