The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism
Open accessAbstract
SMARTCyp is an in silico method that predicts the sites of cytochrome P450-mediated metabolism of druglike molecules. The method is foremost a reactivity model, and as such, it shows a preference for predicting sites that are metabolized by the cytochrome P450 3A4 isoform. SMARTCyp predicts the site of metabolism directly from the 2D structure of a molecule, without requiring calculation of electronic properties or generation of 3D structures. This is a major advantage, because it makes SMARTCyp very fast. Other advantages are that experimental data are not a prerequisite to create the model, and it can easily be integrated with other methods to create models for other cytochrome P450 isoforms. Benchmarking tests on a database of 394 3A4 substrates show that SMARTCyp successfully identifies at least one metabolic site in the top two ranked positions 76% of the time. SMARTCyp is available for download at http://www.farma.ku.dk/p450.
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Role of computer-aided drug design in modern drug discovery
Macalino, S. J. Y., Gosu, V., Hong, S., & Choi, S. (2015) · Archives of Pharmacal Research · doi:10.1007/s12272-015-0640-5 · Cited by 762
Predicting drug metabolism: experiment and/or computation?
Kirchmair, J., Göller, A. H., Lang, D., Kunze, J., Testa, B., Wilson, I. D., Glen, R. C., & Schneider, G. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd4581 · Cited by 502
In silico ADME/T modelling for rational drug design
Wang, Y., Xing, J., Xu, Y., Zhou, N., Peng, J., Xiong, Z., Liu, X., Luo, X., Luo, C., Chen, K., et al. (2015) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583515000190 · Cited by 367
Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms
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Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction
Sadowski, P., Fooshee, D., Subrahmanya, N., & Baldi, P. (2016) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6b00351 · Cited by 65
pragmatic approaches to using computational methods to predict xenobiotic metabolism
Piechota, P., Cronin, M. T. D., Hewitt, M., & Madden, J. C. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400050v · Cited by 30
Metadata
- Authors
- Rydberg, P., Gloriam, D. E., Zaretzki, J., Breneman, C., & Olsen, L.
- Venue
- ACS Medicinal Chemistry Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-03-15
- Volume
- 1
- Issue
- 3
- Pages
- 96-100
- ISSN
- 1948-5875 (ISSN-L)
- OpenAlex
- W1974254541
- Cited by
- 327
- References
- 23
- FWCI
- 13.28
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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