The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Predicting drug metabolism: experiment and/or computation?
Open accessAbstract
Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.
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Citations
Cites
Host-gut microbiota metabolic interactions
Nicholson, J. K., Holmes, E., Kinross, J., Burcelin, R., Gibson, G., Jia, W., & Pettersson, S. (2012) · Science · doi:10.1126/science.1223813 · Cited by 4,760
ChEMBL: a large-scale bioactivity database for drug discovery
Gaulton, A., Bellis, L. J., Bento, A. P., Chambers, J., Davies, M., Hersey, A., Light, Y., McGlinchey, S., Michalovich, D., Al-Lazikani, B., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr777 · Cited by 4,382
DrugBank: a comprehensive resource for in silico drug discovery and exploration
Wishart, D. S. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj067 · Cited by 3,892
Reactions and enzymes in the metabolism of drugs and other xenobiotics
Testa, B., Pedretti, A., & Vistoli, G. (2012) · Drug Discovery Today · doi:10.1016/j.drudis.2012.01.017 · Cited by 254
Microfluidic devices for in vitro studies on liver drug metabolism and toxicity
van Midwoud, P. M., Verpoorte, E., & Groothuis, G. M. M. (2011) · Integrative Biology · doi:10.1039/c0ib00119h · Cited by 115
How do metabolites differ from their parent molecules and how are they excreted?
Kirchmair, J., Howlett, A., Peironcely, J. E., Murrell, D. S., Williamson, M. J., Adams, S. E., Hankemeier, T., van Buren, L., Duchateau, G., Klaffke, W., et al. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci300487z · Cited by 43
Self-citationKitamura, S., & Sugihara, K. (2014) · Xenobiotica · doi:10.3109/00498254.2013.868062 · Cited by 38
Cited by
Daina, A., Michielin, O., & Zoete, V. (2017) · Scientific Reports · doi:10.1038/srep42717 · Cited by 18,367
DrugBank 5.0: a major update to the DrugBank database for 2018
Wishart, D. S., Feunang, Y. D., Guo, A. C., Lo, E. J., Marcu, A., Grant, J. R., Sajed, T., Johnson, D., Li, C., Sayeeda, Z., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1037 · Cited by 8,404
Counting on natural products for drug design
Rodrigues, T., Reker, D., Schneider, P., & Schneider, G. (2016) · Nature Chemistry · doi:10.1038/nchem.2479 · Cited by 1,250
Self-citationIdentification of bioactive metabolites using activity metabolomics
Rinschen, M. M., Ivanisevic, J., Giera, M., & Siuzdak, G. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0108-4 · Cited by 1,008
eD octor: machine learning and the future of medicine
Handelman, G. S., Kok, H. K., Chandra, R. V., Razavi, A. H., Lee, M. J., & Asadi, H. (2018) · Journal of Internal Medicine · doi:10.1111/joim.12822 · Cited by 956
Metadata
- Authors
- Kirchmair, J., Göller, A. H., Lang, D., Kunze, J., Testa, B., Wilson, I. D., Glen, R. C., & Schneider, G.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2015-04-24
- Volume
- 14
- Issue
- 6
- Pages
- 387-404
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W2069457036
- Cited by
- 502
- References
- 7
- FWCI
- 12.69
- Type
- journal article
- Language
- en
- Open access
- green
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- Kirchmair, J., Göller, A. H., Lang, D., Kunze, J., Testa, B., Wilson, I. D., Glen, R. C., & Schneider, G. (2015). Predicting drug metabolism: experiment and/or computation? Nature Reviews Drug Discovery. https://doi.org/10.1038/nrd4581
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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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