The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions
Open accessAbstract
Much of the information on the Cytochrome P450 enzymes (CYPs) is spread across literature and the internet. Aggregating knowledge about CYPs into one database makes the search more efficient. Text mining on 57 CYPs and drugs led to a mass of papers, which were screened manually for facts about metabolism, SNPs and their effects on drug degradation. Information was put into a database, which enables the user not only to look up a particular CYP and all metabolized drugs, but also to check tolerability of drug-cocktails and to find alternative combinations, to use metabolic pathways more efficiently. The SuperCYP database contains 1170 drugs with more than 3800 interactions including references. Approximately 2000 SNPs and mutations are listed and ordered according to their effect on expression and/or activity. SuperCYP (http://bioinformatics.charite.de/supercyp) is a comprehensive resource focused on CYPs and drug metabolism. Homology-modeled structures of the CYPs can be downloaded in PDB format and related drugs are available as MOL-files. Within the resource, CYPs can be aligned with each other, drug-cocktails can be 'mixed', SNPs, protein point mutations, and their effects can be viewed and corresponding PubMed IDs are given. SuperCYP is meant to be a platform and a starting point for scientists and health professionals for furthering their research.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Comparative evaluation of eight docking tools for docking and virtual screening accuracy
Kellenberger, E., Rodrigo, J., Muller, P., & Rognan, D. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20149 · Cited by 577
Predicting the accuracy of protein–ligand docking on homology models
Bordogna, A., Pandini, A., & Bonati, L. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21601 · Cited by 107
Cited by
Luo, Y., Zhao, X., Zhou, J., Yang, J., Zhang, Y., Kuang, W., Peng, J., Chen, L., & Zeng, J. (2017) · Nature Communications · doi:10.1038/s41467-017-00680-8 · Cited by 916
DGIdb: mining the druggable genome
Griffith, M., Griffith, O. L., Coffman, A. C., Weible, J. V., McMichael, J. F., Spies, N. C., Koval, J., Das, I., Callaway, M. B., Eldred, J. M., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2689 · Cited by 533
Information retrieval and text mining technologies for chemistry
Krallinger, M., Rabal, O., Lourenço, A., Oyarzabal, J., & Valencia, A. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00851 · Cited by 281
Drug databases and their contributions to drug repurposing
Masoudi-Sobhanzadeh, Y., Omidi, Y., Amanlou, M., & Masoudi-Nejad, A. (2020) · Genomics · doi:10.1016/j.ygeno.2019.06.021 · Cited by 131
Predictors of Blood Trihalomethane Concentrations in NHANES 1999–2006
Riederer, A. M., Dhingra, R., Blount, B. C., & Steenland, K. (2014) · Environmental Health Perspectives · doi:10.1289/ehp.1306499 · Cited by 46
Metadata
- Authors
- Preissner, S., Kroll, K., Dunkel, M., Senger, C., Goldsobel, G., Kuzman, D., Guenther, S., Winnenburg, R., Schroeder, M., & Preissner, R.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-11-24
- Volume
- 38
- Issue
- suppl_1
- Pages
- D237-D243
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2140049079
- Cited by
- 274
- References
- 2
- FWCI
- 8.09
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions. https://app.cochat.ai/papers/10.1093/nar/gkp970
- The paper
- Preissner, S., Kroll, K., Dunkel, M., Senger, C., Goldsobel, G., Kuzman, D., Guenther, S., Winnenburg, R., Schroeder, M., & Preissner, R. (2010). SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions. Nucleic Acids Research. https://doi.org/10.1093/nar/gkp970
Data sources
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.