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DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome
Open accessAbstract
Identifying new indications for existing drugs (drug repositioning) is an efficient way of maximizing their potential. Adverse drug reaction (ADR) is one of the leading causes of death among hospitalized patients. As both new indications and ADRs are caused by unexpected chemical-protein interactions on off-targets, it is reasonable to predict these interactions by mining the chemical-protein interactome (CPI). Making such predictions has recently been facilitated by a web server named DRAR-CPI. This server has a representative collection of drug molecules and targetable human proteins built up from our work in drug repositioning and ADR. When a user submits a molecule, the server will give the positive or negative association scores between the user's molecule and our library drugs based on their interaction profiles towards the targets. Users can thus predict the indications or ADRs of their molecule based on the association scores towards our library drugs. We have matched our predictions of drug-drug associations with those predicted via gene-expression profiles, achieving a matching rate as high as 74%. We have also successfully predicted the connections between anti-psychotics and anti-infectives, indicating the underlying relevance of anti-psychotics in the potential treatment of infections, vice versa. This server is freely available at http://cpi.bio-x.cn/drar/.
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“It is noteworthy that all ML methods showed relatively small differences in predictive accuracy and the advantage of the DNN was not readily apparent.”
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Metadata
- Authors
- Luo, H., Chen, J., Shi, L., Mikailov, M., Zhu, H., Wang, K., He, L., & Yang, L.
- Affiliations
- Shanghai Jiao Tong University (CN)
- United States Food and Drug Administration (US)
- Corresponding author
- He, Lin
- Yang, Lun
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-05-10
- Volume
- 39
- Issue
- suppl_2
- Pages
- W492-W498
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC3125745
- OpenAlex
- W2143251418
- Cited by
- 206
- References
- 54
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 5 · 2023: 12 · 2022: 10 · 2021: 17 · 2020: 18 · 2019: 26 · 2018: 17 · 2017: 13 · 2016: 22 · 2015: 14 · 2014: 15 · 2013: 14 · 2012: 13
- FWCI
- 13.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Keywords
- drug repurposing, adverse drug reactions, off-target interactions, web server, gene expression profiles, anti-infective agents
- MeSH terms
- Rosiglitazone, Anti-Infective Agents, Pharmaceutical Preparations, Humans, Hypoglycemic Agents, Ligands, Proteins, Software, Antipsychotic Agents, Internet, Thiazolidinediones, Drug Repositioning, Drug-Related Side Effects and Adverse Reactions
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