Cargando…
DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome
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 interaction...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3125745/ https://www.ncbi.nlm.nih.gov/pubmed/21558322 http://dx.doi.org/10.1093/nar/gkr299 |
_version_ | 1782207248613769216 |
---|---|
author | Luo, Heng Chen, Jian Shi, Leming Mikailov, Mike Zhu, Huang Wang, Kejian He, Lin Yang, Lun |
author_facet | Luo, Heng Chen, Jian Shi, Leming Mikailov, Mike Zhu, Huang Wang, Kejian He, Lin Yang, Lun |
author_sort | Luo, Heng |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-3125745 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31257452011-07-05 DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome Luo, Heng Chen, Jian Shi, Leming Mikailov, Mike Zhu, Huang Wang, Kejian He, Lin Yang, Lun Nucleic Acids Res Articles 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/. Oxford University Press 2011-07-01 2011-05-10 /pmc/articles/PMC3125745/ /pubmed/21558322 http://dx.doi.org/10.1093/nar/gkr299 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Luo, Heng Chen, Jian Shi, Leming Mikailov, Mike Zhu, Huang Wang, Kejian He, Lin Yang, Lun DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome |
title | DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome |
title_full | DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome |
title_fullStr | DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome |
title_full_unstemmed | DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome |
title_short | DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome |
title_sort | drar-cpi: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3125745/ https://www.ncbi.nlm.nih.gov/pubmed/21558322 http://dx.doi.org/10.1093/nar/gkr299 |
work_keys_str_mv | AT luoheng drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome AT chenjian drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome AT shileming drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome AT mikailovmike drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome AT zhuhuang drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome AT wangkejian drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome AT helin drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome AT yanglun drarcpiaserverforidentifyingdrugrepositioningpotentialandadversedrugreactionsviathechemicalproteininteractome |