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DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome
Drug–drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug–human protein interactions, it is reasonable to analyze the chemical–protein interactome (CPI) profiles of the drugs to predict thei...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086096/ https://www.ncbi.nlm.nih.gov/pubmed/24875476 http://dx.doi.org/10.1093/nar/gku433 |
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author | Luo, Heng Zhang, Ping Huang, Hui Huang, Jialiang Kao, Emily Shi, Leming He, Lin Yang, Lun |
author_facet | Luo, Heng Zhang, Ping Huang, Hui Huang, Jialiang Kao, Emily Shi, Leming He, Lin Yang, Lun |
author_sort | Luo, Heng |
collection | PubMed |
description | Drug–drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug–human protein interactions, it is reasonable to analyze the chemical–protein interactome (CPI) profiles of the drugs to predict their DDIs. Here we introduce the DDI-CPI server, which can make real-time DDI predictions based only on molecular structure. When the user submits a molecule, the server will dock user's molecule across 611 human proteins, generating a CPI profile that can be used as a feature vector for the pre-constructed prediction model. It can suggest potential DDIs between the user's molecule and our library of 2515 drug molecules. In cross-validation and independent validation, the server achieved an AUC greater than 0.85. Additionally, by investigating the CPI profiles of predicted DDI, users can explore the PK/PD proteins that might be involved in a particular DDI. A 3D visualization of the drug-protein interaction will be provided as well. The DDI-CPI is freely accessible at http://cpi.bio-x.cn/ddi/. |
format | Online Article Text |
id | pubmed-4086096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-40860962014-12-01 DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome Luo, Heng Zhang, Ping Huang, Hui Huang, Jialiang Kao, Emily Shi, Leming He, Lin Yang, Lun Nucleic Acids Res Article Drug–drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug–human protein interactions, it is reasonable to analyze the chemical–protein interactome (CPI) profiles of the drugs to predict their DDIs. Here we introduce the DDI-CPI server, which can make real-time DDI predictions based only on molecular structure. When the user submits a molecule, the server will dock user's molecule across 611 human proteins, generating a CPI profile that can be used as a feature vector for the pre-constructed prediction model. It can suggest potential DDIs between the user's molecule and our library of 2515 drug molecules. In cross-validation and independent validation, the server achieved an AUC greater than 0.85. Additionally, by investigating the CPI profiles of predicted DDI, users can explore the PK/PD proteins that might be involved in a particular DDI. A 3D visualization of the drug-protein interaction will be provided as well. The DDI-CPI is freely accessible at http://cpi.bio-x.cn/ddi/. Oxford University Press 2014-07-01 2014-05-29 /pmc/articles/PMC4086096/ /pubmed/24875476 http://dx.doi.org/10.1093/nar/gku433 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Luo, Heng Zhang, Ping Huang, Hui Huang, Jialiang Kao, Emily Shi, Leming He, Lin Yang, Lun DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome |
title | DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome |
title_full | DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome |
title_fullStr | DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome |
title_full_unstemmed | DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome |
title_short | DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome |
title_sort | ddi-cpi, a server that predicts drug–drug interactions through implementing the chemical–protein interactome |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086096/ https://www.ncbi.nlm.nih.gov/pubmed/24875476 http://dx.doi.org/10.1093/nar/gku433 |
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