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Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships

The level of attrition on drug discovery, particularly at advanced stages, is very high due to unexpected adverse drug reactions (ADRs) caused by drug candidates, and thus, being able to predict undesirable responses when modulating certain protein targets would contribute to the development of safe...

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Autores principales: Galletti, Cristiano, Bota, Patricia Mirela, Oliva, Baldo, Fernandez-Fuentes, Narcis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8533369/
https://www.ncbi.nlm.nih.gov/pubmed/34679164
http://dx.doi.org/10.1093/database/baab068
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author Galletti, Cristiano
Bota, Patricia Mirela
Oliva, Baldo
Fernandez-Fuentes, Narcis
author_facet Galletti, Cristiano
Bota, Patricia Mirela
Oliva, Baldo
Fernandez-Fuentes, Narcis
author_sort Galletti, Cristiano
collection PubMed
description The level of attrition on drug discovery, particularly at advanced stages, is very high due to unexpected adverse drug reactions (ADRs) caused by drug candidates, and thus, being able to predict undesirable responses when modulating certain protein targets would contribute to the development of safer drugs and have important economic implications. On the one hand, there are a number of databases that compile information of drug–target interactions. On the other hand, there are a number of public resources that compile information on drugs and ADR. It is therefore possible to link target and ADRs using drug entities as connecting elements. Here, we present T-ARDIS (Target—Adverse Reaction Database Integrated Search) database, a resource that provides comprehensive information on proteins and associated ADRs. By combining the information from drug–protein and drug–ADR databases, we statistically identify significant associations between proteins and ADRs. Besides describing the relationship between proteins and ADRs, T-ARDIS provides detailed description about proteins along with the drug and adverse reaction information. Currently T-ARDIS contains over 3000 ADR and 248 targets for a total of more 17 000 pairwise interactions. Each entry can be retrieved through multiple search terms including target Uniprot ID, gene name, adverse effect and drug name. Ultimately, the T-ARDIS database has been created in response to the increasing interest in identifying early in the drug development pipeline potentially problematic protein targets whose modulation could result in ADRs. Database URL: http://www.bioinsilico.org/T-ARDIS
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spelling pubmed-85333692021-10-25 Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships Galletti, Cristiano Bota, Patricia Mirela Oliva, Baldo Fernandez-Fuentes, Narcis Database (Oxford) Database Tool The level of attrition on drug discovery, particularly at advanced stages, is very high due to unexpected adverse drug reactions (ADRs) caused by drug candidates, and thus, being able to predict undesirable responses when modulating certain protein targets would contribute to the development of safer drugs and have important economic implications. On the one hand, there are a number of databases that compile information of drug–target interactions. On the other hand, there are a number of public resources that compile information on drugs and ADR. It is therefore possible to link target and ADRs using drug entities as connecting elements. Here, we present T-ARDIS (Target—Adverse Reaction Database Integrated Search) database, a resource that provides comprehensive information on proteins and associated ADRs. By combining the information from drug–protein and drug–ADR databases, we statistically identify significant associations between proteins and ADRs. Besides describing the relationship between proteins and ADRs, T-ARDIS provides detailed description about proteins along with the drug and adverse reaction information. Currently T-ARDIS contains over 3000 ADR and 248 targets for a total of more 17 000 pairwise interactions. Each entry can be retrieved through multiple search terms including target Uniprot ID, gene name, adverse effect and drug name. Ultimately, the T-ARDIS database has been created in response to the increasing interest in identifying early in the drug development pipeline potentially problematic protein targets whose modulation could result in ADRs. Database URL: http://www.bioinsilico.org/T-ARDIS Oxford University Press 2021-10-22 /pmc/articles/PMC8533369/ /pubmed/34679164 http://dx.doi.org/10.1093/database/baab068 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Tool
Galletti, Cristiano
Bota, Patricia Mirela
Oliva, Baldo
Fernandez-Fuentes, Narcis
Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
title Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
title_full Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
title_fullStr Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
title_full_unstemmed Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
title_short Mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
title_sort mining drug–target and drug–adverse drug reaction databases to identify target–adverse drug reaction relationships
topic Database Tool
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8533369/
https://www.ncbi.nlm.nih.gov/pubmed/34679164
http://dx.doi.org/10.1093/database/baab068
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