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Centrality of drug targets in protein networks
BACKGROUND: In the pharmaceutical industry, competing for few validated drug targets there is a drive to identify new ways of therapeutic intervention. Here, we attempted to define guidelines to evaluate a target’s ‘fitness’ based on its node characteristics within annotated protein functional netwo...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8555226/ https://www.ncbi.nlm.nih.gov/pubmed/34715787 http://dx.doi.org/10.1186/s12859-021-04342-x |
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author | Viacava Follis, Ariele |
author_facet | Viacava Follis, Ariele |
author_sort | Viacava Follis, Ariele |
collection | PubMed |
description | BACKGROUND: In the pharmaceutical industry, competing for few validated drug targets there is a drive to identify new ways of therapeutic intervention. Here, we attempted to define guidelines to evaluate a target’s ‘fitness’ based on its node characteristics within annotated protein functional networks to complement contingent therapeutic hypotheses. RESULTS: We observed that targets of approved, selective small molecule drugs exhibit high node centrality within protein networks relative to a broader set of investigational targets spanning various development stages. Targets of approved drugs also exhibit higher centrality than other proteins within their respective functional class. These findings expand on previous reports of drug targets’ network centrality by suggesting some centrality metrics such as low topological coefficient as inherent characteristics of a ‘good’ target, relative to other exploratory targets and regardless of its functional class. These centrality metrics could thus be indicators of an individual protein’s ‘fitness’ as potential drug target. Correlations between protein nodes’ network centrality and number of associated publications underscored the possibility of knowledge bias as an inherent limitation to such predictions. CONCLUSIONS: Despite some entanglement with knowledge bias, like structure-oriented ‘druggability’ assessments of new protein targets, centrality metrics could assist early pharmaceutical discovery teams in evaluating potential targets with limited experimental proof of concept and help allocate resources for an effective drug discovery pipeline. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04342-x. |
format | Online Article Text |
id | pubmed-8555226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-85552262021-10-29 Centrality of drug targets in protein networks Viacava Follis, Ariele BMC Bioinformatics Research BACKGROUND: In the pharmaceutical industry, competing for few validated drug targets there is a drive to identify new ways of therapeutic intervention. Here, we attempted to define guidelines to evaluate a target’s ‘fitness’ based on its node characteristics within annotated protein functional networks to complement contingent therapeutic hypotheses. RESULTS: We observed that targets of approved, selective small molecule drugs exhibit high node centrality within protein networks relative to a broader set of investigational targets spanning various development stages. Targets of approved drugs also exhibit higher centrality than other proteins within their respective functional class. These findings expand on previous reports of drug targets’ network centrality by suggesting some centrality metrics such as low topological coefficient as inherent characteristics of a ‘good’ target, relative to other exploratory targets and regardless of its functional class. These centrality metrics could thus be indicators of an individual protein’s ‘fitness’ as potential drug target. Correlations between protein nodes’ network centrality and number of associated publications underscored the possibility of knowledge bias as an inherent limitation to such predictions. CONCLUSIONS: Despite some entanglement with knowledge bias, like structure-oriented ‘druggability’ assessments of new protein targets, centrality metrics could assist early pharmaceutical discovery teams in evaluating potential targets with limited experimental proof of concept and help allocate resources for an effective drug discovery pipeline. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04342-x. BioMed Central 2021-10-29 /pmc/articles/PMC8555226/ /pubmed/34715787 http://dx.doi.org/10.1186/s12859-021-04342-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Viacava Follis, Ariele Centrality of drug targets in protein networks |
title | Centrality of drug targets in protein networks |
title_full | Centrality of drug targets in protein networks |
title_fullStr | Centrality of drug targets in protein networks |
title_full_unstemmed | Centrality of drug targets in protein networks |
title_short | Centrality of drug targets in protein networks |
title_sort | centrality of drug targets in protein networks |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8555226/ https://www.ncbi.nlm.nih.gov/pubmed/34715787 http://dx.doi.org/10.1186/s12859-021-04342-x |
work_keys_str_mv | AT viacavafollisariele centralityofdrugtargetsinproteinnetworks |