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Drug combinatorics and side effect estimation on the signed human drug-target network
BACKGROUND: The mode of action of a drug on its targets can often be classified as being positive (activator, potentiator, agonist, etc.) or negative (inhibitor, blocker, antagonist, etc.). The signed edges of a drug-target network can be used to investigate the combined mechanisms of action of mult...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4986181/ https://www.ncbi.nlm.nih.gov/pubmed/27526853 http://dx.doi.org/10.1186/s12918-016-0326-8 |
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author | Torres, Núria Ballber Altafini, Claudio |
author_facet | Torres, Núria Ballber Altafini, Claudio |
author_sort | Torres, Núria Ballber |
collection | PubMed |
description | BACKGROUND: The mode of action of a drug on its targets can often be classified as being positive (activator, potentiator, agonist, etc.) or negative (inhibitor, blocker, antagonist, etc.). The signed edges of a drug-target network can be used to investigate the combined mechanisms of action of multiple drugs on the ensemble of common targets. RESULTS: In this paper it is shown that for the signed human drug-target network the majority of drug pairs tend to have synergistic effects on the common targets, i.e., drug pairs tend to have modes of action with the same sign on most of the shared targets, especially for the principal pharmacological targets of a drug. Methods are proposed to compute this synergism, as well as to estimate the influence of the drugs on the side effect of another drug. CONCLUSIONS: Enriching a drug-target network with information of functional nature like the sign of the interactions allows to explore in a systematic way a series of network properties of key importance in the context of computational drug combinatorics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0326-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4986181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49861812016-08-17 Drug combinatorics and side effect estimation on the signed human drug-target network Torres, Núria Ballber Altafini, Claudio BMC Syst Biol Research Article BACKGROUND: The mode of action of a drug on its targets can often be classified as being positive (activator, potentiator, agonist, etc.) or negative (inhibitor, blocker, antagonist, etc.). The signed edges of a drug-target network can be used to investigate the combined mechanisms of action of multiple drugs on the ensemble of common targets. RESULTS: In this paper it is shown that for the signed human drug-target network the majority of drug pairs tend to have synergistic effects on the common targets, i.e., drug pairs tend to have modes of action with the same sign on most of the shared targets, especially for the principal pharmacological targets of a drug. Methods are proposed to compute this synergism, as well as to estimate the influence of the drugs on the side effect of another drug. CONCLUSIONS: Enriching a drug-target network with information of functional nature like the sign of the interactions allows to explore in a systematic way a series of network properties of key importance in the context of computational drug combinatorics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0326-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-08-15 /pmc/articles/PMC4986181/ /pubmed/27526853 http://dx.doi.org/10.1186/s12918-016-0326-8 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Torres, Núria Ballber Altafini, Claudio Drug combinatorics and side effect estimation on the signed human drug-target network |
title | Drug combinatorics and side effect estimation on the signed human drug-target network |
title_full | Drug combinatorics and side effect estimation on the signed human drug-target network |
title_fullStr | Drug combinatorics and side effect estimation on the signed human drug-target network |
title_full_unstemmed | Drug combinatorics and side effect estimation on the signed human drug-target network |
title_short | Drug combinatorics and side effect estimation on the signed human drug-target network |
title_sort | drug combinatorics and side effect estimation on the signed human drug-target network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4986181/ https://www.ncbi.nlm.nih.gov/pubmed/27526853 http://dx.doi.org/10.1186/s12918-016-0326-8 |
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