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Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response

Understanding the mechanisms underlying drug therapeutic action and toxicity is crucial for the prevention and management of drug adverse reactions, and paves the way for a more efficient and rational drug design. The characterization of drug targets, drug metabolism proteins, and proteins associate...

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Autores principales: Piñero, Janet, Gonzalez-Perez, Abel, Guney, Emre, Aguirre-Plans, Joaquim, Sanz, Ferran, Oliva, Baldo, Furlong, Laura I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6168038/
https://www.ncbi.nlm.nih.gov/pubmed/30319692
http://dx.doi.org/10.3389/fgene.2018.00412
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author Piñero, Janet
Gonzalez-Perez, Abel
Guney, Emre
Aguirre-Plans, Joaquim
Sanz, Ferran
Oliva, Baldo
Furlong, Laura I.
author_facet Piñero, Janet
Gonzalez-Perez, Abel
Guney, Emre
Aguirre-Plans, Joaquim
Sanz, Ferran
Oliva, Baldo
Furlong, Laura I.
author_sort Piñero, Janet
collection PubMed
description Understanding the mechanisms underlying drug therapeutic action and toxicity is crucial for the prevention and management of drug adverse reactions, and paves the way for a more efficient and rational drug design. The characterization of drug targets, drug metabolism proteins, and proteins associated to side effects according to their expression patterns, their tolerance to genomic variation and their role in cellular networks, is a necessary step in this direction. In this contribution, we hypothesize that different classes of proteins involved in the therapeutic effect of drugs and in their adverse effects have distinctive transcriptomics, genomics and network features. We explored the properties of these proteins within global and organ-specific interactomes, using multi-scale network features, evaluated their gene expression profiles in different organs and tissues, and assessed their tolerance to loss-of-function variants leveraging data from 60K subjects. We found that drug targets that mediate side effects are more central in cellular networks, more intolerant to loss-of-function variation, and show a wider breadth of tissue expression than targets not mediating side effects. In contrast, drug metabolizing enzymes and transporters are less central in the interactome, more tolerant to deleterious variants, and are more constrained in their tissue expression pattern. Our findings highlight distinctive features of proteins related to drug action, which could be applied to prioritize drugs with fewer probabilities of causing side effects.
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spelling pubmed-61680382018-10-12 Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response Piñero, Janet Gonzalez-Perez, Abel Guney, Emre Aguirre-Plans, Joaquim Sanz, Ferran Oliva, Baldo Furlong, Laura I. Front Genet Genetics Understanding the mechanisms underlying drug therapeutic action and toxicity is crucial for the prevention and management of drug adverse reactions, and paves the way for a more efficient and rational drug design. The characterization of drug targets, drug metabolism proteins, and proteins associated to side effects according to their expression patterns, their tolerance to genomic variation and their role in cellular networks, is a necessary step in this direction. In this contribution, we hypothesize that different classes of proteins involved in the therapeutic effect of drugs and in their adverse effects have distinctive transcriptomics, genomics and network features. We explored the properties of these proteins within global and organ-specific interactomes, using multi-scale network features, evaluated their gene expression profiles in different organs and tissues, and assessed their tolerance to loss-of-function variants leveraging data from 60K subjects. We found that drug targets that mediate side effects are more central in cellular networks, more intolerant to loss-of-function variation, and show a wider breadth of tissue expression than targets not mediating side effects. In contrast, drug metabolizing enzymes and transporters are less central in the interactome, more tolerant to deleterious variants, and are more constrained in their tissue expression pattern. Our findings highlight distinctive features of proteins related to drug action, which could be applied to prioritize drugs with fewer probabilities of causing side effects. Frontiers Media S.A. 2018-09-25 /pmc/articles/PMC6168038/ /pubmed/30319692 http://dx.doi.org/10.3389/fgene.2018.00412 Text en Copyright © 2018 Piñero, Gonzalez-Perez, Guney, Aguirre-Plans, Sanz, Oliva and Furlong. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Piñero, Janet
Gonzalez-Perez, Abel
Guney, Emre
Aguirre-Plans, Joaquim
Sanz, Ferran
Oliva, Baldo
Furlong, Laura I.
Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response
title Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response
title_full Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response
title_fullStr Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response
title_full_unstemmed Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response
title_short Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response
title_sort network, transcriptomic and genomic features differentiate genes relevant for drug response
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6168038/
https://www.ncbi.nlm.nih.gov/pubmed/30319692
http://dx.doi.org/10.3389/fgene.2018.00412
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