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Using the drug-protein interactome to identify anti-ageing compounds for humans

Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and...

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Autores principales: Fuentealba, Matías, Dönertaş, Handan Melike, Williams, Rhianna, Labbadia, Johnathan, Thornton, Janet M., Partridge, Linda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342327/
https://www.ncbi.nlm.nih.gov/pubmed/30625143
http://dx.doi.org/10.1371/journal.pcbi.1006639
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author Fuentealba, Matías
Dönertaş, Handan Melike
Williams, Rhianna
Labbadia, Johnathan
Thornton, Janet M.
Partridge, Linda
author_facet Fuentealba, Matías
Dönertaş, Handan Melike
Williams, Rhianna
Labbadia, Johnathan
Thornton, Janet M.
Partridge, Linda
author_sort Fuentealba, Matías
collection PubMed
description Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.
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spelling pubmed-63423272019-02-01 Using the drug-protein interactome to identify anti-ageing compounds for humans Fuentealba, Matías Dönertaş, Handan Melike Williams, Rhianna Labbadia, Johnathan Thornton, Janet M. Partridge, Linda PLoS Comput Biol Research Article Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans. Public Library of Science 2019-01-09 /pmc/articles/PMC6342327/ /pubmed/30625143 http://dx.doi.org/10.1371/journal.pcbi.1006639 Text en © 2019 Fuentealba et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fuentealba, Matías
Dönertaş, Handan Melike
Williams, Rhianna
Labbadia, Johnathan
Thornton, Janet M.
Partridge, Linda
Using the drug-protein interactome to identify anti-ageing compounds for humans
title Using the drug-protein interactome to identify anti-ageing compounds for humans
title_full Using the drug-protein interactome to identify anti-ageing compounds for humans
title_fullStr Using the drug-protein interactome to identify anti-ageing compounds for humans
title_full_unstemmed Using the drug-protein interactome to identify anti-ageing compounds for humans
title_short Using the drug-protein interactome to identify anti-ageing compounds for humans
title_sort using the drug-protein interactome to identify anti-ageing compounds for humans
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342327/
https://www.ncbi.nlm.nih.gov/pubmed/30625143
http://dx.doi.org/10.1371/journal.pcbi.1006639
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