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Using the drug-protein interactome to identify anti-ageing compounds for humans
Matías Fuentealba, Handan Melike Dönertaş, Rhianna Williams, Johnathan Labbadia, Janet M. Thornton, Linda Partridge
PLoS Computational Biology · 2019 · ▲ 46 citations
Abstract
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(definition) 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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- 10.1371/journal.pcbi.1006639
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- 2026-06-29 MST
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APA
Fuentealba, M., Dönertaş, H.M., Williams, R., Labbadia, J., Thornton, J.M., & Partridge, L. (2019). Using the drug-protein interactome to identify anti-ageing compounds for humans. <em>PLoS Computational Biology</em>. https://doi.org/10.1371/journal.pcbi.1006639
Vancouver
Fuentealba M, Dönertaş HM, Williams R, Labbadia J, Thornton JM, Partridge L. Using the drug-protein interactome to identify anti-ageing compounds for humans. PLoS Computational Biology. 2019. doi:10.1371/journal.pcbi.1006639.
BibTeX
@article{matas2019Usingt,
title = {Using the drug-protein interactome to identify anti-ageing compounds for humans},
author = {Matías Fuentealba and Handan Melike Dönertaş and Rhianna Williams and Johnathan Labbadia and Janet M. Thornton and Linda Partridge},
journal = {PLoS Computational Biology},
year = {2019},
doi = {10.1371/journal.pcbi.1006639},
}
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