AIアルゴリズムが老化に対抗できる薬剤を発見(AI algorithms find drugs that could combat ageing)


2023-06-14 エディンバラ大学



機械学習による老化防止剤の発見 Discovery of senolytics using machine learning

Vanessa Smer-Barreto,Andrea Quintanilla,Richard J. R. Elliott,John C. Dawson,Jiugeng Sun,Víctor M. Campa,Álvaro Lorente-Macías,Asier Unciti-Broceta,Neil O. Carragher,Juan Carlos Acosta & Diego A. Oyarzún
Nature Communications  Published:10 June 2023

AIアルゴリズムが老化に対抗できる薬剤を発見(AI algorithms find drugs that could combat ageing)


Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral infection. Despite growing interest in targeted elimination of senescent cells, only few senolytics are known due to the lack of well-characterised molecular targets. Here, we report the discovery of three senolytics using cost-effective machine learning algorithms trained solely on published data. We computationally screened various chemical libraries and validated the senolytic action of ginkgetin, periplocin and oleandrin in human cell lines under various modalities of senescence. The compounds have potency comparable to known senolytics, and we show that oleandrin has improved potency over its target as compared to best-in-class alternatives. Our approach led to several hundred-fold reduction in drug screening costs and demonstrates that artificial intelligence can take maximum advantage of small and heterogeneous drug screening data, paving the way for new open science approaches to early-stage drug discovery.