AI-Driven Identification of Exceptionally Efficacious Polypharmacological Compounds That Extend the Lifespan of Caenorhabditis elegans.
Abstract
Analysis of existing lifespan-extending geroprotective compounds suggested that polypharmacological compounds are the most effective geroprotectors, specifically those that bind multiple biogenic amine receptors. To test this hypothesis, we used graph neural networks to predict polypharmacological geroprotectors and evaluated them in Caenorhabditis elegans. Over 70% of the selected compounds extended lifespan, with effect sizes in the top 5% compared to all geroprotectors recorded in the DrugAge database. Thus, our study reveals that rationally designing polypharmacological compounds enables the design of geroprotectors with exceptional efficacy.
The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.
Research summary
The paper claims that rationally designed polypharmacological compounds can significantly extend the lifespan of Caenorhabditis elegans. This research is relevant as it addresses the development of compounds aimed at extending lifespan, which is a core aspect of longevity research.
Author of this paper? Send a correction.