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Discovering geroprotectors through the explainable artificial intelligence-based platform AgeXtend.

Sakshi Arora1, Aayushi Mittal1, Subhadeep Duari1

  • 1Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi, India.

Nature Aging
|December 3, 2024
PubMed
Summary
This summary is machine-generated.

Researchers developed AgeXtend, an AI platform, to discover new aging-reducing compounds. This tool successfully identified known longevity molecules and screened billions of compounds, validating novel geroprotectors in model organisms and human cells.

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Area of Science:

  • Biogerontology
  • Computational Biology
  • Metabolomics

Background:

  • Aging is characterized by metabolic shifts impacting cellular health, with many metabolites' roles remaining unknown.
  • Investigating known longevity-promoting compounds offers insights into aging mechanisms and aids in discovering new geroprotectors.

Purpose of the Study:

  • To introduce AgeXtend, an AI-driven platform for predicting geroprotective compounds.
  • To validate AgeXtend's capability in identifying novel longevity molecules and understanding aging pathways.

Main Methods:

  • Developed AgeXtend, an AI platform integrating known geroprotector bioactivity data for prediction, toxicity assessment, and mechanism identification.
  • Screened approximately 1.1 billion compounds using AgeXtend.
  • Validated predicted geroprotectors through lifespan assays in yeast and Caenorhabditis elegans, and investigated microbiome-derived metabolites.
  • Assessed endogenous metabolites as senomodulators in human fibroblast senescence assays.

Main Results:

  • AgeXtend accurately recognized the pro-longevity effects of known geroprotectors like metformin and taurine, even those not used in training.
  • The platform facilitated the identification and experimental validation of numerous novel potential geroprotectors.
  • Endogenous metabolites were identified as potential senomodulators, offering new avenues for aging research.

Conclusions:

  • AgeXtend is a powerful AI tool for discovering geroprotectors and elucidating aging mechanisms.
  • The platform's findings highlight the potential of unexplored compounds and endogenous metabolites in modulating aging.
  • This work advances the understanding of metabolic networks in aging and provides a scalable approach for identifying longevity interventions.