COMPUTATIONAL AND AI-BASED DRUG REPURPOSING APPROACHES IN ANTI-AGING RESEARCH

Abstract

Aging is a multilevel biological process characterized by the progressive loss of structural and functional integrity in tissues and organs, ultimately leading to various diseases. Advances in geroscience and computational biology have accelerated the discovery of potential anti-aging compounds, especially through drug repurposing approaches that utilise existing natural products and approved drugs for novel therapeutic applications. In this review article, we summarize the current understanding of the molecular hallmarks of aging, including DNA damage, genomic instability, mitochondrial dysfunction, impaired proteostasis, and dysregulation of nutrient-sensing pathways. The review discussed the computational and AI approaches that have been used to systematically search for geroprotectors‚ including machine learning‚ deep learning‚ network-based and signature-based approaches‚ along with the high-throughput techniques that have enabled the rapid identification of compounds that extend lifespan․ In summary‚ the present review provides an updated framework to harness the advances in molecular biology and computational science for AI-assisted repurposing of anti-aging therapeutics․