August 31, 2021 Artificial intelligence (AI) has been paired with one of the simplest of organisms--the nematode Caenorhabditis elegans--to enlighten the scientific community about the physical and chemical properties of drug compounds with anti-aging effects, according to Brendan Howlin, reader in computational chemistry at the University of Surrey (U.K.). The predictive power of the methodology has just been demonstrated using an established database of small molecules found to extend life in model organisms. The 1,738 compounds in the DrugAge database were broadly separated into flavonoids (e.g., from fruits and vegetables), fatty acids (e.g, omega-3 fatty acids), and those with a carbon-oxygen bond (e.g., alcohol)--all heavily tied to nutrition and lifestyle choices. Pharmaceuticals could be developed based on that nutraceutical knowledge, including the importance of the number of nitrogen atoms, says Howlin. Unlike prior efforts using AI to identify compounds that slow the aging process, Howlin used machine learning to calculate the quantitative structure–activity relationship (QSAR) of molecules.

The University of Surrey has built an artificial intelligence (AI) model that identifies chemical compounds that promote healthy aging -- paving the way towards pharmaceutical innovations that extend a person's lifespan. In a paper published by Nature Communication's Scientific Reports, a team of chemists from Surrey built a machine learning model based on the information from the DrugAge database to predict whether a compound can extend the life of Caenorhabditis elegans -- a translucent worm that shares a similar metabolism to humans. The worm's shorter lifespan gave the researchers the opportunity to see the impact of the chemical compounds. "Ageing is increasingly being recognized as a set of diseases in modern medicine, and we can apply the tools of the digital world, such as AI, to help slow down or protect against aging and age-related diseases. Our study demonstrates the revolutionary ability of AI to aid the identification of compounds with anti-aging properties."