New Delhi: Artificial intelligence (IA) Guided screening has identified three anti-aging treatments drug candidates targeting ‘zombie’ cells, an important milestone for both longevity investigationthe researchers revealed.
The team of the Massachusetts Institute of Technology (WITH) and the Broad Institute of WITH and harvarddescribed AI-guided screening of more than 800,000 compounds to reveal three drug candidates with comparable efficacy and superior medical chemistry properties to those currently under investigation.
“The data demonstrates that we can explore the chemical space in silico and emerge with multiple antiaging compound candidates that are more likely to be successful in the clinic, compared to even the most promising examples of their kind being studied today.” said Felix Wong, first author of the paper.
The researchers combined synthetic biology and machine learning to tackle aging, demonstrating the power of AI to discover new “senolytic” compounds, a class of small molecules that are intensively studied for their ability to suppress age-related processes. such as fibrosis, inflammation and cancer.
Senolytics are compounds that selectively induce apoptosis, or programmed cell death, in senescent cells that are no longer dividing.
A hallmark of aging, senescent cells have been implicated in a wide spectrum of age-related diseases and conditions, including cancer, diabetes, cardiovascular disease, and Alzheimer’s disease.
“One of the most promising routes to treating age-related diseases is to identify therapeutic interventions that selectively kill these cells from the body in a similar way to how antibiotics kill bacteria without harming host cells. The compounds we discovered show high selectivity as well as the favorable medicinal chemical properties needed to produce a successful drug,” explained Satotaka Omori, head of aging biology at Integrated Biosciences.
