Artificial intelligence (AI)- guided screening has identified three anti-aging drug candidates targeting 'zombie' cells, a significant milestone for both longevity research and the application of AI in drug discovery, researchers revealed.
The team from the Massachusetts Institute of Technology (MIT) and the Broad Institute of MIT and Harvard, described the AI-guided screening of more than 800,000 compounds to reveal three drug candidates with comparable efficacy and superior medicinal chemistry properties than those currently under investigation.
"The data demonstrate that we can explore chemical space in silico and emerge with multiple candidate anti-aging compounds that are more likely to succeed in the clinic, compared to even the most promising examples of their kind being studied today," said Felix Wong, co-founder of biotechnology company Integrated Biosciences and first author of the paper published in the journal Nature Aging.
Researchers combined synthetic biology and machine learning to target aging, demonstrating the power of AI to discover novel "senolytic" compounds, a class of small molecules under intense study 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 broad spectrum of age-related diseases and conditions including cancer, diabetes, cardiovascular disease, and Alzheimer's disease.
"One of the most promising routes to treat age-related diseases is to identify therapeutic interventions that selectively remove these cells from the body similarly to how antibiotics kill bacteria without harming host cells. The compounds we discovered display high selectivity, as well as the favourable medicinal chemistry properties needed to yield a successful drug," explained Satotaka Omori, head of aging biology at Integrated Biosciences.
Scientists believe that the compounds discovered will have improved prospects in clinical trials and will eventually help restore health in aging individuals.
"This work illustrates how AI can be used to bring medicine a step closer to therapies that address aging, one of the fundamental challenges in biology," said James J. Collins, Termeer Professor of Medical Engineering and Science at MIT and founding chair of the Integrated Biosciences Scientific Advisory Board. (PB/NewsGram)