Artificial intelligence identifies targeting anti-aging drug candidates

SAN CARLOS, California – New publication in the May issue Natural Aging by researchers from Integrated Biosciences, a biotechnology company that combines synthetic biology and machine learning to target aging, demonstrate the power of artificial intelligence (AI) to discover new senolytic compounds, a class of small molecules that are being studied intensively for their ability to suppress aging. processes such as fibrosis, inflammation and cancer. Paper, “Discovering small molecule senolytics with deep neural networks,” written in collaboration with researchers from the Massachusetts Institute of Technology (MIT) and the Broad Institute of MIT and Harvard, describes an AI-guided screening of more than 800,000 compounds to reveal three drugs. candidates with comparable efficacy and superior medicinal chemical properties to senolytics are currently under investigation.

“The results of this study are an important milestone for longevity research and the application of artificial intelligence to drug discovery,” said Felix Wong, Ph.D., co-founder of Integrated Biosciences and first author of the publication. “These data show that we can explore the chemical space in silicon and coming up with candidate anti-aging compounds that are more likely to be successful in the clinic, even than the most promising examples of their kind currently studied.”

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. Despite promising clinical results, most of the senolytic compounds identified to date are hampered by poor bioavailability and adverse side effects. Integrated Biosciences was founded in 2022 to address these barriers, target other neglected signs of aging, and advance antiaging drug development more generally using artificial intelligence, synthetic biology, and other next-generation tools.

“One of the most promising routes to treating age-related diseases is identifying therapeutic interventions that selectively remove these cells from the body, similar to the way antibiotics kill bacteria without harming host cells. The compounds we found display high selectivity, as well as the favorable medicinal chemistry properties needed to produce successful drugs,” said Satotaka Omori, Ph.D., Head of Aging Biology in Integrated Biosciences and co-author of the first publication. “We believe that compounds discovered using our platform will have better prospects in clinical trials and will ultimately help restore the health of aging individuals.”

In their new study, Integrated Biosciences researchers trained a deep neural network on experimentally generated data to predict the senolytic activity of any molecule. Using this AI model, they discovered three highly selective and potent senolytic compounds from a chemical space of more than 800,000 molecules. All three display chemical properties indicating high oral bioavailability and were found to have favorable toxicity profiles in hemolysis and genotoxicity assays. Structural and biochemical analysis showed that the three compounds bind Bcl-2, a protein that regulates apoptosis and is also a target of chemotherapy. Experiments that tested either compound in 80-week-old mice, roughly the same as an 80-year-old human, found that it cleared senescent cells and reduced the expression of aging-related genes in the kidneys.

“This work illustrates how AI can be used to bring medicine one step closer to therapies that tackle aging, one of the fundamental challenges in biology,” said James J. Collins, Ph.D., Termeer Professor of Engineering and Medical Sciences at MIT and founding chairman Integrated Biosciences Scientific Advisory Council. “Integrated Biosciences builds on basic research my academic lab has been doing for the last decade or so, showing that we can target cellular stress responses using systems and synthetic biology. This experimental tour de force and the stellar platforms that resulted in it make this work stand out in the field of drug discovery and will drive substantial advances in longevity research.”

Dr Collins, who is the senior author at Natural Aging paper, led the team that discovered the first antibiotics identified by machine learning in 2020.

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About Integrated Biosciences

Integrated Biosciences is an early-stage biotechnology company that has developed a proprietary synthetic biology and AI platform to target age-related cellular stress responses. Integrated Biosciences was founded by MIT, Harvard, and Princeton-trained scientists Felix Wong, Ph.D., and Max Wilson, Ph.D., in 2022. Its scientific advisors include James J. Collins, Ph.D., one of the founder of the field of synthetic biology and Termeer Professor of Medical Engineering and Science at MIT, and Sir David WC MacMillan Ph.D., 2021 Nobel Prize winner in Chemistry and James S. McDonnell Distinguished University Professor of Chemistry at Princeton. Its investors include Root Ventures, Mission BioCapital, Conscience VC, Reinforced Ventures and Polymath Capital. Integrated Biosciences based in San Carlos, California.