In less than a month, researchers have used AlphaFold, an artificial intelligence (AI)-powered protein structure database, to design and synthesize a potential drug to treat hepatocellular carcinoma (HCC), the most common type of primary liver cancer. The researchers successfully applied AlphaFold to an end-to-end AI-powered drug discovery platform called Pharma.AI. That included a biocomputational engine, PandaOmics, and a generative chemistry engine, Chemistry42. They discovered a novel target for HCC – a previously undiscovered treatment pathway – and developed a “novel hit molecule” that could bind to that target without the aid of an experimentally determined structure. The feat was accomplished in just 30 days from target selection and after only synthesizing seven compounds.

In a second round of AI-powered compound generation, researchers discovered a more potent hit molecule – although any potential drug would still need to undergo clinical trials. The study – published in Chemical Science – is led by the University of Toronto Acceleration Consortium Director Alán Aspuru-Guzik, Nobel laureate Michael Levitt and Insilico Medicine founder and CEO Alex Zhavoronkov.

“While the world was fascinated with advances in generative AI in art and language, our generative AI algorithms managed to design potent inhibitors of a target with an AlphaFold-derived structure,” Zhavoronkov said. “AlphaFold broke new scientific ground in predicting the structure of all proteins in the human body,” added co-author Feng Ren, chief scientific officer and co-CEO of Insilico Medicine. “At Insilico Medicine, we saw that as an incredible opportunity to take these structures and apply them to our end-to-end AI platform in order to generate novel therapeutics to tackle diseases with high unmet need. This paper is an important first step in that direction.”

Source: https://www.utoronto.ca/
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