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.
“What this paper demonstrates is that for health care, AI developments are more than the sum of their parts,” said Aspuru-Guzik, a professor of chemistry and computer science in U of T’s Faculty of Arts & Science and the Canada 150 Research Chair in Theoretical and Quantum Chemistry. “If one uses a generative model targeting an AI-derived protein, one can substantially expand the range of diseases that we can target. If one adds self-driving labs to the mix, we will be in uncharted territory. Stay tuned!”
(Photo courtesy of Insilico Medicine)