Original story from McMaster University (Canada). A new AI model, called SyntheMol-RL, can generate structurally novel antibiotic candidates that are easy to develop in the lab and likely to be soluble in the body. Researchers at McMaster University (Canada) have developed a new generative artificial intelligence (AI) model capable of drastically speeding up drug discovery – and, in early tests, it has already designed a brand-new antibiotic. The discovery is a demonstration of how AI could dramatically improve the slow and costly search for new antimicrobial medicines, as bacteria and other microbes continue to evolve resistance to our current suite of drugs. The new model, called SyntheMol-RL, is trained to explore a vast chemical space of up to 46 billion possible compounds – far beyond what could realistically be tested in the lab, where even large-scale screens top out at around a million molecules. Drawing on roughly 150,000 molecular ‘building blocks’ and a set of 50 chemical synthesis reactions, the AI model is designed to generate structurally novel antibiotic candidates. “In the lab, we can build chemical compounds using a set of smaller chemical fragments, which can be stuck together like molecular Lego blocks,” shared Assistant Professor Jon Stokes, whose laboratory developed the new model. “SyntheMol-RL configures those fragments in different ways, faster than humans ever could, to create new, larger chemical compounds that should – based on its knowledge – be antibacterial.” Stokes, a member of the Michael G. DeGroote Institute for Infectious Disease Research, explained that while generative AI is…
