A team of scientists at the Massachusetts Institute of Technology (MIT) used generative AI to invent two new potential antibiotics that could kill drug-resistant gonorrhoea and MRSA (Staphylococcus aureus).
The researchers used generative AI algorithms to design over 36 million possible compounds and computationally screened them for antimicrobial traits. The top candidates appeared to be structurally distinct from existing antibiotics and seem to function by novel mechanisms that disrupt bacterial cell membranes.
In their study, published in Cell, the group employed two different approaches. First, they directed generative AI algorithms to design molecules based on a specific chemical fragment that showed antimicrobial activity. Second, they let the algorithms freely generate molecules, without having to include a particular fragment.
The candidate pool was also narrowed down by removing any fragments predicted to be cytotoxic to human cells and that were known to be similar to existing antibiotics. Aarti Krishnan, an MIT postdoc and a lead of the study, said: “We wanted to get rid of anything that would look like an existing antibiotic, to help address the antimicrobial resistance crisis in a fundamentally different way.”
He continued, “By venturing into underexplored areas of chemical space, our goal was to uncover novel mechanisms of action.”
The method enabled researchers to generate and evaluate theoretical compounds that have never been observed before. Now, they hope that they can apply this strategy to identify and design compounds with activity against other species of bacteria.
James Collins, Professor of Medical Engineering and Science at MIT, stated: “AI can enable us to come up with molecules, cheaply and quickly, and in this way, expand our arsenal, and really give us a leg up in the battle of our wits against the genes of superbugs.”
