Massachusetts Institute of Technology (MIT) researchers have used deep learning to identify a new class of antibiotic candidates that can kill methicillin-resistant Staphylococcus aureus (MRSA).
The study represents more good news in the battle against antimicrobial resistance, as researchers from Harvard University and Roche also recently announced the discovery of a novel class of antibiotics.
The research shows that these compounds can kill methicillin-resistant Staphylococcus aureus (MRSA) grown in a lab dish and in two mouse models of MRSA infection. The compounds also show very low toxicity against human cells, making them particularly good drug candidates.
A key innovation of the new study is that the researchers were also able to figure out what kinds of information the deep-learning model was using to make its antibiotic potency predictions. This knowledge could help researchers to design additional drugs that might work even better than the ones identified by the model.
“The insight here was that we could see what was being learned by the models to make their predictions that certain molecules would make for good antibiotics. Our work provides a framework that is time-efficient, resource-efficient, and mechanistically insightful, from a chemical-structure standpoint, in ways that we haven’t had to date,” said James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering.
The study is part of the Antibiotics-AI Project at MIT, led by Collins, which aims to discover new classes of antibiotics against seven types of deadly bacteria, over seven years.
Sharing ground-breaking knowledge
The discovery has been welcomed by the AIDS Healthcare Foundation (AHF), but they have urged governments to ensure everyone benefits from ground-breaking technologies.
“News of the creation of the first new antibiotics in 60 years using AI is an extremely promising development,” said AHF Senior Global Medical Director Dr Adele Schwartz Benzaken. “These deep learning models are part of all our futures. With taxpayers funding most of the pharmaceutical innovation, we urge policymakers to ensure governments get their fair share in intellectual property rights from medical discoveries using artificial intelligence where public funds were involved.”