May 19, 2024
Aided by machine learning, scientists find a novel antibiotic able to kill superbugs in mice
Clostridium difficile seen through an electron microscope.
Clostridium difficile seen through an electron microscope.

For decades, discovering novel antibiotics meant digging through the same patch of dirt. Biologists spent countless hours screening soil-dwelling microbes for properties known to kill harmful bacteria. But as superbugs resistant to existing antibiotics have spread widely, breakthroughs were becoming as rare as new places to dig.

Now, artificial intelligence is giving scientists a reason to dramatically expand their search into databases of molecules that look nothing like existing antibiotics.

A study published Thursday in the journal Cell describes how researchers at the Massachusetts Institute of Technology used machine learning to identify a molecule that appears capable of countering some of the world’s most formidable pathogens.

When tested in mice, the molecule, dubbed halicin, effectively treated the gastrointestinal bug Clostridium difficile (C. diff), a common killer of hospitalized patients, and another type of drug-resistant bacteria that often causes infections in the blood, urinary tract, and lungs.

The most surprising feature of the molecule? It is structurally distinct from existing antibiotics, the researchers said. It was found in a drug-repurposing database where it was initially identified as a possible treatment for diabetes, a feat that showcases the power of machine learning to support discovery efforts.

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