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.