Artificial Intelligence Discovers Potent Antibiotic

Researchers used a machine-learning platform to test more than 100 million molecules for antibacterial activity.

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Anewly designed artificial intelligence tool based on the structure of the brain has identified a molecule capable of wiping out a number of antibiotic-resistant strains of bacteria, according to a study published on February 20 in Cell. The molecule, halicin, which had previously been investigated as a potential treatment for diabetes, demonstrated activity against Mycobacterium tuberculosis, the causative agent of tuberculosis, and several other hard-to-treat microbes.

The discovery comes at a time when novel antibiotics are becoming increasingly difficult to find, reports STAT, and when drug-resistant bacteria are a growing global threat. The Interagency Coordination Group (IACG) on Antimicrobial Resistance convened by United Nations a few years ago released a report in 2019 estimating that drug-resistant diseases could result in 10 million deaths per year by 2050. Despite the urgency in the search for new antibiotics, a lack of financial incentives has caused pharmaceutical companies ...

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Meet the Author

  • Amy Schleunes

    A former intern at The Scientist, Amy studied neurobiology at Cornell University and later earned her MFA in creative writing from the University of Iowa. She is a Los Angeles–based writer, editor, and communications strategist who collaborates on nonfiction books for Harper Collins and Houghton Mifflin Harcourt, and also teaches writing at Johns Hopkins University CTY. Her favorite projects involve sharing the insights of science and medicine.

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