AI finds hundreds of potential antibiotics in snake and spider venom

Snake, scorpion, and spider venom are most frequently associated with poisonous bites, but with the help of artificial intelligence, they might be able to help fight antibiotic resistance, which contributes to more than one million deaths worldwide each year.

Researchers at the University of Pennsylvania used a deep-learning system called APEX to sift through a database of more than 40 million venom encrypted peptides (VEPs), tiny proteins evolved by animals for attack or as a defense mechanism.

In a matter of hours, the algorithm flagged 386 compounds with the molecular hallmarks of next-generation antibiotics.

"Venoms are evolutionary masterpieces, yet their antimicrobial potential has barely been explored," said senior author César de la Fuente, Ph.D., a Presidential Associate Professor of Psychiatry, Microbiology, Bioengineering, Chemical and Biomolecular Engineering, and Chemistry. "APEX lets us scan an immense chemical space in just hours and identify peptides with exceptional potential to fight the world's most stubborn pathogens."

From the AI-selected shortlist, the team synthesized 58 venom peptides for laboratory testing. 53 killed drug-resistant bacteria – including Escherichia coli and Staphylococcus aureus – at doses that were harmless to human red blood cells.

Image source: Ludivine Lamare, Wikimedia Commons, CC BY-SA 4.0.

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