AI helps find potential antibiotics in snake and spider venom

By Stephen Beech

Hundreds of potential antibiotics have been discovered in snake and spider venom, thanks to AI.

A screening of global venom libraries, powered by artificial intelligence, uncovered dozens of "promising" new drug candidates.

Snake, scorpion, and spider venom are usually associated with poisonous bites.

But with the help of AI, scientists say they might be able to help fight antibiotic resistance, which contributes to more than one million deaths worldwide every year.

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

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

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Study senior author Professor César de la Fuente said: “Venoms are evolutionary masterpieces, yet their antimicrobial potential has barely been explored.

“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 synthesised 58 venom peptides for lab testing.

The findings, published in the journal Nature Communications, showed that 53 killed drug-resistant bacteria, including E.coli and Staphylococcus aureus, at doses that were harmless to human red blood cells.

Co-author Dr. Marcelo Torres said: “By pairing computational triage with traditional lab experimentation, we delivered one of the most comprehensive investigations of venom-derived antibiotics to date.”

Co-author Dr. Changge Guan noted that the platform mapped more than 2,000 entirely new antibacterial "motifs" - short, specific sequences of amino acids within a protein or peptide responsible for their ability to kill or inhibit bacterial growth.

The team is now taking the top peptide candidates, which could lead to new antibiotics, and improving them through medicinal chemistry tweaks.