AI uncovers antimicrobial fragments hidden in prions
TL;DR Summary
Researchers used APEX 1.1 to mine 19.3 million fragments from 2,897 prion-related proteins, identifying 1,179 prionins predicted to be antimicrobial (median MIC ≤ 64 μM). Out of 75 synthesized, 59 inhibited at least one pathogen and 42 achieved MIC ≤16 μM, mainly against Gram-negative bacteria, often via membrane disruption as shown by NPN and DiSC3-5 assays. In vivo, two lead prionins reduced bacterial burden in a mouse Acinetobacter baumannii skin infection model with favorable selectivity. The study suggests prion-related proteins are a rich source of cryptic AMP leads, though physiological roles remain unproven.
Topics:health#antibiotic-discovery#antimicrobial-peptides#deep-learning#prion-related-proteins#prionins#science
- Deep learning reveals antimicrobial peptides within prions Nature
- AI tool could speed antibiotic development National Institutes of Health (.gov)
- AI Reveals Unexpected Source of Antibiotic Candidates in Prion Proteins | Newswise Newswise
- Penn researchers develop predictive AI model for antibiotic discovery The Daily Pennsylvanian
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