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| Main Authors: | , |
|---|---|
| Format: | Artículo científico |
| Language: | en |
| Published: |
Engineering microbiology
2025
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| Online Access: | https://pubmed.ncbi.nlm.nih.gov/41982661/ |
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Table of Contents:
- Archaeasins as a promising resource for developing next-generation antibiotics uncovered via deep learning. Du, Huan Liu, Yang Fighting against antibiotic resistance has an unexpected ally, archaea. Despite the extensive exploration of antimicrobial peptides in bacteria and eukaryotes, the archaeal domain has been overlooked. A recent study employed deep learning to screen archaeasins. The synthesized versions showed a 93 % success rate against pathogens by depolarizing the cytoplasmic membrane, not the outer membrane. This highlights the promise and deep learning power of archaea for antibiotic discovery and the culture of uncultured archaea.