AI Article Synopsis
- The research focuses on creating a new framework called deepAMP to develop effective antimicrobial peptides (AMPs) to tackle the issue of antimicrobial resistance.
- DeepAMP was used to design and test 29 AMP candidates, with over 90% outperforming a known antimicrobial, showing effectiveness against both Gram-positive and Gram-negative bacteria.
- Three specific AMPs significantly reduced resistance to Staphylococcus aureus and proved effective in treating skin infections in mice, presenting a promising alternative to traditional antibiotics.
Article Abstract
Development of potent and broad-spectrum antimicrobial peptides (AMPs) could help overcome the antimicrobial resistance crisis. We develop a peptide language-based deep generative framework (deepAMP) for identifying potent, broad-spectrum AMPs. Using deepAMP to reduce antimicrobial resistance and enhance the membrane-disrupting abilities of AMPs, we identify, synthesize, and experimentally test 18 T1-AMP (Tier 1) and 11 T2-AMP (Tier 2) candidates in a two-round design and by employing cross-optimization-validation. More than 90% of the designed AMPs show a better inhibition than penetratin in both Gram-positive (i.e., S. aureus) and Gram-negative bacteria (i.e., K. pneumoniae and P. aeruginosa). T2-9 shows the strongest antibacterial activity, comparable to FDA-approved antibiotics. We show that three AMPs (T1-2, T1-5 and T2-10) significantly reduce resistance to S. aureus compared to ciprofloxacin and are effective against skin wound infection in a female wound mouse model infected with P. aeruginosa. In summary, deepAMP expedites discovery of effective, broad-spectrum AMPs against drug-resistant bacteria.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364768 | PMC |
| http://dx.doi.org/10.1038/s41467-024-51933-2 | DOI Listing |
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