One-Step Design of Potent and Nonhemolytic Antimicrobial Peptides by Using a Database-Guided, Nonmachine Learning Approach.

ABSTRACT: The search for antibiotics is urgent because of the global antibiotic resistance problem. While a variety of strategies are actively sought, interest in antimicrobial peptides persists due to high potency and low chance of resistance development. The establishment of the antimicrobial peptide database laid the foundation for peptide prediction and design. Both artificial intelligence and non-AI approaches have been demonstrated. Since AI remains a black box and does not teach us how to design peptide antibiotics, this study took a database-guided approach. Our peptide design benefited from the recent classification of peptides into hemolytic and nonhemolytic groups in the APD6. Our designed peptides rapidly killed Gram-negative bacteria Escherichia coli and Acinetobacter baumanni

SUBMITTER: Mechesso AF 

PROVIDER: S-EPMC12927767 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature