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Antimicrobial peptides (AMPs) show promise solutions due to their multiple mechanisms of action and reduced propensity for resistance development. This study introduces LLAMP (Large Language model for AMP activity prediction), a target species-aware AI model that leverages pre-trained language models to predict minimum inhibitory concentration values of AMPs. Using LLAMP, we screened approximately 5.5 million peptide sequences, identifying peptides 13 and 16 as the most selective and most potent candidates, respectively. Analysis of attention values allowed us to pinpoint critical amino acid residues (e.g., Trp, Lys, and Phe). Using the critical amino acids, the sequence of the most selective peptide 13 was engineered to increase amphipathicity through targeted modifications, yielding peptide 13\u20135 with an overall enhancement in antimicrobial activity but a reduction in selectively. Notably, peptides 13\u20135 and 16 demonstrated antimicrobial potency and selectivity comparable to the clinically investigated AMP pexiganan. Our work demonstrates the potential of AI to expedite the discovery of peptide-based antibiotics to combat antibiotic resistance.<\/jats:p>","DOI":"10.1093\/bib\/bbaf343","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T05:36:51Z","timestamp":1752817011000},"source":"Crossref","is-referenced-by-count":12,"title":["AI-guided discovery and optimization of antimicrobial peptides through species-aware language model"],"prefix":"10.1093","volume":"26","author":[{"given":"Daehun","family":"Bae","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST) , Buk-gu, Gwangju 61005 ,","place":["Republic of Korea"]}]},{"given":"Minsang","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Chemistry, Gwangju Institute of Science and Technology (GIST) , Buk-gu, Gwangju 61005 ,","place":["Republic of Korea"]}]},{"given":"Jiwon","family":"Seo","sequence":"additional","affiliation":[{"name":"Department of Chemistry, Gwangju Institute of Science and Technology (GIST) , Buk-gu, Gwangju 61005 ,","place":["Republic of Korea"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5109-9114","authenticated-orcid":false,"given":"Hojung","family":"Nam","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST) , Buk-gu, Gwangju 61005 ,","place":["Republic of Korea"]},{"name":"AI Graduate School, Gwangju Institute of Science and Technology (GIST) , Buk-gu, Gwangju 61005 ,","place":["Republic of Korea"]}]}],"member":"286","published-online":{"date-parts":[[2025,7,18]]},"reference":[{"key":"2025071801364671100_ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature.2014.15135","article-title":"WHO warns against \u2018post-antibiotic\u2019 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