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However, efficient generation of diverse AMPs without prior knowledge of peptide structures or sequence alignments remains a challenge. Here, ProT\u2010Diff is introduced, a modularized deep generative approach that combines a pretrained protein language model with a diffusion model for the de novo generation of AMPs sequences. ProT\u2010Diff generates thousands of AMPs with diverse lengths and structures within a few hours. After silico physicochemical screening, 45 peptides are selected for experimental validation. Forty\u2010four peptides showed antimicrobial activity against both gram\u2010positive or gram\u2010negative bacteria. Among broad\u2010spectrum peptides, AMP_2 exhibited potent antimicrobial activity, low hemolysis, and minimal cytotoxicity. An in vivo assessment demonstrated its effectiveness against a drug\u2010resistant\n                    <jats:italic>E. coli<\/jats:italic>\n                    strain in acute peritonitis. This study not only introduces a viable and user\u2010friendly strategy for de novo generation of antimicrobial peptides, but also provides potential antimicrobial drug candidates with excellent activity. It is believed that this study will facilitate the development of other peptide\u2010based drug candidates in the future, as well as proteins with tailored characteristics.\n                  <\/jats:p>","DOI":"10.1002\/advs.202406305","type":"journal-article","created":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T11:19:08Z","timestamp":1727263148000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["ProT\u2010Diff: A Modularized and Efficient Strategy for De Novo Generation of Antimicrobial Peptide Sequences by Integrating Protein Language and Diffusion Models"],"prefix":"10.1002","volume":"11","author":[{"given":"Xue\u2010Fei","family":"Wang","sequence":"first","affiliation":[{"name":"Precision Scientific (Beijing) Co. Ltd.  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