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  3. AI agent-based discovery of D-enantiomeric antimicrobial peptides against multidrug-resistant bacterial infection

AI agent-based discovery of D-enantiomeric antimicrobial peptides against multidrug-resistant bacterial infection

  • Biomaterials. 2025 Dec 22:329:123927. doi: 10.1016/j.biomaterials.2025.123927.
Qingzhou Kong 1,  Yinuo Zhao 1,  Haifan Gong 2,  Luoyao Kang 3,  Jialu Fu 1,  Lixiang Li 4,  Boyao Wan 1,  Peizhu Wang 1,  Xiaojuan Li 1,  Yue Wang 1,  Jinghui Zhang 1,  Yanbo Yu 4,  Xiaoyun Yang 4,  Xiuli Zuo 4,  Haina Wang 5,  Yanqing Li 6
Affiliations

Affiliations

  • 1 Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • 2 Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China; The Chinese University of Hong Kong, Shenzhen, China.
  • 3 Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China; The Chinese University of Hong Kong, Hong Kong, China.
  • 4 Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China; Shandong Provincial Microecological Research and Biotherapy Center, Jinan, China; Shandong Provincial Clinical Research Center for Digestive Disease, Jinan, China.
  • 5 School of Pharmaceutical Sciences, Shandong University, Jinan, China. Electronic address: [email protected].
  • 6 Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China; Shandong Provincial Microecological Research and Biotherapy Center, Jinan, China; Shandong Provincial Clinical Research Center for Digestive Disease, Jinan, China. Electronic address: [email protected].
PMID: 41443039 DOI: 10.1016/j.biomaterials.2025.123927
Abstract

Antimicrobial peptides (AMPs) offer a route to counter resistant pathogens but are often hampered by proteolysis, whereas D-peptides resist proteases yet remain underexplored due to data scarcity and design challenges. Here, we present PeptiD-Agent, a purely agent based framework that predicts D-peptide antimicrobial activity with extremely limited data, enabling rapid discovery of potent candidates. Using this approach, we identified DA2, a D-enantiometric AMP lead with broad-spectrum activity against drug-resistant bacteria and minimal hemolytic toxicity. DA2 showed high stability under physiological conditions, including resistance to enzymatic degradation and serum. Mechanistic studies indicate that DA2 exerts bactericidal effects by disrupting the integrity of the Bacterial membrane in concert with multiple synergistic mechanisms. In murine models of skin wounds and intraperitoneal Infection, DA2 conferred significant protection against drug-resistant pathogens and, when delivered via hydrogel, accelerated wound healing. These findings establish a computational route to potent, stable D-peptide antimicrobials and provide a general strategy for AMP design in data-scarce settings.

Keywords

AI agent; Antimicrobial peptide; Antimicrobial resistance; D-enantiomeric peptide.

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