AI-Based D-Amino Acid Substitution for Optimizing Antimicrobial Peptides to Treat Multidrug-Resistant Bacterial Infection.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Published Date: Jan 14, 2026

Abstract

D-amino acid substitution provides an effective strategy for optimizing antimicrobial peptides (AMPs) by enhancing their stability. However, the absence of universal rules renders traditional screening methods time-consuming and labor-intensive, potentially leading to reduced or complete loss of activity. Here, we curated a D-amino acid-substituted AMP dataset from published literature and databases. We then developed ADAPT, an AI-based tool for predicting the functional impact of D-amino acid substitutions, and integrated it into a high-throughput screening pipeline for AMP optimization. Of the variants obtained through this pipeline, 80% exhibited enhanced antibacterial activity. Among these, dR2-1 showed exceptional broad-spectrum antimicrobial activity, reduced toxicity, and substantially improved stability. Mechanistic studies confirmed a membrane-targeting antibacterial mode of action. Furthermore, we engineered a hydrogel delivery system that effectively treated cutaneous infections in mice. Overall, our study established an AI-based framework for D-amino acid substitution in AMPs, enabling the efficient discovery of potent and stable candidates with enhanced clinical translation potential.

Authors

  • Yinuo Zhao
    Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Qingzhou Kong
    Department of Gastroenterology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Haifan Gong
    Shanghai Artificial Intelligence Laboratory, Yunjing Road 701, Shanghai, China.
  • Lixiang Li
    Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Jialu Fu
    Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Boyao Wan
    Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Peizhu Wang
    Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Xiaojuan Li
    Program of Advanced Musculoskeletal Imaging (PAMI), Cleveland Clinic, Cleveland, Ohio, USA.
  • Yue Wang
    Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
  • Jinghui Zhang
    State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China.
  • Yanbo Yu
    Department of Gastroenterology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Xiaoyun Yang
    Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiuli Zuo
    Department of Gastroenterology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
  • Haina Wang
    School of Pharmaceutical Sciences, Shandong University, Jinan, China.
  • Yanqing Li
    Department of Gastroenterology, Qilu Hospital of Shandong University, Jinan, Shandong, China.

Keywords

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