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<p>Antimicrobial peptides (AMPs) are a promising strategy to combat antimicrobial resistance. However, the identification of AMPs is both time-consuming and labor-intensive. Artificial intelligence (AI) provides new opportunities for AMP discovery. In this review, we summarize recent advances in AI-driven AMP discovery, focusing on four strategies: AMP prediction, AMP generation, AMP mining, and AMP optimization. In addition, we summarize the structure, functions, and translational applications of AMPs. Finally, we discuss the remaining challenges in AI-driven AMP discovery and outline potential directions for future research.</p> Graphical Abstract <p></p>

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Artificial Intelligence-Driven Antimicrobial Peptide Discovery: Prediction, Generation, Mining and Optimization

  • 期刊论文

  • 发表日期：

    2026年4月22日

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  • Ji Lv,
  • Guixia Liu,
  • Xiangrun Zhou,
  • Yue Chen

摘要

Antimicrobial peptides (AMPs) are a promising strategy to combat antimicrobial resistance. However, the identification of AMPs is both time-consuming and labor-intensive. Artificial intelligence (AI) provides new opportunities for AMP discovery. In this review, we summarize recent advances in AI-driven AMP discovery, focusing on four strategies: AMP prediction, AMP generation, AMP mining, and AMP optimization. In addition, we summarize the structure, functions, and translational applications of AMPs. Finally, we discuss the remaining challenges in AI-driven AMP discovery and outline potential directions for future research.

Graphical Abstract