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Antimicrobials

Explainable artificial intelligence evolves antimicrobial peptides

Nature Microbiology volume 10, pages 267–269 (2025)Cite this article

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An explainable deep learning model enables the identification and virtual optimization of antimicrobial peptides (AMPs) from the oral microbiome, yielding novel AMPs with activity against ESKAPE pathogens and demonstrating efficacy in a mouse wound infection model.

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Fig. 1: Identification and optimization of AMPs found in the oral microbiome.

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Author notes

  1. These authors contributed equally: Jeremie Alexander, Gary Liu.

Authors and Affiliations

  1. Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada

    Jeremie Alexander, Gary Liu & Jonathan M. Stokes

  2. Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada

    Jeremie Alexander, Gary Liu & Jonathan M. Stokes

  3. David Braley Centre for Antibiotic Discovery, McMaster University, Hamilton, Ontario, Canada

    Jeremie Alexander, Gary Liu & Jonathan M. Stokes

Authors
  1. Jeremie Alexander
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  2. Gary Liu
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  3. Jonathan M. Stokes
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Corresponding author

Correspondence to Jonathan M. Stokes.

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Competing interests

J.M.S. is a founder of Stoked Bio. The other authors declare no competing interests.

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Alexander, J., Liu, G. & Stokes, J.M. Explainable artificial intelligence evolves antimicrobial peptides. Nat Microbiol 10, 267–269 (2025). https://doi.org/10.1038/s41564-024-01919-z

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