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Bioinspired materials

Deep learning unlocks antimicrobial self-assembling peptides

Nature Materials volume 24, pages 1168–1169 (2025)Cite this article

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A deep-learning framework identifies peptides that show antimicrobial activity against multidrug-resistant bacteria, eradicate biofilms, and treat intestinal bacterial infection in mice.

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Fig. 1: Antimicrobial self-assembling peptides are a promising tool to overcome antimicrobial resistance and biofilm-associated infections.

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Authors and Affiliations

  1. Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Xiaoqiong Xia & Cesar de la Fuente-Nunez

  2. Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA

    Xiaoqiong Xia & Cesar de la Fuente-Nunez

  3. Department of Chemistry, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA

    Xiaoqiong Xia & Cesar de la Fuente-Nunez

  4. Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA, USA

    Xiaoqiong Xia & Cesar de la Fuente-Nunez

Authors
  1. Xiaoqiong Xia
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  2. Cesar de la Fuente-Nunez
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Corresponding author

Correspondence to Cesar de la Fuente-Nunez.

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Competing interests

C.d.l.F.-N. is a co-founder of, and scientific advisor to, Peptaris, Inc., provides consulting services to Invaio Sciences, and is a member of the Scientific Advisory Boards of Nowture S.L., Peptidus, European Biotech Venture Builder, the Peptide Drug Hunting Consortium (PDHC), ePhective Therapeutics, Inc. and Phare Bio. X.X. declares no competing interests.

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Xia, X., de la Fuente-Nunez, C. Deep learning unlocks antimicrobial self-assembling peptides. Nat. Mater. 24, 1168–1169 (2025). https://doi.org/10.1038/s41563-025-02299-3

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