Computational design of antimicrobial peptide nanopores

doi:10.1038/s41589-026-02269-z

Computational design of antimicrobial peptide nanopores

2026-08-03

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AI

Gabriela Balíková Novotná

César de la Fuente‐Núñez

R

Robert Vácha *

DOI：10.1038/s41589-026-02269-z

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Antibiotic resistance is a global health threat, driving the need for new molecules that kill bacteria via nontraditional mechanisms. Here, we present a computational de novo design strategy for α-helical peptides that self-assemble into large, stable and membrane-spanning nanopores with antimicrobial activity, including in vivo efficacy against drug-resistant pathogens. Molecular dynamics simulations guided the selection of sequences for transmembrane barrel-stave pore formation, which were validated by microscopy, electrophysiology and fluorescence assays. Using computational and experimental analyses, including negative design controls, we developed general design guidelines and 52 modular sequence templates with tunable antimicrobial, pore-forming properties. Mechanistic studies confirmed bacterial cytoplasmic membrane disruption via designed nanopore formation. A tuned lead peptide selectively killed drug-resistant ESKAPEE bacteria, including Acinetobacter baumannii, without harming human cells, and showed anti-infective efficacy in preclinical mouse infection models. The framework presented here enables the design of synthetic peptide nanopores for precision antimicrobials, anticancer agents, molecular sensors and delivery systems. A computational de novo design framework enables the design of α-helical peptides that assemble into transmembrane barrel-stave pores (TBPs). Here, TBPs are designed for antimicrobial activity, with broader potential applications in nanopore sensing and drug delivery.

Computational design of antimicrobial peptide nanopores

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