Design of Specific Peptide Inhibitors of Toxin-Antitoxin-Mediated Antiphage Defense

Toxin–antitoxin (TA) systems are widespread antiphage defense elements in bacteria that may impede successful phage therapy. Phage-encoded inhibitors of these systems have been discovered that enhance phage infection capacity. We used fragment-based design with deep-learning scoring functions to design peptide inhibitors of the toxin RelE. Our peptides extend a fragment of the native RelB antitoxin and are sufficient to inhibit RelE toxicity. Successful inhibitors share a highly conserved binding mode that mimics the native antitoxin but have diverse sequences, with alternative contacts used to form the peptide–protein interface. Designed peptides show different interaction specificities toward RelE family proteins, distinct from the wild-type RelB antitoxin, and inhibit the antiphage defense activity of multiple orthologous RelBE systems. This work showcases the use of structure-based computational design to generate peptide binders that serve as potential counter-defense elements.