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.