<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Ghose DA</submitter><funding>Howard Hughes Medical Institute</funding><funding>NIGMS NIH HHS</funding><pagination>4496-4507</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12739935</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>14(11)</volume><pubmed_abstract>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 defe</pubmed_abstract><journal>ACS synthetic biology</journal><pubmed_title>Design of Specific Peptide Inhibitors of Toxin-Antitoxin-Mediated Antiphage Defense.</pubmed_title><pmcid>PMC12739935</pmcid><funding_grant_id>R35 GM149227</funding_grant_id><pubmed_authors>Swanson SR</pubmed_authors><pubmed_authors>Ghose DA</pubmed_authors><pubmed_authors>Laub MT</pubmed_authors><pubmed_authors>Birnbaum F</pubmed_authors><pubmed_authors>Keating AE</pubmed_authors><pubmed_authors>Britton D</pubmed_authors><pubmed_authors>Gan JL</pubmed_authors><pubmed_authors>Mahoney EM</pubmed_authors></additional><is_claimable>false</is_claimable><name>Design of Specific Peptide Inhibitors of Toxin-Antitoxin-Mediated Antiphage Defense.</name><description>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 defe</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Nov</publication><modification>2026-06-06T05:56:05.226Z</modification><creation>2026-05-27T03:11:53.059Z</creation></dates><accession>S-EPMC12739935</accession><cross_references><pubmed>41139285</pubmed><doi>10.1021/acssynbio.5c00498</doi></cross_references></HashMap>