ArticleJournal of the American Chemical Society2026
Identification of Antibacterial Cyclic Peptides with a High-Throughput Cell-Based Dropout Screen.
Article in Journal of the American Chemical Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Antimicrobial resistance is a growing global health threat, necessitating new antibiotics and discovery strategies. Here, we report a target-agnostic negative-selection screening platform that combines an intracellular library of 3.2 million cyclic peptides with next-generation sequencing to identify antibacterial cyclic peptides through the depletion of their encoding sequences. Clustering of depleted sequences by shared pharmacophores enables robust hit identification and allows focused library design. Using this approach, we identify a cyclic peptide scaffold that inhibits the previously untargeted essential iron-sulfur cluster carrier protein ErpA. This work establishes a general and scalable framework for the discovery of intracellular antibacterial targets and associated inhibitors directly in living cells.
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