Identification of Antibacterial Cyclic Peptides with a High-Throughput Cell-Based Dropout Screen

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.