<p dir="ltr">Cyclic peptides are a growing drug class with over 40 FDA-approved drugs, with natural product cyclic peptides being the inspiration for many of these medicines (e.g., the antibiotic daptomycin, the immunosuppressant cyclosporine A, and the antifungal caspofungin). Two major types of cyclic peptide natural products exist: (1) the ribosomally synthesized and post-translationally modified peptides (RiPPs) and (2) those made by nonribosomal peptide synthetases (NRPSs). Even though many uncharacterized cyclic peptide biosynthetic gene clusters (BGCs) exist, the discovery of new cyclic peptide natural products remains a challenge because many BGCs are cryptic. Herein, we describe the development of a new approach to access the products of these cryptic NRPS BGCs and the discovery of many novel bioactive compounds from this approach. Specifically, we utilized bioinformatics programs to predict the amino acid sequences associated with the multimodular NRPS and the presence of a nearby penicillin-binding protein (PBP)-like thioesterase (TE, PBP-TE) to determine that the predicted peptides are head-to-tail cyclized. Following the bioinformatics-guided predictions, solid phase peptide synthesis (SPPS) followed by solution phase cyclization enabled access to a library of predicted cyclic peptides that we then screened for interesting bioactivities. From this screening, we have identified molecules that stimulate the proteasome, inhibit the growth of free-living amoebas, selectively lyse Gram-negative bacteria, and suppress the immune system. Structure activity relationships for these molecules have been determined, with more potent analogs being discovered. Future directions include mechanism of action studies, as well as expanding the peptide library to include more off-loading methods and tailoring enzymes that might modify the peptide after release from the NRPS.</p>