Nonribosomal peptides (NRPs) such as penicillin, vancomycin and related molecules isolated from microbial sources have been a staple for drug discovery for many decades. We propose to employ multi-stage mass-spectrometry (MSn) for de novo sequencing of NRPs, including cyclic NRPs. Analysis of MSn spectra of a cyclic peptide results in the difficult combinatorial problem of interpreting multiple linear peptides from the same spectrum. This proposal develops new combinatorial algorithms for solving this issue. Since the MSn based mass spectrometry analysis of NPRs is fast and inexpensive and requires minimal amounts of material (<1 5g), this approach opens a possibility of high-throughput sequencing of many unknown NRPs accumulated in large bioactivity marine cyanobacterial screening programs. In parallel to the automation of the NRPs sequencing efforts, we will harvest a set of orphan gene clusters from marine actinomycetes to generate a library of cyclic peptides. The algorithms developed in this proposal will be used to fully characterize this cyclic imine library. This work not only sets the stage for the automated characterization of NRPs but will also be applicable to the characterization of other peptidic natural products such as peptaibols, peptide derived toxins or lantibiotics.
This project describes the development and application of a novel mass spectrometry based method and corresponding algorithms that allow the de novo sequencing of complex therapeutic agents that are non-ribosomally derived.
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