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Nat Chem Biol. 2017 Jan;13(1):30-37. doi: 10.1038/nchembio.2219. Epub 2016 Oct 31.

Dereplication of peptidic natural products through database search of mass spectra.

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Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California, USA.
Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA.
Laboratory of Aquatic Natural Products Chemistry, School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.
Department of Pharmacology, University of California, San Diego, La Jolla, California, USA.


Peptidic natural products (PNPs) are widely used compounds that include many antibiotics and a variety of other bioactive peptides. Although recent breakthroughs in PNP discovery raised the challenge of developing new algorithms for their analysis, identification of PNPs via database search of tandem mass spectra remains an open problem. To address this problem, natural product researchers use dereplication strategies that identify known PNPs and lead to the discovery of new ones, even in cases when the reference spectra are not present in existing spectral libraries. DEREPLICATOR is a new dereplication algorithm that enables high-throughput PNP identification and that is compatible with large-scale mass-spectrometry-based screening platforms for natural product discovery. After searching nearly one hundred million tandem mass spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure, DEREPLICATOR identified an order of magnitude more PNPs (and their new variants) than any previous dereplication efforts.

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