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Chem Biol. 2015 Sep 17;22(9):1259-69. doi: 10.1016/j.chembiol.2015.08.008. Epub 2015 Sep 10.

Exploration of Nonribosomal Peptide Families with an Automated Informatic Search Algorithm.

Author information

1
The David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
2
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON L8N 3Z5, Canada.
3
The Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada.
4
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON L8N 3Z5, Canada; The Michael G. DeGroote Institute for Infectious Disease Research, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8N 3Z5, Canada. Electronic address: magarv@mcmaster.ca.

Abstract

Microbial natural products are some of the most important pharmaceutical agents and possess unparalleled chemical diversity. Here we present an untargeted metabolomics algorithm that builds on our validated iSNAP platform to rapidly identify families of peptide natural products. By utilizing known or in silico-dereplicated seed structures, this algorithm screens tandem mass spectrometry data to elaborate extensive molecular families within crude microbial culture extracts with high confidence and statistical significance. Analysis of peptide natural product producers revealed an abundance of unreported congeners, revealing one of the largest families of natural products described to date, as well as a novel variant with greater potency. These findings demonstrate the effectiveness of the iSNAP platform as an accurate tool for rapidly profiling large families of nonribosomal peptides.

PMID:
26364933
DOI:
10.1016/j.chembiol.2015.08.008
[Indexed for MEDLINE]
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