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J Ind Microbiol Biotechnol. 2016 Mar;43(2-3):293-8. doi: 10.1007/s10295-015-1675-9. Epub 2015 Sep 8.

Informatic search strategies to discover analogues and variants of natural product archetypes.

Author information

1
Department of Biochemistry and Biomedical Sciences, The Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, L8N 3Z5, Canada.
2
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON, L8N 3Z5, Canada.
3
Department of Chemistry, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, C1A 4P3, Canada.
4
Department of Biomedical Sciences, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, PEI, C1A 4P3, Canada.
5
Department of Biochemistry and Biomedical Sciences, The Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, L8N 3Z5, Canada. magarv@mcmaster.ca.
6
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON, L8N 3Z5, Canada. magarv@mcmaster.ca.

Abstract

Natural products are a crucial source of antimicrobial agents, but reliance on low-resolution bioactivity-guided approaches has led to diminishing interest in discovery programmes. Here, we demonstrate that two in-house automated informatic platforms can be used to target classes of biologically active natural products, specifically, peptaibols. We demonstrate that mass spectrometry-based informatic approaches can be used to detect natural products with high sensitivity, identifying desired agents present in complex microbial extracts. Using our specialised software packages, we could elaborate specific branches of chemical space, uncovering new variants of trichopolyn and demonstrating a way forward in mining natural products as a valuable source of potential pharmaceutical agents.

KEYWORDS:

Informatic platforms; LC–MS/MS; Natural products; Nonribosomal peptides; Peptaibols

PMID:
26350080
DOI:
10.1007/s10295-015-1675-9
[Indexed for MEDLINE]

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