Automated identification of depsipeptide natural products by an informatic search algorithm

Michael A. Skinnider, Chad W. Johnston, Rostyslav Zvanych, Nathan A. Magarvey

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Nonribosomal depsipeptides are a class of potent microbial natural products, which include several clinically approved pharmaceutical agents. Genome sequencing has revealed a large number of uninvestigated natural-product biosynthetic gene clusters. However, while novel informatic search methods to access these gene clusters have been developed to identify peptide natural products, depsipeptide detection has proven challenging. Herein, we present an improved version of our informatic search algorithm for natural products (iSNAP), which facilitates the detection of known and genetically predicted depsipeptides in complex microbial culture extracts. We validated this technology by identifying several depsipeptides from novel producers, and located a large number of novel depsipeptide gene clusters for future study. This approach highlights the value of chemoinformatic search methods for the discovery of genetically encoded metabolites by targeting specific areas of chemical space.

Original languageEnglish (US)
Pages (from-to)223-227
Number of pages5
JournalChemBioChem
Volume16
Issue number2
DOIs
StatePublished - Dec 8 2015
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Molecular Biology
  • Biochemistry
  • Organic Chemistry

Keywords

  • Bioinformatics
  • Chemoinformatics
  • Depsipeptides
  • Mass spectrometry
  • Natural products

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