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 language | English (US) |
|---|---|
| Pages (from-to) | 223-227 |
| Number of pages | 5 |
| Journal | ChemBioChem |
| Volume | 16 |
| Issue number | 2 |
| DOIs | |
| State | Published - Dec 8 2015 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Biochemistry
- Molecular Medicine
- Molecular Biology
- Organic Chemistry
Keywords
- Bioinformatics
- Chemoinformatics
- Depsipeptides
- Mass spectrometry
- Natural products