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Methods Mol Biol. 2012;944:23-45. doi: 10.1007/978-1-62703-122-6_2.

Bioinformatics approaches and software for detection of secondary metabolic gene clusters.

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1
The J. Craig Venter Institute, Rockville, MD, USA. natalief@jcvi.org

Abstract

The accelerating pace of microbial genomics is sparking a renaissance in the field of natural products research. Researchers can now get a preview of the organism's secondary metabolome by analyzing its genomic sequence. Combined with other -omics data, this approach may provide a cost-effective alternative to industrial high-throughput screening in drug discovery. In the last few years, several computational tools have been developed to facilitate this process by identifying genes involved in secondary metabolite biosynthesis in bacterial and fungal genomes. Here, we review seven software programs that are available for this purpose, with an emphasis on antibiotics & Secondary Metabolite Analysis SHell (antiSMASH) and Secondary Metabolite Unknown Regions Finder (SMURF), the only tools that can comprehensively detect complete secondary metabolite biosynthesis gene clusters. We also discuss five related software packages-CLUster SEquence ANalyzer (CLUSEAN), ClustScan, Structure Based Sequence Analysis of Polyketide Synthases (SBSPKS), NRPSPredictor, and Natural Product searcher (NP.searcher)-that identify secondary metabolite backbone biosynthesis genes. This chapter offers detailed protocols, suggestions, and caveats to assist researchers in using these tools most effectively.

PMID:
23065606
DOI:
10.1007/978-1-62703-122-6_2
[Indexed for MEDLINE]
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