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In silico detection tools to identify fungal secondary metabolites and their biosynthetic gene clusters

J. Lakhani,A. Khunteta,Anupama Chowdhary,D. Harwani

Published 2020 in Unknown venue

ABSTRACT

Abstract Secondary metabolites are natural products produced by plants, fungi, and bacteria. After their discovery and due to the revolution in the pharmaceutical industry, secondary metabolites such as penicillin, streptomycin, and cyclosporine were manufactured in bulk for human welfare. The secondary metabolites are synthesized by the specialized enzymes encoded by coregulated genes located on the biosynthetic gene clusters (BGCs). There are two methods to identify fungal secondary metabolites and their corresponding BGCs: manual methods or in silico methods. The manual methods are time-consuming and complex; conversely, in silico tools are relatively simple, and promising. Most of the in silico tools identify previously known biosynthetic gene clusters by matching the gene sequences to the already available secondary metabolites gene data sets. Some of the in silico tools such as SMURF, ClusterFinder, and Grape can identify known and unknown biosynthetic gene clusters in the submitted genome. Due to the availability of several online tools, it is crucial to know the key functions of each tool to solve a research problem. Therefore, in this chapter, a comprehensive survey of currently available in silico tools has been made that can identify biosynthetic gene clusters in various fungal genomes. The key functions of in silico tools, namely SMURF, antiSMASH, PRISM, SMIPS, SeMPI, DEREPLICATOR   +, CASSIS, MIDDAS-M, NP.searcher, ClustScan, CLUSEAN, FunGeneClusterS, ClusterFinder, EvoMining, MIPS-CG, Pep2Path, GRAPE, GARLIC, NRPSpredictor, and SMBP, are discussed, along with the official uniform resource locator (URL) for each tool. Schematic workflow for the identification of the biosynthetic gene cluster has also been proposed, which is further extended as a decision chart in this review.

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