2024 Vol. 30 No.1 PP 163-166
https://doi.org/10.33451/florafauna.v30i1pp163-166
Identification of biosynthetic gene clusters using bioinformatic tools
Shantirani Thokchom1, *Saikat Mukherjee1, Debananda S Ningthoujam1 and Sumita Banerjee2
1Department of Biochemistry,
Manipur University, MANIPUR - 795003, INDIA
2Department of Oral Pathology,
Dental College, Regional Institute of Medical Sciences,
IMPHAL- 795004 (MANIPUR), INDIA.
*Corresponding Author :
E-mail:mukherjeesaikat333@gmail.com
ABSTRACT
Biosynthetic gene clusters (BGCs) are genomic regions responsible for producing natural products with diverse biological
activities. Identifying and characterizing these gene clusters is crucial for understanding the biosynthesis of secondary metabolites
and for drug discovery efforts. In recent years, bioinformatics tools have played a pivotal role in the identification, annotation, and
analysis of BGCs in microbial genomes. Tools such as antiSMASH, PRISM, and MultiGeneBlast leverage computational algorithms,
comparative genomics, and machine learning techniques have been developed to predict BGCs based on the presence of
biosynthetic enzymes and other conserved features. These tools enable the inference of chemical structures of natural products
encoded by BGCs, further enhancing our understanding of secondary metabolite biosynthesis. They have become indispensable
in the field of natural product discovery, empowering researchers to uncover novel secondary metabolites with potential therapeutic
applications.
KEY WORDS : AntiSMASH, Biosynthetic gene clusters (BGCs), Multigeneblast PRISM, Secondary metabolites,.