Integrated Bioinformatics Approach to Metabolite Detection from Metagenomic Data v1

The exploration of metabolites derived from metagenomic data holds immense potential for the discovery of novel bioactive compounds with applications in pharmaceuticals, agriculture, and biotechnology. However, the complex nature of metagenomic datasets, coupled with the biochemical diversity and the presence of unknown enzymes, poses significant challenges to identifying metabolites accurately. This study presents the development of a comprehensive protocol designed to streamline the identification of metabolites from metagenome data. The protocol integrates advanced bioinformatics tools and databases, including antiSMASH for identifying biosynthetic gene clusters (BGCs). This study involves the identification of metabolites from bacterial species which can be potential Biofertilizers. But the pipeline can be used in general for the metabolite identification for any case study.