Exploring secondary metabolite biosynthesis clusters in the genome of Zea mays through in silico analysis

Secondary metabolites play a crucial role in plant defense, adaptation, and potential therapeutic applications. The identification of their biosynthetic pathways is essential for discovering novel bioactive compounds. Zea mays (maize) is known for its diverse pharmacological properties, including antimicrobial, antioxidant, and anticancer activities. However, the biosynthetic gene clusters (BGCs) responsible for producing these bioactive compounds in Z. mays remain largely unexplored. In this study, we employed an in-silico genome mining approach to systematically identify and analyze BGCs in Z. mays. Using advanced bioinformatics tools such as PlantiSMASH and KNApSAck, we predicted key secondary metabolite clusters and their biosynthetic pathways. Additionally, we utilized MaizeGDB, a curated genomic database, to perform comparative genomic analyses and functional annotations of the identified clusters. Our findings highlight the potential of Z. mays as a rich source of secondary metabolites with promising applications in medicine and agriculture. This study provides new insights into the genomic organization of BGCs in Z. mays, paving the way for future research on natural product discovery.