Genome sequencing provides potential strategies for drug discovery and synthesis

Abstract

Medicinal plants are renowned for their abundant production of secondary metabolites, which exhibit notable pharmacological activities and great potential for drug development. The biosynthesis of secondary metabolites is highly intricate and influenced by various intrinsic and extrinsic factors, resulting in substantial species diversity and content variation. Consequently, precise regulation of secondary metabolite synthesis is of utmost importance. In recent years, genome sequencing has emerged as a valuable tool for investigating the synthesis and regulation of secondary metabolites in medicinal plants, facilitated by the widespread use of high-throughput sequencing technologies. This review highlights the latest advancements in genome sequencing within this field and presents several strategies for studying secondary metabolites. Specifically, the article elucidates how genome sequencing can unravel the pathways for secondary-metabolite synthesis in medicinal plants, offering insights into the functions and regulatory mechanisms of participating enzymes. Comparative analyses of plant genomes allow identification of shared pathways of metabolite synthesis among species, thereby providing novel avenues for obtaining cost-effective biosynthetic intermediates. By examining individual genomic variations, genes or gene clusters associated with the synthesis of specific compounds can be discovered, indicating potential targets and directions for drug development and the exploration of alternative compound sources. Moreover, the advent of gene-editing technology has enabled the precise modifications of medicinal plant genomes. Optimization of specific secondary metabolite synthesis pathways becomes thus feasible, enabling the precise editing of target genes to regulate secondary metabolite production within cells. These findings serve as valuable references and lessons for future drug development endeavors, conservation of rare resources, and the exploration of new resources.

Decoding cardiovascular risks: analyzing type 2 diabetes mellitus and ASCVD gene expression

“…In recent years, the explosion of genomic data availability has elevated bioinformatics analysis methods to indispensable tools in scientific research ( 8 , 9 ). Bioinformatics analysis plays a pivotal role in deciphering this wealth of information, enabling the identification of Differentially Expressed Genes (DEGs), conducting intricate Gene Ontology (GO) analyses, and performing insightful pathway analyses ( 10 ).…”