Microorganisms, abundant in nature, are prolific producers of a diverse array of natural products (NPs) that are fundamental in the development of innovative therapeutics. Despite their significant potential, the field faces considerable challenges, including the continuous emergence of potential health threats, as well as novel pathogen strains and viruses. The advent and implementation of advanced technologies, such as culture strategies, genomics mining, and artificial intelligence (AI), are facilitating a paradigm shift in pharmaceutical research, introducing innovative methodologies and perspectives. The development and maturation of these technologies have enhanced the exploration of microbial-derived NPs, thereby advancing pharmaceutical research and development. This review synthesizes recent developments in this context, emphasizing their applications in pharmaceutical discovery and development. Through systematic analysis and synthesis, it provides objective insights into the promising prospects and future direction of this essential field.
Biological Products/chemistry* ; Drug Discovery ; Humans ; Artificial Intelligence ; Bacteria/metabolism*

Based on a letrozole-induced rat model of polycystic ovary syndrome (PCOS), serum metabolomics was employed to characterize metabolic abnormalities, identify potential biomarkers, and investigate their roles in the pathogenesis and progression of PCOS. Metabolomic analyses revealed significantly decreased levels of cholesterol, pregnenolone, leucine, and citrate in the serum of model rats, accompanied by elevated levels of androsterone glucuronide (ADTG) and linoleic acid, indicating dysregulation of key pathways including steroid biosynthesis, branched-chain amino acid metabolism, tricarboxylic acid (TCA) cycle, and lipid metabolism. To elucidate the tissue origins and molecular mechanisms underlying these metabolic alterations, ovarian proteomics and qRT-PCR analyses were further integrated. The results confirmed the upregulation of key enzymes involved in the related metabolic pathways, such as 17α-hydroxylase (CYP17A1), 11β-hydroxysteroid dehydrogenase (HSD11B1), branched-chain amino acid aminotransferase (BCAT2), fatty acid desaturase 2 (FADS2), and oxoglutarate dehydrogenase (OGDH). These findings suggest that both “cholesterol precursor depletion-androgen accumulation” and “energy/lipid metabolic reprogramming” constitute core features of metabolic disturbances in PCOS. Through multi-omic cross-validation, six serum metabolites with high stability and clinical translational potential were identified as promising combinational biomarkers for the auxiliary diagnosis of PCOS. This study employed a metabolomics-guided strategy, supported by proteomic and transcriptomic validation, which has not only deepened our understanding of PCOS metabolic mechanisms but also provided us with a theoretical foundation for its auxiliary diagnosis.