Abstract
The gut microbiome plays a crucial role in renal diseases, influencing conditions such as renal cell carcinoma (RCC), acute kidney injuries, and diabetic nephropathy. Recent studies highlight the association between gut microbial metabolites (GMM) and RCC progression. This study employs a computational network pharmacology framework to explore the mechanistic action of gut microbiota-derived metabolites against RCC. GMM were selected from the gutMgene database and analyzed for common targets using DisGeNET, Gene Card, and OMIM. Downstream analysis included gene ontology, KEGG pathway enrichment, metabolite-target-pathway-disease network construction, and protein-protein interaction analysis. Further, key metabolites were evaluated for drug-likeness, ADMET properties, and molecular docking, followed by molecular dynamics simulations (MDS) to assess complex stability. The JUN/AP-1 gene emerged as the prime target, exhibiting the highest binding affinity with Icaritin (- 5.9 kcal/mol), followed by Quercetin and Luteolin. MDS confirmed the stable binding of Icaritin to the active site throughout the simulation. These GMM may influence anticancer activity through distinct regulatory pathways involving the JUN/AP-1 gene, either by inhibiting or modulating its function. These insights establish a basis for further in vitro and in vivo investigations, supporting the development of microbiome-based therapeutic approaches.