NFKB1-targeted metabolites as novel therapeutic approaches for erectile dysfunction: evidence from gut microbiota network pharmacology and machine learning.

Background: Growing evidence suggests that alterations in the gut microbiota may contribute to the pathogenesis of erectile dysfunction (ED).

Aim: To investigate the potential causal relationship between specific gut microbial taxa and ED, identify key microbial metabolites and their associated target genes, and evaluate their therapeutic potential through computational drug screening.

Methods: Genome-wide association study (GWAS) summary statistics for gut microbiota and ED were obtained from the MiBioGen, IEU OpenGWAS, and FinnGen databases. Mendelian randomization (MR) analysis was performed using the TwoSampleMR package to assess potential causal relationships. A microbiota-metabolite-target gene network was constructed using data from GutMGene, Super-PRED, and GeneCards databases to explore the microbiota-host interaction axis. The DeepPurpose machine learning framework was utilized to predict drug-target binding affinities, and top-ranking drug-gene pairs were validated by molecular docking to assess binding free energies and confirm interaction stability.

Outcomes: The study aimed to identify specific gut microbiota, metabolites, and target genes associated with ED and evaluate their therapeutic potential.

Results: MR analysis revealed a negative association between ED and the gut microbial genera Alistipes, Butyricicoccus, and Dialister, suggesting a potential protective role. Machine learning predictions indicated strong binding affinities between target genes (NFKB1, TLR4, CYP3A4) and bile acid derivatives (Tauroursodeoxycholic acid and Taurochenodeoxycholic acid). Molecular docking confirmed high binding affinities of NFKB1 to Tauroursodeoxycholic acid (-9.81 kcal/mol) and Taurochenodeoxycholic acid (-9.35 kcal/mol).

Clinical implications: These findings suggest that gut microbiota and their metabolites could serve as potential therapeutic targets for ED interventions.

Strengths and limitations: The study provides novel insights into the gut microbiota-ED relationship by integrating multi-omics data and advanced computational methods. However, validation in preclinical or clinical studies is needed to translate these findings into therapeutic applications.

Conclusion: Specific gut microbiota, through metabolites and associated target genes, may influence the onset of ED. These findings highlight potential therapeutic targets and provide a basis for future interventions in ED treatment.