Prediction and validation of activity of anti-hyperuricemic nephropathy drugs based on transcriptomic data
Objective To screen small molecule drugs that can be used to treat hyperuricemic nephropathy(HN)from existing drugs by using transcriptomic data,providing new ideas for the treatment of HN.Methods HN dataset was obtained from GEO data,and differentially expressed genes were screened.KEGG and GO enrichment analyses were performed on the core target using Metascape platform.The protein-protein interaction network(PPI)was constructed using String database,and Cytoscape calculated node connectivity to screen the core genes of HN pathogenesis.Anti-HN drugs were predicted in CMAP database,and interactions between drug candidates and core targets were analyzed by molecular docking.The HN model was established by potassium oxazinate combined with adenine to validate the renal protective function of candidate drugs.Results A total of 557 differentially expressed genes were screened from HN transcriptome dataset GSE190205,including 374 up-regulated genes and 183 down-regulated genes.The differentially expressed genes were involved in rheumatoid arthritis,fatty acid degradation,TNF signaling pathway,phagosome et al.ITGAM,TLR2,CD68,CD44 and CCL5 genes might be involved in the pathogenesis of HN.By CMAP analysis,candidate drugs such as M-3M3FBS,enzastaurin,betulinate and entecavir were screened.Further animal experiments confirmed that enzastaurin had good renal protection function,significantly decreased the kidney index,serum Cre and serum BUN of HN rats(P<0.05 or P<0.01),and improved the kidney tissue injury.Conclusion The"drug relocation"strategy based on transcriptomic data can screen effective anti-HN drugs from old drugs,which provides a new idea for the study of HN drugs.
万方数据
维普
