Network Pharmacology and Molecular Docking to Explore the Mechanism of Compound Qilian Tablets in Treating Diabetic Retinopathy

Background Diabetic Retinopathy (DR) is one of the common chronic complications of diabetes mellitus, which has developed into the leading cause of irreversible visual impairment in adults worldwide. The Compound Qilian Tablets (CQLT) were developed in China for the treatment and prevention of DR, but their mechanism of action is still unclear. Objective In the present study, network pharmacology, molecular docking, and in vivo validation experiments were used to investigate the active components and molecular mechanisms of CQLT against DR. Methods The active components and targets of CQLT were collected through the TCSMP database, and the targets of DR were obtained from GeneCards, OMIM, and Drugbank databases. We established a protein-protein interaction network using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the Metascape database. Molecular docking using AutoDock Vina was performed to investigate the interactions between components of CQLT and core targets. Moreover, we selected ZDF rats to establish a DR model for the experimental studies. Results 39 active components and 448 targets in CQLT were screened, among which 90 targets were shared with DR. KEGG pathway enrichment analysis identified 181 pathways. The molecular docking results demonstrated that the main active components had strong binding ability to the core targets. The results from animal experiments indicate that the mechanism of CQLT against DR is associated with inhibiting the retinal mTOR/HIF-1 alpha/VEGF signaling pathway, alleviating the inflammatory response, suppressing retinal neovascularization, and protecting the function and morphology of the retina. Conclusion The present study preliminarily explored the mechanism of CQLT in treating DR and demonstrated that CQLT exerts anti-DR effects through multiple components, multiple targets, and multiple pathways. These findings suggest that CQLT shows promise as a potential therapeutic agent for DR and could contribute to developing novel treatments.