In this study, we used the network pharmacology approach to explore the potential disease targets of the
We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform to search for the key active compounds and targets of the drug pair. Based on the GeneCards database, the relevant targets for the drug pair were obtained. Then, we performed the molecular docking of the screened core active ingredients and proteins using the DAVID database and the R AutoDock Vina software. Based on the GSE22255 dataset, these screened target proteins were used to build random forest (RF) and support vector machine (SVM) models. Finally, a new IS nomogram prediction model was constructed and evaluated.
There were 36 active compounds in the EUO-TT drug pair. CHRM1, NR3C1, ADRB2, and OPRD1 proteins of the neuroactive ligand-receptor interaction pathway interacted with the proteins related to the ferroptosis pathway. Molecular docking experiments identified 12 active ingredients of the drug pair that may tightly bind to those target proteins. We constructed a visual IS nomogram prediction model using four genes (CHRM1, NR3C1, ADRB2, and OPRD1). The calibration curve, DCA, and clinical impact curves all indicated that the nomogram model is clinically applicable and diagnostically capable. CHRM1, NR3C1, ADRB2, and OPRD1, the target genes of the four effective components of the EUO-TT drug pair, were considered as risk markers for IS.
The active ingredients of EUO-TT drug pair may act on proteins associated with the neuroactive ligand-receptor interaction pathway to regulate ferroptosis in vascular neurons cells, ultimately affecting the onset and progression of hypertension.