Research on antithrombotic mechanism of Paeoniae Radix Alba based on data mining, network pharmacology and molecular docking technology

Abstract The antithrombotic mechanism of Paeoniae Radix Alba(PRA) was studied with data mining, network pharmacology and molecular docking techniques. The active ingredient of PRA was through mining and screening TCMSP database and literature, using the SwissTargetPrediction website to predict the target of the material. The Genacard database was used to mine "thrombotic" related targets, and the Cytoscape3.7.2 was used to construct PRA "active ingredients-thrombotic targets" network relationships. The target of antithrombotic drug was obtained by R language, Wencketty Diagram was drawn, and Kegg enrichment analysis was carried out. Then the core target of antithrombotic drug was selected by insertion of Cytonca, and its binding property to the core target was verified by molecular docking method. A total of 14 active components were selected from PRA and 257 targets were selected, among which 83 were antithrombotic targets and a total of 13 core antithrombotic targets were obtained, namely AKT1, ESR1, SRC, SERPINE1, MMP2, JUN, PTGS2, EGFR, FGF2, KDR, GAPDH, MMP9, VEGFA. A total of 1830 GO enrichment results were obtained, of which 1711 were enriched in biological processes (BP), 99 in molecular functions (MF) and 17 in cellular components (CC). A total of 127 KEGG signaling pathways were enriched. The docking results further showed that the active components of PRA could form intermolecular hydrogen bonds with the Amino acid residues of the core targets, and had strong binding properties. Based on data mining, network pharmacology and molecular docking techniques, PRA has been proved to have the characteristics of antithrombotic multi-pathway and synergistic therapy, and the possible targets of PRA antithrombotic and its mechanism of action were explored. It provides a theoretical basis for its further experimental study and clinical application.