Network pharmacology and molecular docking in the exploration of Taohong Siwu decoction against coronary heart disease

Abstract

Abstract Taohong Siwu decoction (TSD) is a traditional Chinese medicine formulation that has been widely used to treat coronary heart disease (CHD), although its underlying biological mechanism is unknown. Using gene or pathway terminology for analytical studies, protein‒protein interaction (PPI) network-based analysis, and PPI cluster recognition, we performed network pharmacology and molecular docking methods in this research. We used the MCODE method to evaluate the efficacy of TSD for CHD and to screen core targets. This research uses network pharmacology and molecular docking methods to first define the possible mechanism of TSD in the treatment of CHD. Method: The active ingredients of TSD and their targets were obtained by TCMSP, and a drug-component-target map was constructed using Cytoscape software. The pathogenic targets of CHD were obtained through the Gene Cardsdatabase, and the intersection obtained between the screened targets and the drug targets was added to the STRING database to create a PPI network.Cytoscape was used to examine the results, and the core targets were screened in MCODE. In the DAVID database, overlapping targets underwent GO and KEGG analysis. Finally, the core targets and active ingredients were analyzed by molecular docking. Result: The drug-ingredient-target network model has 216 nodes and 669 connections. Kaempferol, luteolin, and baicalein were the main substances with the highest degree values. AKT1, IL-6, and TNF are the primary receptors in the PPI network with the highest degrees. TSD therapy for CHD primarily involves control of cardiac contractility, and according to GO and KEGG analysis, lipid and atherosclerosis, the PI3K-AKT signaling pathway, smooth muscle hyperplasia, apoptosis, and death-induced signaling are involved. On the basis of molecular docking results, kaempferol, luteolin, and baicalein have high affinities for AKT1, IL-6, and TNF.