Main active constituent identification in Guanxinjing capsule, a traditional Chinese medicine, for the treatment of coronary heart disease complicated with depression
Abstract
Abstract
Guanxinjing capsules (GXJCs) are used in traditional Chinese medicine as a common therapy for coronary heart disease (CHD) complicated with depression. In this study, we aimed to identify the main active constituents in GXJCs and to investigate the mechanisms of GXJC action on CHD complicated with depression. The chemical constituent profile of the GXJC was identified by UHPLC-LTQ-Orbitrap assay, and oral bioavailability was evaluated to screen the GXJC drug-like chemical constituents. A total of 16 GXJC drug-like chemical constituents were identified. Then, putative targets of the GXJC drug-like chemical constituents were predicted using MedChem Studio, with 870 genes found to be the putative targets of these molecules. After that, a GXJC putative target-known CHD/depression therapeutic target network was constructed, and four topological features, including degree, betweenness, closeness and K-coreness, were calculated. According to the topological feature values of the GXJC putative targets, 14 main active constituents were identified because their corresponding putative targets had topological importance in the GXJC putative target-known CHD/ depression therapeutic target network, which were defined as the candidate targets of GXJC against CHD complicated with depression. Functionally, these candidate targets were significantly involved in several CHD/depression-related pathways, including repairing pathological vascular changes, reducing platelet aggregation and inflammation, and affecting patient depression. This study identified a list of main active constituents of GXJC acting on CHD complicated with depression using an integrative pharmacology-based approach that combined active chemical constituent identification, drug target prediction and network analysis. This method may offer an efficient way to understand the pharmacological mechanisms of traditional Chinese medicine prescriptions.
Keywords:
traditional Chinese medicine; Guanxinjing capsule; coronary heart disease; depression; integrative pharmacology; in silico ADME prediction; target prediction; network analysis
Guanxinjing capsules (GXJCs) are used in traditional Chinese medicine as a common therapy for coronary heart disease (CHD) complicated with depression. In this study, we aimed to identify the main active constituents in GXJCs and to investigate the mechanisms of GXJC action on CHD complicated with depression. The chemical constituent profile of the GXJC was identified by UHPLC-LTQ-Orbitrap assay, and oral bioavailability was evaluated to screen the GXJC drug-like chemical constituents. A total of 16 GXJC drug-like chemical constituents were identified. Then, putative targets of the GXJC drug-like chemical constituents were predicted using MedChem Studio, with 870 genes found to be the putative targets of these molecules. After that, a GXJC putative target-known CHD/depression therapeutic target network was constructed, and four topological features, including degree, betweenness, closeness and K-coreness, were calculated. According to the topological feature values of the GXJC putative targets, 14 main active constituents were identified because their corresponding putative targets had topological importance in the GXJC putative target-known CHD/ depression therapeutic target network, which were defined as the candidate targets of GXJC against CHD complicated with depression. Functionally, these candidate targets were significantly involved in several CHD/depression-related pathways, including repairing pathological vascular changes, reducing platelet aggregation and inflammation, and affecting patient depression. This study identified a list of main active constituents of GXJC acting on CHD complicated with depression using an integrative pharmacology-based approach that combined active chemical constituent identification, drug target prediction and network analysis. This method may offer an efficient way to understand the pharmacological mechanisms of traditional Chinese medicine prescriptions.