Screening out active components of QSYXG
As shown in Supplement 1, 55 unique bioactive components of QSYXG were screened out from the 628 chemical components. Respectively, there were two bioactive ingredients in Angelica sinensis, 13 bioactive components in Astragali radix, 23 bioactive components in Lycii fructus, 8 bioactive components in Polygonati rhizoma, 15 bioactive components in Ginseng radix et rhizoma. Among these, β-sitosterol was a common component of Angelica sinensis, Lycii fructus, Polygonati rhizoma and Ginseng radix et rhizoma, Stigmasterol was shared by Angelica sinensis, Lycii fructus and Ginseng radix et rhizoma, and kaempferol is simultaneously exist in Astragali radix and Ginseng radix et rhizoma.
Potential targets of QSYXG for the treatment of MF
Molecular similarity matching and database searching were used to obtain the targets of the active ingredients in QSYXG. A total of 224 potential targets were found after eliminating the overlaps. These targets of active compounds in QSYXG were mapped with 399 candidate targets relating to MF from the GeneCard database with ‘score’ ≥ 10.0, as shown in Supplement 2~3. This identified 59 targets of 55 components in QSYXG that were associated with MF, as shown in Figure 2-1, Supplement 4. These targets were considered to be the potential targets of QSYXG for the treatment of MF and used to establish a component-target network comprising 114 nodes (55 active ingredients and 59 potential targets) and 250 edges, as shown in Figure 2-2.
The candidate targets of QSYXG against MF
As demonstrated by network biology, multiple disease-related genes and proteins could synergistic effects in MF. To elucidate the pharmacological mechanism by which QSYXG alleviates MF, a protein-protein network (PPI) was constructed with 1,387 nodes and 26,914 edges, which may embody the behaviour and characteristic of the biomolecules，as shown in Figure 2-3A, Supplement 5. Subsequently, a topological analysis of the PPI was conducted. Nodes with topological features exceeding the intermedy of all nodes were reputed as hubs in the network, and therefore candidate targets in the present study. These candidate targets were determined in the light of a widely used plugin CytoNCA, based on targets with higher values of the two topological features ‘Degree’ and ‘Betweenness centrality’. Following the construction of the PPI network, calculation of these two topological parameters for all targets identified that targets with ‘Degree’ > 61 and ‘Betweenness centrality’ > 600 were the candidate targets of QSYXG for the treatment of MF. Ultimately, 15 direct targets were identified, as shown in Figure 2-3B~2-3C, Supplement 6~7.
Enrichment analysis of GO and KEGG pathway
To illuminate the biological properties of the 59 targets of QSYXG for MF, the GO and pathway enrichment analyses were conducted via colorspace, stringi, ggplot2, DOSE, clusterProfiler and enrichplot in the R programming language package. These enable the comparison of biological subjects among gene clusters that support humans via the implementation of methods to statistically analyse and visualise functional profiles (GO and KEGG) of gene and gene clusters. There were 478 biological process (BP), 20 cellular component (CC) and 22 molecular function (MF) terms in total, which fulfill the requirements of count ≥ 2. The detailed GO information is shown in Supplement 8-10. The top 20 significantly enriched terms in the BP, CC and MF categories are shown in Figure 5A–C, which enunciated that QSYXG may generate its therapeutic effects on MF via responses to lipopolysaccharides and hypoxia, cytokine receptor binding, and tetrapyrrole binding in the cytosol, membrane raft and membrane regions.
To explore the signal pathways of QSYXG that were potentially associated with MF, KEGG pathway analysis of related targets was enforced. The detailed results indicated that the alleviation of MF by QSYXG was closely related to 20 pathways, including several significant signalling pathways including the TNF signalling pathway, IL−17 signalling pathway, MAPK signalling pathway and C-type lectin receptor signalling pathway, as shown in Figure 6, Supplement 11.
QSYXG suppresses myocardial fibrosis
Isoproterenol-induced myocardial injury lesions are featured by necrotic myocytes, inflammation and consecutive restorative fibrosis. Myocyte necrosis and obvious infiltration of inflammatory cells—mainly macrophages—into the myocardial tissue were seen in the model group. In the QSYXG group, the myocardial trauma was almost renovated, but sporadic scars in the injured areas were observed. Slight collagen deposition was seen in the myocardium of the normal and negative control groups. Additionally, obvious collagen fibre deposition around the arterioles and metarterioles was present in the model group and thick collagen fibres were present between myocardiocytes. In most cases, the main feature was collagen interstitial fibrosis, giving a ‘brindled’ look to the myocardium through the alternation of areas with fibrosis and areas of myocardial cells. The extent of myocardial fibrosis in the QSYXG group was evidently smaller than in the model group, suggesting that QSYXG could alleviate MF.
QSYXG regulates the expression of PTGS2, MAPK14, AKT1 and MAPK8
The KEGG pathway enrichment results indicated that the TNF, IL−17, C-type lectin receptor, Toll-like receptor and VEGF signalling pathways were intimately associated with MF treatment by QSYXG. The primary targets, including PTGS2, MAPK14, AKT1, MAPK8, were predicted in the enrichment of these five pathways. The effect of QSYXG on AKT1, MAPK8, MAPK14 and PTGS2 protein expression was explored by immunohistochemistry analysis. The results show a conspicuously increased in AKT1 and the down-regulated expression of MAPK8, MAPK14 and PTGS2, as shown in Figure 4.
MAPK8 and MAPK14 are potential myocardial fibrosis targets
To confirm that the expression of MAPK8 and MAPK14 was affected in isoproterenol-induced H9C2 cells, western blot assay was used to determine the effect on protein levels. A significant reduction in the expression of MAPK8 and MAPK14 was observed in QSYXG-treated cells compared to model group cells. There was no significant difference in the expression of MAPK8 and MAPK14 at the protein level in QSYXG-treated cells compared to control group cells.
QSYXG alleviates extensive changes in cytoskeleton structure
The F-actin organisation in H9C2 cells was investigated by fluorescent phalloidin staining. Cardiomyocytes in the control group presented regular and well-defined actin organisation, while cardiomyocytes in the model group showed more interspersed and aberrant F-actin disposition. The differences could be visualised in the typical cardiomyocytes. However, treatment by QSYXG improved F-actin organisation in cardiomyocytes contrasted with the model group and produced a marked remission in isoproterenol-induced cardiac hypertrophy and cardiac fibrosis.
QSYXG ameliorates isoproterenol-aggravated injury
The function of QSYXG on the expression of AKT1 and PTGS2 in isoproterenol-induced H9C2 cells was investigated by Immunofluorescence staining. The expression of AKT1 was lower in the model group than the control group, and QSYXG could enhanced its expression. The expression of PTGS2 was higher in the model group compared with the control group, but the expression was lower in the QSYXG group than the model group, as shown in Figure 5.