Pharmacological mechanism of JiaWeiSiWu granule in the treatment of hypertension based on network pharmacology

Introduction

Hypertension is a type of vascular disease that seriously affects human health. If blood pressure is at a high level for a long time, it can cause serious complications such as stroke, heart failure, and renal failure (1). Currently, there are a wide variety of anti-blood pressure drugs, but the occurrence rate of the complications cannot be reduced. The side effects of certain drugs can also influence the metabolism, and blood pressure is not only needed to be actively reduced for the treatment of hypertension, but also, the protection of the target organ is taken into account (2). Some treatments lower patient treatment compliance, resulting in a low control rate and low treatment rate (3). The traditional Chinese medicine (TCM) treatment of hypertension has multi-target functions, and can reduce the adverse reactions caused by taking other medicines (4,5).

JiaWeiSiWu granule (JWSWG) was devised by our hospital after the long-term accumulation of clinical experience and screening effective prescriptions (6,7). JWSWG has been applied clinically for more than a decade, and the preliminary results show that blood pressure can be reduced, while also protecting the target organ at the same time. JWSWG is composed of 7 Chinese medicines, namely DiHuang, ChiShao, DangGui, ChuanXiong, GouQi, DiGuPi, and DiLong. DiHuang functions to nourish blood and nourish yin, as well as cooling blood and generating jin. ChiShao functions to cool blood, clear heat, and regulate qi. DangGui functions to replenish blood circulation and activate blood, as well as nourishing the liver and regulating blood. ChuanXiong functions to activate qi, activate blood, and relieve pain. GouQi can treat vertigo, nourish the liver, nourish yin, and nourish essence. DiGuPi can clear heat, cool blood, and clear collaterals. DiLong has the effect of clearing away heat and clearing collaterals. The combination of multiple Chinese medicines is effective in nourishing qi and activating blood circulation as well as nourishing the liver and kidneys. It has been confirmed by clinical and scientific research for many years that JWSWG can accelerate symptom relief, control blood pressure, regulate blood lipids, and prevent the damage of target organs (8-10).

A major feature of Chinese medicine is that the components are various and complex. Up to now, the research on TCM has been limited to explaining its mechanisms and pathways for a target gene, and has lacked a whole view and syndrome differentiation view of TCM (11). TCM is characterized by its multi-component, multi-target, and multi-pathway mechanisms, which fits well with the network-oriented and multi-component research methods that network pharmacology focuses on. Therefore, network pharmacology is now widely applied in pharmacological studies of TCM (12,13).

At present, there is a lack of research on the multi-target and multi-pathway mechanisms of JWSWG. The mechanism of JWSWG in treating hypertension needs to be further studied. In this study, the relationship and connection of biological network nodes were analyzed with the technology and methods of TCM network pharmacology, which revealed the mechanism of JWSWG in treating hypertension. Subsequently, the multi-level network of “molecule-target-pathway-disease” was employed to accomplish the comprehensive network analysis of molecular action. Finally, the binding of the target and its corresponding components was verified by molecular docking. The mechanism of JWSWG in treating hypertension was eventually expounded from the overall view, providing novel research directions for further experimental and clinical studies.

We present the following article in accordance with the MDAR reporting checklist (available at https://dx.doi.org/10.21037/apm-21-1140).

Methods

Materials

The following programs and databases were used: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, http://tcmspw.com/tcmsp.php); UniProt (http://www.uniprot.org/); STRING database (https://string-db.org/); Cytoscape software (Version 3. 6. 0) and the tool Network Analyzer and its apps: ClueGO, CluePedia; Bioconductor (https://bioconductor.org/bioLite.R) and its packages: org. Hs. eg.db, clusterProfiler; The R programming language (RGUI); KEGG PATHWAY Database (https://www.kegg.jp); GeneCards database (https://www.genecards.org/).The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). All these databases are publicly available, and ethical approval was unnecessary.

Study methods

Selecting active components and targets of JWSWG

The effective chemical components of JWSWG (DiHuang, ChiShao, DangGui, ChuanXiong, GouQi, DiGuPi) were obtained by using the TCMSP database (DiLong is not a herbal medicine, so we did not analyze it) (14). TCMSP is a distinctive pharmacology platform for Chinese herbal medicines which can reflect the relationships and connections among drugs, targets, and diseases. Two important indicators of pharmaceutically active ingredients in researching and developing drugs are oral bioavailability (OB) and drug-likeness (DL). OB reflects the absorption and distribution of drugs in the human body, and DL reflects the similarity between the components and existing drugs, as well as the possibility of developing drugs. Therefore, the screening conditions of the main active components and relevant targets of JWSWG from TCMSP were OB ≥30% and DL ≥0.18. Human gene codes were screened out with the UniProt knowledge base, retrieval form: [Homo sapiens (organism)]. All the searched genes were corrected to their official names.

Screening out action targets

The corresponding targets of hypertension were searched with the keyword “hypertension” in the GeneCards database. GeneCards is one of the most comprehensive websites for human genetic information, providing integrative, user-friendly information on all annotated and predicted human genes. The targets which related to both the drug JWSWG and the disease hypertension were the possible action targets of JWSWG in treating hypertension.

Constructing and analyzing the “medicine-compound-target-disease” network

According to the compounds and targets screened, the “medicine-compound-target-disease” network was constructed. Then, this network was analyzed by the Cytoscape software which has the function of “Network Analyzer”. Nodes represented the herbal medicine of JWSWG, compounds, action targets, and disease, while edges represented the relationships among them. Therefore, the key compounds of JWSWG in treating hypertension were selected in accordance with the junctions of the compound and target.

Constructing the protein-protein interaction (PPI) network and selecting the key targets

The STRING database was employed to construct the PPI network. The genes which were screened out from medicine-disease interaction target proteins were introduced into STRING, the research species was defined as “Homo sapiens”, 0.4 was set as the minimum interaction score, and default settings were applied as for other parameters to acquire the PPI network of JWSWG on hypertension. Then, the PPI network was subjected to topology analysis by virtue of the “Network analyzer” function of Cytoscape software, and the key targets with advanced degrees were determined.

Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis

The entrezIDs of action targets were obtained by RGUI and org.Hs.eg.db. GO functional enrichment including molecular function (MF), biological process (BP), and cellular component (CC) as well as KEGG pathway enrichment were obtained by RGUI and clusterProfiler. Furthermore, by enriching the GO functions and KEGG pathways by inputting action targets into ClueGO, and employing CluePedia to edit the networks, the connection between action targets and pathways were displayed more directly.

Verification of molecular docking

The binding of the target proteins and their corresponding components was verified by molecular docking. The 2D and 3D structures of the small-molecule compounds were obtained from the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) and the macromolecular protein target receptors were obtained from the RCSB PDB database (http://www.rcsb.org/). Molecular docking simulations of macromolecular protein target receptors and their corresponding compounds were performed using AutoDockTool 1.5.6 and AutoDock Vina software, and further demonstration was using the PyMOL Molecular Graphics System (Version 2.4.0).

Screening results of candidate compounds and targets

Under the conditions of OB ≥30% and DL ≥0.18, a total of 87 possible compounds of JWSWG were obtained using the TCMSP. The essential information of all possible compounds is displayed in Table 1. The TCMSP was adopted to obtain the relevant targets of the 87 compounds. Then, Homo sapiens search was employed to screen out corresponding human gene codes in the UniProt knowledge base, and 102 target genes were selected as a result (Table 2).

Table 1 Candidate compounds of JWSWG with OB and DL paraments
Full table

Table 2 The corresponding targets of candidate compounds
Full table

Action targets acquisition

By intersecting 102 compound target genes with 6,732 hypertension target genes, 88 action target genes were obtained from the GeneCards database (Table 3).

Table 3 Intersection action target genes
Full table

Network construction and analysis results

Cytocsape software was employed to construct the “medicine-compound-target-disease” interaction network on the basis of the 88 action target genes. The network showed 146 nodes (51 compound nodes, 88 target gene nodes, 6 herbal medicine nodes, and 1 disease node) and 395 edges (Figure 1). From the figure, it was found that the most valuable compounds were quercetin, beta-sitosterol, baicalein, stigmasterol, acacetin, ellagic acid, and glycitein (Table 4). These high-value compounds are the possible key compounds in treating hypertension with JWSWG.

Figure 1 The “medicine-compound-target-disease” network. A total of 146 nodes (51 compound nodes, 88 target gene nodes, 6 herbal medicine nodes, and 1 disease node) and 395 edges were shown in the network.

Table 4 Key compounds of JWSWG in the treatment of hypertension
Full table

Constructing the PPI network and screening the key targets

The STRING database was employed to construct the PPI network by analyzing the 88 intersection target genes for the purpose of exploring the mechanism of JWSWG in treating hypertension. The lowest interaction score was set to 0.4, then 87 targets in this network showed protein interaction (one target did not have protein interaction), and 787 edges indicated the interaction between proteins (Figure 2). The figure showed that the high-degree targets were interleukin 6 (IL6), caspase 3 (CASP3), epithelial growth factor receptor (EGFR), proto-oncogene myc (MYC), vascular endothelial growth factor A (VEGFA), estrogen receptor α (ESR1), cyclin D1 (CCND1), proto-oncogene c-Fos (FOS), tyrosine kinase receptor 2 (ERBB2), and androgen receptor (AR) (Table 5, Figure 3). The above-mentioned targets are therefore the possible key targets for JWSWG in treating hypertension.

Figure 2 PPI network of JWSWG in treating hypertension. The lowest interaction score was set to 0.4, then 87 targets in this network showed the protein interaction (one target did not), and 787 edges indicated the interaction between proteins. PPI, protein-protein interaction; JWSWG, JiaWeiSiWu granule.

Table 5 Key genes of JWSWG in treating hypertension
Full table

Figure 3 Key genes revealed by the PPI network. This figure showed that the high-degree targets were IL6, CASP3, EGFR, MYC, VEGF A, ESR1, CCND1, FOS, ERBB2, and AR. PPI, protein-protein interaction; IL, interleukin; CASP, caspase; EGFR, epithelial growth factor receptor; MYC, proto-oncogene myc; VEGF, vascular endothelial growth factor; ESR1, estrogen receptor α; CCND1, cyclin D1; FOS, proto-oncogene c-Fos; ERBB, tyrosine kinase receptor; AR, androgen receptor.

GO functional enrichment analysis

GO functions were enriched by RGUI and clusterProfiler, and the results of GO-MF, GO-BP, and GO-CC were as follows.

The 88 intersection target genes influenced 107 MF (P value <0.05, q value <0.05). The P value ranking was adopted as the screen condition and the MF information of the top 20 was obtained. The intersection genes of JWSWG in treating hypertension were principally involved in nuclear receptor activity, transcription factor activity, direct ligand regulated sequence-specific DNA binding, steroid hormone receptor activity, steroid binding, proximal promoter sequence-specific DNA binding, DNA-binding transcription activator activity, RNA polymerase II-specific, protein heterodimerization activity, RNA polymerase II proximal promoter sequence-specific DNA binding, cofactor binding, heme binding, tetrapyrrole binding, ubiquitin-like protein ligase binding, ubiquitin protein ligase binding, Hsp90 protein binding, RNA polymerase II transcription factor binding, chromatin binding, ammonium ion binding, G protein-coupled amine receptor activity, nuclear hormone receptor binding, and activating transcription factor binding (Table 6, Figure 4).

Table 6 GO-MF of drug-disease intersection genes (from clusterProfiler)
Full table

Figure 4 Histogram of GO-MF enrichment analysis (from clusterProfiler). The intersection genes of JWSWG in treating hypertension primarily converged on nuclear receptor activity, transcription factor activity, direct ligand regulated sequence-specific DNA binding, steroid hormone receptor activity, steroid binding, proximal promoter sequence-specific DNA binding, DNA-binding transcription activator activity, RNA polymerase II-specific, protein heterodimerization activity, RNA polymerase II proximal promoter sequence-specific DNA binding, cofactor binding, heme binding, tetrapyrrole binding, ubiquitin-like protein ligase binding, ubiquitin protein ligase binding, Hsp90 protein binding, RNA polymerase II transcription factor binding, chromatin binding, ammonium ion binding, G protein-coupled amine receptor activity, nuclear hormone receptor binding, and activating transcription factor binding. GO-MF, Gene Ontology molecular function; JWSWG, JiaWeiSiWu granule.

The 88 intersection target genes influenced 1,331 BP (P value <0.05, q value <0.05). The P value ranking was adopted as the screen condition and the BP information of the top 20 was obtained. The intersection genes of JWSWG in treating hypertension were chiefly enriched in response to steroid hormone, response to ketone, response to xenobiotic stimulus, cellular response to xenobiotic stimulus, response to toxic substance, regulation of body fluid levels, response to oxidative stress, response to metal ion, response to antibiotic, response to oxygen levels, cellular response to steroid hormone stimulus, response to hypoxia, cellular response to drug, response to decreased oxygen levels, reactive oxygen species metabolic process, cellular response to oxidative stress, gland development, response to radiation, intracellular receptor signaling pathway, and response to acid chemical (Table 7, Figure 5).

Table 7 GO-BP of drug-disease intersection genes (from clusterProfiler)
Full table

Figure 5 Histogram of GO-BP enrichment analysis (from clusterProfiler). The intersection genes of JWSWG in treating hypertension chiefly converged on response to steroid hormone, response to ketone, response to xenobiotic stimulus, cellular response to xenobiotic stimulus, response to toxic substance, regulation of body fluid levels, response to oxidative stress, response to metal ion, response to antibiotic, response to oxygen levels, cellular response to steroid hormone stimulus, response to hypoxia, cellular response to drug, response to decreased oxygen levels, reactive oxygen species metabolic process, cellular response to oxidative stress, gland development, response to radiation, intracellular receptor signaling pathway, and response to acid chemical. GO-BP, Gene Ontology biological process; JWSWG, JiaWeiSiWu granule.

The 88 intersection target genes influenced 61 CC (P value <0.05, q value <0.05). The P value ranking was adopted as the screen condition and the CC information of the top 20 was obtained. The intersection genes of JWSWG in treating hypertension were primarily enriched in membrane raft, membrane microdomain, membrane region, nuclear chromatin, nuclear chromosome part, chromatin, axon terminus, integral component of postsynaptic membrane, neuron projection terminus, intrinsic component of postsynaptic membrane, integral component of presynaptic membrane, transcription factor complex, axon part, intrinsic component of presynaptic membrane, receptor complex, integral component of synaptic membrane, intrinsic component of synaptic membrane, presynapse, distal axon, and glutamatergic synapse (Table 8, Figure 6).

Table 8 GO-CC of drug-disease intersection genes (from clusterProfiler)
Full table

Figure 6 Histogram of GO-CC enrichment analysis (from clusterProfiler). The intersection genes of JWSWG in the treatment of hypertension chiefly converged on membrane raft, membrane microdomain, membrane region, nuclear chromatin, nuclear chromosome part, chromatin, axon terminus, integral component of postsynaptic membrane, neuron projection terminus, intrinsic component of postsynaptic membrane, integral component of presynaptic membrane, transcription factor complex, axon part, intrinsic component of presynaptic membrane, receptor complex, integral component of synaptic membrane, intrinsic component of synaptic membrane, presynapse, distal axon, and glutamatergic synapse. GO-CC, Gene Ontology cellular component; JWSWG, JiaWeiSiWu granule.

KEGG pathway enrichment analysis

RGUI and clusterProfiler were applied to KEGG pathway enrichment. The analysis of KEGG pathway enrichment indicated that the 88 intersecting target genes were observably enriched in 107 pathways (P value <0.05, q value <0.05). Among which, the top 20 pathways included prostate cancer, Kaposi sarcoma-associated herpesvirus infection, hepatitis B, human cytomegalovirus infection, fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, colorectal cancer, hepatocellular carcinoma, proteoglycans in cancer, platinum drug resistance, bladder cancer, apoptosis, breast cancer, thyroid hormone signaling pathway, p53 signaling pathway, hepatitis C, PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, legionellosis, and endometrial cancer, suggesting that JWSWG plays a crucial role in treating hypertension by working on the above-mentioned multiple pathways (Table 9, Figure 7). The chief pathways are displayed in Figures 8 and 9.

Table 9 Pathway information of drug-disease intersection genes
Full table

Figure 7 Histogram of KEGG pathway enrichment analysis. The top 20 pathways were prostate cancer, Kaposi sarcoma-associated herpesvirus infection, hepatitis B, human cytomegalovirus infection, fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, colorectal cancer, hepatocellular carcinoma, proteoglycans in cancer, platinum drug resistance, bladder cancer, apoptosis, breast cancer, thyroid hormone signaling pathway, p53 signaling pathway, hepatitis C, PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, legionellosis, and endometrial cancer, suggesting that JWSWG plays a crucial role in treating hypertension by working on the above-mentioned multiple pathways. KEGG, Kyoto Encyclopedia of Genes and Genomes; EGFR, epithelial growth factor receptor; JWSWG, JiaWeiSiWu granule.

Figure 8 Prostate cancer pathway.

Figure 9 Fluid shear stress and atherosclerosis pathway.

Molecular docking

We obtained the 3D structures of the small-molecule compounds from the PubChem Database and the macromolecular protein target receptors from the RCSB PDB database. Then, molecular docking simulations of potential targets and their corresponding compounds were performed using AutoDockTool 1.5.6 and AutoDock Vina software. Finally, the binding of the target and its corresponding component was verified by molecular docking and demonstrated by the PyMOL Molecular Graphics System. We selected IL6-beta-sitosterol to demonstrate. In the molecular docking simulations of IL6-beta-sitosterol, minimum affinity was −7.0 kcal/mol, grid center was −0.585, 0.365 and 0.253, dist from best mode was 0.000 rmsd l.b. and 0.000 rmsd u.b. (Figure 10).

Figure 10 IL6-beta-sitosterol molecular docking. (A) 3D structures of beta-sitosterol; (B) 3D structures of IL6; (C) molecular docking simulation; and (D) molecular docking simulation (display protein surface). IL6, interleukin 6.

Statistical analysis

A part of the statistical analysis was simultaneously conducted with the biotechnology add-ons of the software and platforms that have been disclosed in previous sections. In the GO function and KEGG pathway enrichment, an adjusted P (adj. P) value was used and adj. P<0.05 was perceived as statistically significant.

Discussion

In recent years, with the changes of people’s diets and lifestyles, the incidence of hypertension has increased year by year, becoming a serious public health problem. Persistent hypertension not only increases the risk of cardiovascular and cerebrovascular adverse events, but also causes damage to target organs such as the heart, brain, and kidneys, among others, which seriously threatens the health and safety of patients (15). Renal injury is particularly common, as the kidney can be regulated by water and sodium metabolism and secretory pressure, and antihypertensive substances affect the fluctuation of blood pressure. Essential hypertension can also cause renal arteriosclerosis, resulting in renal function damage. After renal function is damaged, the hypertension will be further aggravated, thus forming a vicious circle (16).

JWSWG was formed with the background of several years of clinical practice. The original basic prescription includes DiHuang, DangGui, ChuanXiong, GouQi, DiGuPi, and DiLong. Modern pharmacological studies of DiHuang have shown that it can significantly reduce blood pressure, improve renal function, and reduce blood glucose. Studies also showed that the indexes of hemorheology in the model group of blood stasis syndrome were markedly higher than those in the normal group, and the indexes of hemorheology in the low dose group were significantly lower than those in the model group. Therefore, DiHuang can also significantly improve microcirculation (17). The pharmacological effects of ChiShao include anticoagulation and antithrombosis. ChiShao could significantly reduce blood viscosity, fibrin content, erythrocyte aggregation index, and hematocrit in rats with blood stasis (18,19). Also, ChiShao could significantly improve microcirculation (20). ChiShao has also been shown to decrease the viscosity of serum and plasma, inhibit platelet aggregation, prolong prothrombin time and activated partial thromboplastin time, and had protective effects on renal ischemia, cerebral ischemia, and myocardial ischemia (21-23). Modern pharmacology shows that DangGui has the effects of dilating blood vessels, reducing vascular resistance, improving organ blood flow, reducing platelet aggregation and antithrombosis, increasing low shear whole blood viscosity, enhancing erythrocyte aggregation, promoting platelet aggregation, increasing cardiac blood supply, reducing myocardial oxygen consumption, and protecting cardiomyocytes (24-26). ChuanXiong can dilate the coronary artery, increase coronary flow, inhibit aortic smooth muscle contraction, and antagonize the pressor effects of methoxyamine, phenylephrine, and epinephrine. It can also inhibit platelet aggregation and inhibit thrombosis (27-29). GouQi has the functions of enhancing immunity, reducing blood lipids, lowering blood glucose, lowering blood pressure, protecting the liver, and preventing radiation damage, and also has anti-hypoxia, anti-tumor, anti-aging, and anti-fatigue effects, among others. GouQi could protect against cerebral ischemia-reperfusion injury in mice (30-32). Modern pharmacological studies have revealed that DiGuPi has the activities of lowering blood pressure, regulating blood lipids, and lowering blood sugar, and also has anti-pyretic, antibacterial, and antiviral properties (33,34).

A number of clinical studies have demonstrated that JWSWG has a remarkable effect on treating hypertension and its complications. JWSWG can effectively reduce blood pressure, has obvious curative effect on hypertension of yin deficiency and yang hyperactivity, and can effectively reduce the level of serum CRP (7). JWSWG can effectively reduce urinary albumin in patients with hypertension while controlling blood pressure to achieve a protective effect on the kidneys (6,8). JWSWG is safe and reliable in the treatment of stable angina pectoris complicated with dyslipidemia in patients with stable angina pectoris caused by phlegm and blood stasis. It can not only reduce angina pectoris attack, improve ischemic changes of electrocardiogram, reduce nitroglycerin dosage, and improve TCM symptoms, but also improve blood lipid levels (10). JWSWG can reduce the increase of serum total cholesterol and low density lipoprotein cholesterol in patients with mild to moderate hypertension with yin deficiency and yang hyperactivity, and can improve many indexes of hemorheology in patients with mild to moderate hypertension (35). JWSWG can treat sleep disorders after cerebral infarction, which can dispel blood stasis, promote new blood generation, smooth qi, unobstruct the heart and brain choroid, restore heart spirit, and recover sleep (9). JWSWG can not only effectively improve visual acuity, retinal circulation time, and TCM syndrome, but can also help to improve the hemorheological indexes of patients (36).

The ingredients of Chinese medicine are various and complex. In the study of TCM, there are currently still some problems, including the complex compositions and unclear mechanisms of action. Most of the current research has the limitation of explaining mechanisms and pathways of Chinese medicine for a certain target gene, and the lack of holistic studies on multi-component, multi-target, and multi-pathway aspects of TCM. Nowadays, network pharmacology is well developed, and utilizes the research methods of network goal and multi-component therapy, which is in accordance with the feature of “multi-component, multi-target, and multi-pathway” of TCM, and is widely applied to pharmacological research on TCM (37,38).

In this study, the whole view of TCM and syndrome differentiation were combined with the method of network pharmacology analysis. With the support of the corresponding databases and software, the network was constructed and the pathway enrichment of the targets was analyzed. The mechanism of JWSWG in the treatment of hypertension was systematically discussed.

In this study, quercetin, beta-sitosterol, baicalein, stigmasterol, acacetin, ellagic acid, and glycitein were the key compounds of JWSWG in treating hypertension. It has been shown that quercetin can decrease blood pressure and heart rate in elderly hypertensive rats (39). Quercetin can inhibit the proliferation of aortic wall fibroblasts, smooth muscle cells, and the synthesis and secretion of collagen, and delay the process of arteriosclerosis (40). Beta-sitosterol has the effects of reducing blood lipids, and has anticancer and anti-inflammation effects (41). Baicalin has a protective effect on rat cardiomyocytes damaged by ischemia in vivo or oxidative injury in vitro (42). Baicalin has a protective effect on myocardial ischemia and reperfusion injury (43,44). Stigmasterol lowers cholesterol and reduces the risk of cardiovascular disease (45). Acacetin has a protective effect on blood lipid metabolism and atherosclerosis in mice (46-48). Ellagic acid can ameliorate cerebral ischemia or reperfusion injury and has an effect on antioxidant and antimicrobial activity (49,50).

The key targets for JWSWG in the treatment of hypertension were IL6, CASP3, EGFR, MYC, VEGFA, ESR1, CCND1, FOS, ERBB2, and AR. GO enrichment analysis suggested that the target genes related to JWSWG in the treatment of hypertension were related to a variety of molecular functions, biological processes, and cell compositions. We used ClueGO and CluePedia analysis to express this more intuitively (Figure 11). These target genes play important roles in the regulation of endothelial function and the neuroendocrine system, and are also involved in anti-inflammatory and antioxidative effects.

Figure 11 GO enrichment analysis (from ClueGO). GO, Gene Ontology.

KEGG pathway enrichment analysis indicated that multiple pathways were involved in the pathogenic mechanisms of hypertension. The chief pathways included prostate cancer, Kaposi sarcoma-associated herpesvirus infection, hepatitis B, human cytomegalovirus infection, fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, colorectal cancer, hepatocellular carcinoma, proteoglycans in cancer, platinum drug resistance, bladder cancer, apoptosis, breast cancer, thyroid hormone signaling pathway, p53 signaling pathway, hepatitis C, PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, legionellosis, and endometrial cancer, suggesting that JWSWG plays a crucial role in treating hypertension by working on the above-mentioned pathways. The main pathways showed that the key nodes of these pathways were closely related to hypertension (51-55) (Figures 8,9,12).

Figure 12 KEGG enrichment analysis (from ClueGO). KEGG, Kyoto Encyclopedia of Genes and Genomes.

The inadequacies of this study are as follows: First, network pharmacology is supported by data, the data collection process may not inclusive. Furthermore, the setting of screening criteria for effective active components was not completely accurate. Second, in this study, only 6 main herbs were analyzed. Lastly, the effect of dosage of Chinese medicine on treatment results was not taken into account.

Conclusions

To summarize, this research elaborated on the connections among the active components, targets, and pathways of JWSWG in treating hypertension based on network pharmacology. We also determined the characteristic of “multi-component, multi-target, and multi-pathway” of JWSWG. Pathway enrichment analysis revealed that the mechanisms of JWSWG in treating hypertension may include inhibiting the secretion of inflammatory factors, participating in anti-inflammatory responses, inhibiting oxidative stress, regulating vascular endothelial function, and regulating the neuroendocrine system to reduce blood pressure and protect target organs.

In this study, the connections and relationships of biological network nodes were obtained to analyze the mechanism of JWSWG in treating hypertension, and to perform comprehensive network analysis of molecular action. Overall, the mechanism of JWSWG in treating hypertension was revealed, providing a new direction for research on the pharmacology of TCM, and providing fresh research ideas, methods, and a theoretical foundation for future experimental and clinical research.

Acknowledgments

Funding: This study is supported by Natural Science Foundation of Shanghai (17ZR1418300).

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://dx.doi.org/10.21037/apm-21-1140

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/apm-21-1140). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). All these databases are publicly available, and ethical approval was unnecessary.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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