Exploring the mechanism of Xiaoqinglong decoction in the treatment of infantile asthma based on network pharmacology and molecular docking : Medicine

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Research Article: Observational Study

Exploring the mechanism of Xiaoqinglong decoction in the treatment of infantile asthma based on network pharmacology and molecular docking

Chen, Daman BMa; Chen, Qiqi BMb; Zhao, Kaibo BMb; Guo, Yongqi BSb; Huang, Yuxin BMb; Yuan, Zehuan BMb; Cai, Yujia BMb; Li, Sitong BMa; Xu, Jiarong BSb; Lin, Xiaohong MMc,*

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Medicine 102(2):p e32623, January 13, 2023. | DOI: 10.1097/MD.0000000000032623
  • Open

Abstract

1. Introduction

Infantile asthma (IA) is a lung disease with recurrent wheezing and coughing in childhood, which can cause wheezing, shortness of breath, and prolonged breathing during acute flare-ups, and in severe cases can lead to dyspnea and inability to lie down, although it could be relieved by itself or improved after treatment.[1] According to the relevant epidemiological studies, the number of asthma patients in the world has exceeded 300 million, while the number in China has exceeded 30 million,[2] among which the prevalence rate of children has increased from 1.09% in 1990 to 3.02% in 2010, showing a rapid growth trend. At present, the main clinical drug treatments for the acute stage of the IA are hormones and bronchodilators, etc, but the therapeutic effect is not ideal due to poor compliance and heavy economic burden, and long-term use of hormones is not conducive to the healthy growth and development of children. Therefore, the combination of traditional Chinese medicine in the treatment of IA can effectively solve the shortcomings of Western medical routine therapy.

IA belongs to the category of wheezing syndrome and asthma syndrome in traditional Chinese medicine. Traditional Chinese medicine is effective in the treatment of asthma, among which Xiaoqinglong decoction (XQLD) is particularly effective. Asthma was first defined in Danxi’s Mastery of Medicine,[3] and XQLD was first recorded in Zhongjing Zhang’s Treatise on Cold Pathogenic and Miscellaneous Diseases. In XQLD, Mahuang and Guizhi can relieve exterior syndrome as well as dispel cold, and Mahuang can profoundly relieve asthma; Ganjiang and Banxia can dispel cold and resolve phlegm; Wuweizi and Baishao are to collect yin and promoting fluid; all herbs are used together to warm the lung and dissipate cold, resolve phlegm and settle asthma. That’s the reason why XQLD is widely used in the Chinese population for the treatment of cold asthma. In clinical application and randomized clinical trials,[4–6] XQLD has been proved to be effective in the treatment of asthma. In order to further explore the mechanism of XQLD in the treatment of IA, this study analyzed its mechanism through network pharmacology and molecular docking. And the corresponding workflow was shown in Figure 1.

F1
Figure 1.:
Workflow of network pharmacology and molecular docking.

2. Materials and methods

2.1. Screening of active ingredients and targets of XQLD

Ganjiang (Zingiberis Rhizoma), Guizhi (Cinnamomi Ramulus), Mahuang (Ephedrae Herba), Baishao (Paeoniae Radix Alba), Gancao (Licorice), Xixin (Asari Radix Et Rhizoma), Banxia (Arum Ternatum Thunb), and Wuweizi (Schisandrae Chinensis Fructus) were searched from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, https://tcmsp-e.com/tcmsp.php). TCMSP database incorporates key absorption, distribution, metabolism, and excretion-related properties such as human oral bioavailability (OB), drug-likeness (DL) and so on, which can be used for active compound screening. The active ingredients of XQLD were screened according to the absorption, distribution, metabolism, and excretion screening criteria with OB ≥ 30% and DL ≥ 0.18, and the corresponding predicted protein targets of the active ingredients were collected.

2.2. Acquisition of intersection targets for XQLD treating IA

The keyword “Infantile Asthma” was searched in OMIM (http://www.omim.org/) database and Gencards (https://www.genecards.org/) database respectively, and the disease targets of IA were obtained after deleting repetitive genes. The intersection targets of XQLD in the treatment of IA was obtained by merging the ingredient targets of XQLD and the disease targets of IA by Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/).

2.3. Construction of active ingredient-intersection target network

By using Cytoscape 3.7.2 software, the active ingredients and intersection targets of XQLD in the treatment of IA were collected, and the active ingredient-intersection target network was constructed. The nodes represent the active ingredients or intersection targets, and the edges represent the interaction between the active ingredients and the intersection targets.

2.4. Construction of protein-protein interaction (PPI) network

STRING online platform (https://string-db.org) was used to construct PPI network of XQLD in the treatment of IA, and the PPI network was obtained to directly reflect the interaction between proteins. The interaction genes obtained from PPI network were introduced into Cytoscape 3.7.2 for topological analysis, and the proteins that played an important role in the network were screened out.

2.5. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis

The potential target set of XQLD for the treatment of IA was imported into DAVID database for GO analysis and KEGG pathway enrichment analysis, which were carried out visually by R Studio software.

2.6. Molecular docking

The key ingredients and core targets of XQLD in the treatment of IA were verified by molecular docking. The mol2 format files of the key ingredients of XQLD were downloaded in the TCMSP database, and the pdb format files of the core targets were downloaded in the RSCB PDB (http://www.rcsb.org/) database. The force field used to minimize the ligand energy is MMFF94, and the Chem3D is used to minimize the ligand energy of small molecules. The macromolecules were dehydrated, the ligand was removed and hydrogenated by PyMOL 2.4, and then the non-polar hydrogen was combined with AutoDock 1.5.6, and the macromolecular charge was calculated and converted into pdbqt format. Because the binding sites between proteins and small molecules were unknown in this study, we used blind docking. The binding pocket coordinates is generated with the protoligand of crystal structure as the center, and the input configuration file set as size_x = 126, size_y = 126, size_z = 126. Finally, the key ingredients and core targets will be docked with Autodock, and the docking parameters are set to genetic algorithm. Dexamethasone is currently recognized as one of the drugs for the treatment of asthma. We will dock dexamethasone and core targets in the same way for further verification. The docking result will be visualized through PyMOL 2.4.

3. Results

3.1. The active ingredients and corresponding targets of XQLD

According to the standard of OB ≥ 30%, DL ≥ 0.18 to screen in TCMSP database, there were 5 active ingredients in Zingiberis Rhizoma, 7 in Cinnamomi Ramulus, 23 in Ephedra Herba, 13 in Paeoniae Radix Alba, 92 in licorice, 8 in Asari Radix Et Rhizoma, 13 in Arum Ternatum Thunb, and 8 in Schisandrae Chinensis Fructus. After deduplicating, there were 150 active ingredients in total, Supplemental Digital Content 1, https://links.lww.com/MD/1333.

3.2. Disease target genes and intersection target genes

After searching the OMIM and Gencards databases with “Infantile Asthma” as the keyword, a total of 2241 disease target genes were obtained after merging and deduplicating. By mapping the intersection targets of the active ingredients of XQLD with the disease target genes of IA, 92 intersection targets were obtained (Fig. 2), Supplemental Digital Content 2, https://links.lww.com/MD/1334

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Figure 2.:
Venn diagram of the intersection targets of XQLD and IA. IA = infantile asthma, XQLD = Xiaoqinglong decoction.

3.3. Active ingredient-intersection target network

The active ingredient-intersection target network of XQLD was constructed by utilizing Cytoscape 3.7.2 software (Fig. 3), with a total of 226 nodes and 1330 edges. By Network Analyzer analysis, the top 5 key active ingredients were quercetin, kaempferol, β-sitosterol, luteolin, and stigmasterol (Table 1).

Table 1 - Top 5 key active ingredients by degree value.
MOL ID Active ingredient Degree Affiliated herbs
MOL000098 Quercetin 122 Ephedrae herba, Licorice
MOL000422 Kaempferol 116 Ephedrae herba, Paeoniae radix alba, Licorice, Asari radix et rhizoma
MOL000358 β-sitosterol 80 Zingiberis rhizoma, Cinnamomi ramulus, Ephedrae herba, Paeoniae radix alba, Arum ternatum thunb
MOL000006 Luteolin 26 Ephedrae herba
MOL000449 Stigmasterol 24 Ephedrae herba, Arum ternatum thunb

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Figure 3.:
Active ingredient-intersection target network. The ovals represent active compounds, and the rectangles represent targets.

3.4. Construction of the PPI network and core targets screening

The 92 intersection targets of XQLD in the treatment of IA were introduced into STRING database to analyze the protein interaction of the potential targets of XQLD in the treatment of IA, and the results were introduced into Cytoscape 3.7.2 for visualization (Fig. 4). The average degree, betweenness centrality and closeness centrality were 20.696, 0.010, and 0.521 respectively, among which 40 parameters of targets were above the average, and the topologic parameters of the top 10 key proteins were shown in Table 2. Therefore, we speculated that targets such as interleukin 6 (IL6), cystatin 3 (CASP3), estrogen receptor 1 (ESR1), hypoxia inducible factor 1A (HIF1A), HSP90AA1 and epidermal growth factor receptor (EGFR) play a significant regulatory role in XQLD treating IA.

Table 2 - Topology parameters of the top 10 key targets in the PPI network.
Target Betweenness centrality Closeness centrality Degree
IL6 0.138512 0.754237 60
CASP3 0.054739 0.717742 54
ESR1 0.050779 0.700787 54
HIF1A 0.030726 0.689922 52
HSP90AA1 0.04699 0.684615 51
EGFR 0.032718 0.679389 49
MYC 0.021697 0.674242 49
CCND1 0.019305 0.654412 48
PPARG 0.05526 0.669173 47
FOS 0.029722 0.659259 44
CASP3 = cystatin 3, EGFR = epidermal growth factor receptor, ESR1 = estrogen receptor 1, HIF1A = hypoxia inducible factor 1A, IL6 = interleukin 6, PPI = protein-protein interaction.

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Figure 4.:
PPI network of XQLD in the treatment of IA. The size and color of the nodes indicate the different degree. IA = infantile asthma, PPI = protein-protein interaction, XQLD = Xiaoqinglong decoction.

3.5. GO enrichment analysis and KEGG enrichment analysis

The R software was used to analyze the GO function and KEGG pathway enrichment of the intersection targets. There were 127 items of GO enrichment analysis, including 405 biological processes, 63 cellular components, and 107 molecular functions, Supplemental Digital Contents 3 and 4, https://links.lww.com/MD/1335; https://links.lww.com/MD/1336. Biological process was mainly related to positive regulation of transcription from ribonucleic acid polymerase II promoter, positive regulation of gene expression, and positive regulation of cell proliferation. Cellular component was associated with nucleus, cytosol, and cytoplasm. Molecular function was mainly connected with protein binding, identical protein binding, and enzyme binding (Fig. 5). One hundred twenty-five pathways were obtained by KEGG enrichment analysis, among which the top 20 KEGG pathways were screened out according to P value (Fig. 6). The results of KEGG enrichment showed that it was related to apoptosis, IL-17 signal pathway, tumor necrosis factor (TNF) signal pathway and P13K-Akt signal pathway. The R software was used to analyze the target pathways, and the mechanism of apoptosis and TNF signal pathway was shown in Figures 7 and 8, among which the red mark was the potential target of XQLD in treating IA.

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Figure 5.:
GO function enrichment analysis. GO = Gene Ontology.
F6
Figure 6.:
KEGG pathway enrichment analysis. KEGG = Kyoto Encyclopedia of Genes and Genomes.
F7
Figure 7.:
Mechanism of apoptosis signal pathway. Core targets are marked in red.
F8
Figure 8.:
Mechanism of TNF signal pathway. Core targets are marked in red. TNF = tumor necrosis factor.

3.6. Molecular docking

According to the results of network pharmacology, the top 5 key active ingredients including quercetin, kaempferol, β-sitosterol, luteolin, and stigmasterol were docked with the top 6 core targets including IL6, CASP3, ESR1, HIF1A, HSP90AA1, and EGFR. The result of molecular docking was represented by heat map (Fig. 9), and the unit of docking result was kcal·mol−1. If the binding energy is <0, it means that ligand and receptor can spontaneously bind, and the smaller the value, the higher the binding activity. The deeper the color was, the better the binding activity between the ingredients and the targets was. The result showed that most of the key active ingredients of XQLD had better binding activity with key targets in the treatment of IA. After selecting the binding energy <−6 kcal mol−1, the simulation diagram of molecular docking was constructed by PyMOL software (Fig. 10).

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Figure 9.:
Binding energy heat map of core active ingredients and core targets.
F10
Figure 10.:
Visualization result of molecular docking.

Combined with the docking and PyMOL visualization results, the docking accuracy between the key active ingredients and its key target proteins was calculated. Luteolin bound to EGFR by 7 hydrogen bonds between it and LYS-745, GLN-791, MET-793, ASN-842, and ASP-855. Other forces including π-π stacked bonds between it and ALA-743, LEU-718 and LEU-844 were also found. The β-sitosterol was attracted to CASP3, ESR1 and EGFR by alkyl, π-alkyl, van der Waals forces and hydrogen bond, while the hydrogen bonding as the main force of interaction. Stigmasterol was attracted to EGFR by 6 π-alkyl between it and LYS-806, PHE-910 and MET-987, as well as hydrogen bond between it and THR-909. When encountered to HIF1A, it formed 1 hydrogen bond with ARG-51 and alkyl.

4. Discussion

IA is a common chronic respiratory disease characterized by airway hyperresponsiveness, chronic airway inflammation, and airway remodeling.[7] The functions of children are not yet perfect, so the defensive qi instability results in being invaded by external evils, unclean diet breeds turbid phlegm, which mutually accumulate to induce asthma.[8] Compared with the treatment of Western medicine, syndrome differentiation and treatment of traditional Chinese medicine considers from the perspective of overall concept, featuring its unique advantages and characteristics. Based on network pharmacology and molecular docking, this study revealed the mechanism of XQLD in the treatment of IA from multi-targets and multi-pathways, and discussed the key active ingredients, potential targets and pathways of XQLD in the treatment of IA.

Active ingredients of XQLD were searched and screened through database, and the active ingredient-intersection target network was further constructed and analyzed, which obtained top 5 key active ingredients including quercetin, kaempferol, β-sitosterol, luteolin, and stigmasterol. Studies have shown that airway epithelial cell activation may lead to airway hyperresponsiveness and airway remodeling, while kaempferol can inhibit eosinophil infiltration and airway inflammation by blocking NF-κB signal transduction.[9] In guinea pig asthma model, β-sitosterol exerted its anti-asthma effect by inhibiting the reaction of T helper cell type 2 (Th2) and the synthesis and release of Th2 cytokines, significantly increasing the tidal volume and decreasing the respiratory rate, which was about the same level as the control group.[10] Luteolin can effectively reduce the expression of IgE, alleviate pulmonary inflammation and asthma symptoms by inhibiting the synthesis and excessive secretion of pro-inflammatory cytokines such as IL-6 and TNF-α.[11] Through the topology analysis of the PPI network, the core targets including IL6, CASP3, ESR1, HIF1A, HSP90AA1 and EGFR were screened. IL-6 is an inflammatory factor, which participates in many pathological processes such as inflammatory response and cellular immunity. Clinical experiments have found that overexpression of IL-6 in asthma patients induces compensatory hyperplasia such as alveolar walls thickening and lung interstitium increasing, and also stimulates a variety of inflammatory factors, which finally leads to pulmonary fibrosis.[12] ESR1 is an estrogen receptor expressed in pulmonary myofibroblasts. When ESR1 is activated by estrogen, it will lead to phosphorylation of Raf1 and extracellular signal-regulated kinase, and inhibit the proliferation of pulmonary myofibroblasts. Therefore, estrogen can be used as a replacement therapy for female patients with asthma.[13] EGFR can downregulate the expression of Claudin1 in bronchial epithelial cells, destroy the function of respiratory epithelial barrier and lead to excessive mucus secretion.[14]

KEGG pathway enrichment analysis shows that XQLD in the treatment of IA is related to apoptosis, IL-17 signal pathway, TNF signal pathway, P13K-Akt signal pathway, etc. The main pathological features of asthma patients are excessive cellular response of Th2 and specific IgE driven airway hyperresponsiveness.[15] Asthma can be pathologically divided into Th2-high type (eosinophil) and Th2-low type (non-eosinophil) according to the content of eosinophils in sputum.[16] Th17 cells are the key participants of Th2-low type, which are differentiated by T lymphocyte precursors stimulated by a variety of cytokines, and can secrete a variety of inflammatory cytokines, among which IL-17 is the most iconic effector.[17] When IL-17 is activated in airway smooth muscle cells, it releases a variety of bioactive substances such as elastase, which leads to lung tissue destruction and mucus oversecretion, and induces airway hyperresponsiveness, playing an important role in airway remodeling in asthma patients.[18,19] P13K-Akt signaling pathway participates in the regulation of Th17 cells, which can affect the development of proliferation, aggregation, activation, and apoptosis of inflammatory cells, so as to inhibit the dominant differentiation of Th17 as well as decrease the level of inflammatory factor IL-17.[20] The activation of TNF pathway plays a role through NF-κB signal pathway, resulting in the overexpression of IL-1, IL-6, IL-8, TNF-α, and chemokines, thus aggravating inflammatory and immune responses.[21] Among them, TNF-α is released by Th2 and neutrophils, which can accelerate the aggregation of inflammatory cells such as neutrophils and vascular endothelial cells, and stimulate immune cells to release IL-1β and IL-6.[22]

We performed molecular docking to verify whether the key active ingredients of XQLD have good binding activity with the core targets of IA. When the binding energy is <0, the small molecular ligand can bind to the protein receptor spontaneously, and the smaller the number is, the stronger the binding ability is.[23] The results of molecular docking showed that most of the binding energies of 30 pairs of results performed by simulation docking are <−5.0 kcal·mol−1, which means that the active ingredients of XQLD have a good affinity with the targets. The binding energies of β-sitosterol with CASP3, ESR1 and EGFR are all <−6.0 kcal·mol−1, and the binding energy of stigmasterol with HIF1A is the lowest: −6.9 kcal·mol−1. Studies found that β-sitosterol shows good pharmacological activities in anti-inflammation, antioxidation, reducing blood lipids and regulating immunity, which helps to treat IA.[24] Quercetin can reduce tracheal inflammatory reaction by downregulating the levels of IL-4, IL-5, and miR-155. Experiments showed that stigmasterol could significantly reduce eosinophils, lymphocytes and mononuclear cells in guinea pig model of asthma. It has a significant therapeutic effect on IA by reducing the infiltration of inflammatory cells around bronchi, blood vessels and alveoli.[25] The above combination may play an important role in the treatment of IA with XQLD.

5. Conclusion

Inhaled glucocorticoids are preferred in the asthma guidelines for the treatment of IA, which can improve chronic airway inflammation and reduce abnormal hypersecretion of airway mucus for asthma, as well as long-acting β2 agonists and leukotriene receptor antagonists.[26] However, when these drugs are used, they are prone to recurrence if discontinued, and their long-term use may affect the growth and development of children,[27] and compliance is poor.[28] Therefore, there is an urgent need to find a fully effective treatment for IA.

In Chinese medicine, XQLD has the efficacy of pungent warming to relieve superficial symptoms, warming the lung and resolving drinks, and is mainly used to treat external cold and internal drinks, but its pharmacological mechanism of action in treating IA is still unclear. The multi-component, multi-target and multi-pathway model of Chinese medicine is consistent with the systematic and holistic nature of network pharmacology. Therefore, this study explores the molecular mechanism of XQLD in the treatment of IA based on network pharmacology, which can lay a theoretical foundation for expanding its application in clinical practice and subsequent research.

The results of this study confirmed that key active ingredients such as quercetin, kaempferol, β-sitosterol, luteolin, stigmasterol in XQLD may act on potential core targets such as IL6, CASP3, ESR1, HIF1A, HSP90AA1, EGFR, participating in apoptosis, IL-17 signal pathway, TNF pathway, P13K-Akt signal pathway, and so on. This study has a certain feasibility and reliability, which provides a new idea for the treatment of IA, but the data in this study were mainly obtained from databases, which may be incomplete and need to be combined with literature search for screening and supplementation; the target prediction database is not perfect and has certain limitations, and further animal experiments and clinical trials are needed to verify the prediction results.

Author contributions

Conceptualization: Daman Chen, Zehuan Yuan, Xiaohong Lin.

Data curation: Qiqi Chen, Yuxin Huang, Zehuan Yuan, Yujia Cai, Sitong Li.

Funding acquisition: Xiaohong Lin.

Methodology: Kaibo Zhao, Yongqi Guo, Zehuan Yuan, Yujia Cai.

Project administration: Daman Chen, Xiaohong Lin.

Writing – original draft: Daman Chen, Qiqi Chen, Kaibo Zhao, Yongqi Guo, Yuxin Huang, Sitong Li, Jiarong Xu, Xiaohong Lin.

Writing – review and editing: Daman Chen, Qiqi Chen, Kaibo Zhao, Yongqi Guo, Xiaohong Lin.

Abbreviations:

CASP3 =
cystatin 3
DL =
drug-likeness
EGFR =
epidermal growth factor receptor
ESR1 =
estrogen receptor 1
GO =
Gene Ontology
HIF1A =
hypoxia inducible factor 1A
IA =
infantile asthma
IL =
interleukin
KEGG =
Kyoto Encyclopedia of Genes and Genomes
OB =
oral bioavailability
PPI =
protein-protein interaction
TCMSP =
Traditional Chinese Medicine Systems Pharmacology
Th2 =
T helper cell type 2
TNF =
tumor necrosis factor
XQLD =
Xiaoqinglong decoction

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Keywords:

infantile asthma (IA); molecular docking; network pharmacology; Xiaoqinglong decoction (XQLD)

Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.