Network Pharmacology Analysis of Xuanfei Baidu Granule in the Treatment of Intestinal Flora Disorder

Miao, Yaodong; Chen, Rui; Zhang, Zeyu; Liu, Yaoyuan; Yang, Fengwen; Zhang, Junhua

doi:https://doi.org/10.1155/2022/7883756

Advanced Gut & Microbiome Research

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Abstract Introduction Data and Methods Results and Analysis Discussion Conclusion Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2022 | Article ID 7883756 | https://doi.org/10.1155/2022/7883756

Network Pharmacology Analysis of Xuanfei Baidu Granule in the Treatment of Intestinal Flora Disorder

Yaodong Miao,^1,2Rui Chen,³Zeyu Zhang,⁴Yaoyuan Liu,⁴Fengwen Yang,⁵and Junhua Zhang⁶

Academic Editor: Jian Wu

Received06 Jun 2022

Accepted07 Aug 2022

Published11 Oct 2022

Abstract

Objective. This study is aimed at analyzing the molecular mechanism of Xuanfei Baidu Granule (XFBDG) in the treatment of intestinal flora disorder based on network pharmacology. Methods. The TCMSP database was used to obtain the active components and target proteins of XFBDG, while the GeneCards database was used to obtain the related proteins of intestinal flora disorder. The Rx64 4.0.2 software was used to analyze the GO functional enrichment and KEGG pathway enrichment of drug component target protein and disease-related protein to obtain the pathway-enriched proteins and screen the core proteins for topology analysis of the pathway target by using the STRING database and Cytoscape v3.8.2 software. The Cytoscape v3.8.2 software was used to analyze the relationship between each component and enriched protein, and the AutoDock Vina software was used for molecular docking of core proteins and components. Results. XFBDG contains 133 active components that can act on 249 proteins related to intestinal flora disorder. The effects include the following: (i) regulation of functions—the response to drug, cellular response to chemical stress, response to oxidative stress, and RNA polymerase II-specific DNA-binding transcription factor binding and (ii) regulation of signaling pathways such as the IL-17 signaling pathway, TNF signaling pathway, and Th17 cell differentiation pathway. The enriched core proteins in these pathways are IFNG, IL4, PTGS2, JUN, and IL1B that set in a higher level of binding with the corresponding drug components. Conclusion. XFBDG can act on IFNG, IL4, PTGS2, JUN, and IL1B proteins through its active components such as quercetin, luteolin, and kaempferol to regulate the IL-17, TNF, and Th17 cell differentiation pathways and further regulate the response to drug, cellular response to chemical stress, response to oxidative stress, and RNA polymerase II-specific DNA-binding transcription factor binding. In addition, owing to its antioxidant and anti-inflammatory properties and related immune responses, XFBDG can achieve a balance of intestinal flora and microbial metabolism.

1. Introduction

Xuanfei Baidu Granule (XFBDG) is an effective prescription developed by academician Zhang Boli to cope with the coronavirus disease 2019 (COVID-19) pandemic, which has been entered into the “The Diagnosis and Treatment Program of Coronavirus Pneumonia (A Trial Version of the Sixth and Seventh Edition).” Its prescription includes the classic prescription of traditional Chinese medicine (TCM) ingredients including Maxingshigan Decoction (MXSGD), Maxingyigan Decoction (MXYGD), Tinglidazao Xiefei Decoction (TLDZXFD), and Qianjin Weijing Decoction (QJWJD). XFBDG can ventilate the lung to eliminate dampness, clear heat for expelling pathogenic factors from the exterior, remove heat from the lung, and carry out overall detoxification. The most important function of XFBDG is to treat the symptoms of stagnated lungs due to noxious dampness; accordingly, it has been widely used with a significant curative effect as a first-line COVID-19 therapy. The classic theory of TCM states that “the lungs are associated with the large intestine which is mainly in charge of transportation.” Furthermore, “the lungs and the large intestine are intertwined in a mutual relationship,” which means that both organs interact with and are influenced by each other, both physiologically and pathologically. Intestinal microbes and their metabolites are closely related to human health, and this is consistent with the recognition of modern medicine on the relationship between intestinal microbes and respiratory diseases. Therefore, maintaining intestinal microbial homeostasis has great significance for the prevention and treatment of pulmonary diseases: (i) microecological experiments have proven that some flora can change synchronously in the pulmonary or intestinal diseases of rats, which indicate that the change of microecological flora could be one of the ways and manifestations of “pulmonary and intestinal diseases” [1], (ii) modern medicine believes that various respiratory diseases can be prevented by regulating intestinal flora and intestinal immunity, suggesting that the gut-lung axis could be the bridge between the lung and large intestine [2–4], (iii) MXSGD can regulate Th1/Th2 immune balance, increase the numbers of Bifidobacteria and Lactobacillus, improve intestinal flora, and relieve clinical symptoms of bronchial asthma [5], (iv) MXSGD combined with azithromycin also has noticeable efficacy in the treatment of mycoplasma pneumonia for children, which can relate to the improvement of immune function by increasing anti-inflammatory factors and decreasing proinflammatory factors [6], and (v) QJWJD has similar immune effects on the decomposition of intestinal flora and filamentous bacteria, both of which can be affected by the expression of Th17 cell genes and proteins [7, 8].

Network pharmacology has become a new strategy for drug research, as it can accurately predict and analyze the mechanism of action of TCM compounds by interpreting the regulation mechanism of drugs on diseases from micro to macrodimensions. In addition, molecular docking can calculate the affinity between the receptor and ligand and some forms of binding, by which the results can be evaluated and screened. Given the efficacy of the classic prescription combined to formulate XFBDG for the treatment of intestinal flora disorder, this study adopts network pharmacology to explore the molecular mechanism of the prescription in the treatment of intestinal flora disorder, aiming to provide clues and ideas for subsequent experiments and clinical research.

2. Data and Methods

2.1. Ingredient Screening and Target Protein Acquisition

The following were considered as the conditions from the TCMSP database (http://tcmspw.com/tcmsp.php) to screen the effective components and target proteins of XFBDG (except gypsum): , , , , , and [9, 10]. The main component CaSO4 target protein of gypsum was screened from the SEA database (https://sea.bkslab.org/), and the last step was to import all target proteins into the UniProt database (https://www.uniprot.org/) for standardization of their names.

2.2. Intersection Targets of Acquisition of “Disease-Related Protein” and “Effective Component Target Protein”

“Intestinal flora disorder”, “Dysbiosis of the intestinal flora,” and “Intestinal dysbiosis” were selected as the search term from the GeneCards database (http://www.genecards.org/) to obtain the disease-related proteins and void intersection with target protein of XFBDG, which was finally saved as a file and named Drug-Disease.

2.3. Analysis of GO Functional Enrichment and KEGG Pathway Enrichment

Drug-Disease was analyzed using the Rx64 4.0.2 software with as the screening condition for GO functional enrichment analysis and KEGG pathway enrichment analysis. GO functional enrichment analysis mainly includes biological process (BP), molecular function (MF), and cellular component (CC). The top 10 functions of each of the three sections obtained through GO enrichment analysis are presented as bar charts, while the first 30 pathways obtained through KEGG pathway enrichment analysis are presented as bubble maps (the ordinate is the pathway name, the abscissa is the gene proportion, the circle area represents the number of enriched genes, and the color represents the enrichment degree, with darker red representing more noticeable enrichment). A literature search about disease-related pathways was carried out using PubMed (https://pubmed.ncbi.nlm.nih.gov/), and data on enriched proteins were obtained from the KEGG enrichment results. The STRING database and Cytoscape v3.8.2 software were used to screen the enriched core proteins and to make path-target topology analysis on the conditions that the degree value, degree of mediator, density, centrality, and the local-edged connectivity of network were all higher than the median level.

2.4. Network Construction of a Component-Target Topology Analysis

The active components and pathway-enriched proteins of XFBDG were imported into the Cytoscape v3.8.2 software and then processed in the visualization method to construct the component-target network in which the node represents compounds and targets and the line represents the interaction relationship between nodes.

2.5. Molecular Docking Verification and Screening

In molecular docking, the enriched core protein was used as the receptor, while the corresponding TCM component was used as the ligand. The 2D structure of TCM components was transformed into the 3D structure with the Chem3D.exe software, and its structure was optimized and saved as lig.mol2. The crystal structure of the target protein was obtained through the PDB database (http://www.rcsb.org/), and it was treated by PyMolwin.exe software to remove H₂O and small molecule ligands and saved as rep.pdb. The two files of rep.pdb and lig.mol2 were imported into AutoDockTools 1.5.6 software and transformed into PDBQT format to fix the active position. As Autodock Vina was used for molecular docking to select the components that have the lowest docking affinity with the target protein, PyMOLWin.exe software was used to visualize the docking results.

3. Results and Analysis

3.1. Effective Component and Target Protein of XFBDG

There are 132 kinds of active ingredients (except gypsum) in XFBDG according to the TCMSP database, including 12 kinds of Ephedra, nine kinds of bitter apricot seed, six kinds of the seed of Job’s tears, two kinds of Rhizoma Atractylodis, six kinds of patchouli, 17 kinds of sweet wormwood herb, seven kinds of Polygonum cuspidatum, eight kinds of European verbena herb, one kind of reed rhizome, five kinds of Lepidium seed, seven kinds of pomelo peel, and 81 kinds of root of Ural licorice (Table 1). The main component of gypsum is CaSO₄, and 249 kinds of effective component target proteins were obtained after protein prediction and standardized treatment.

3.2. Intersection Target of “Intestinal Flora Disorder-Related Protein” and “Target Protein of XFBDG”

406 proteins related to intestinal flora disorder were obtained from the GeneCards database, and 57 proteins were obtained after the intersections with 249 drug target proteins (Figure 1).

3.3. GO and KEGG Enrichment Analysis

The results of GO and KEGG enrichment analysis showed the following: GO functional enrichment analysis revealed a total of 2001 functional items (Figure 2), among which there were (1) 1829 BP, mainly including response to the drug, cellular response to chemical stress, response to the metal ion, response to oxidative stress, response to lipopolysaccharide, and response to molecule of bacterial origin; (2) 30 CC, mainly relating to transcription regulator complex, vesicle lumen, and membrane raft; and (3) 142 MF, mainly involving RNA polymerase II-specific DNA-binding transcription factor binding, DNA-binding transcription factor binding, and cytokine activity. The KEGG pathway enrichment analysis revealed a total of 152 signaling pathways (Figure 3). IL-17 signaling pathway [11], TNF signaling pathway [12], and Th17 cell differentiation [13] have the closest relation with intestinal microflora disorder. The interaction network of pathway-enriched proteins was constructed (Figure 4(a)) in which the yellow node represents core proteins and the red node represents related proteins, the blue triangle represents the pathways related to intestinal flora disorder, the red circular node represents the general enrichment proteins, and the yellow circular node represents core enrichment protein in the pathway-target topology analysis network (Figure 4(b)). Therefore, IFNG, IL4, PTGS2, JUN, IL1B, IL6, TNF, RELA, and CASP3 appear to play key roles in regulating the IL-17, TNF, and Th17 cell differentiation signaling pathways.

(a)

(b)

3.4. Network Construction of Drug Component-Target Protein

The results of the drug component-target protein topological analysis network (Figure 5) show that the network contains 151 nodes and 307 connection lines. In the figure, the inside matrix represents the drug effective components: cyan is the root of Chinese licorice, dark green is the seed of Job’s tears, orange is sweet wormwood herb, gray is patchouli, brown is Ephedra, blue is Lepidium seed, blue gray is bitter apricot seed, purple is Polygonum cuspidatum, pink is pomelo peel, and light blue is Rhizoma Atractylodis. Multicolored nodes represent the components that drugs commonly have, while circular structures represent the pathway-enriched proteins. For example, red is the general enriched protein, and yellow is the core enriched protein. The results show that the main components of this prescription are quercetin, luteolin, wogonin, kaempferol, and irisolidone, and PTGS2 is the top one strongly regulated by drugs among the core proteins.

3.5. Molecular Docking between the Core Target and the Drug Effective Ingredient

The affinity between receptor and ligand that goes lower than -5 kJ·mol^-1 indicates that the receptor and ligand have a good binding ability [14]. The docking accuracy between the core target protein and corresponding main components was verified by the molecular docking experiment. The affinity between the target protein and the corresponding compound was <-5 kJ·mol^-1 (Table 2), and the molecular docking pattern constructed with the target protein and the compound with the strongest affinity (Figure 6) showed that there was a good binding ability between the drug component and the target.

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(b)

(c)

(d)

(e)

(f)

(g)

(h)

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4. Discussion

XFBDG is a compound prescription of MXSGD, MXYGD, TLDZXFD, and QJWJD and works by ventilating the lungs to eliminate dampness, clearing heat to expel pathogenic factors from the exterior, removing heat from the lung, and detoxifying. According to TCM, “the lungs and the large intestine are intertwined in a mutual relationship,” which means that both organs interact with and are influenced by each other, both physiologically and pathologically. Intestinal flora not only affects the maturation and development of the host immune system but also affects the stability of the host metabolic homeostasis through the cross-communication of microbial metabolites or cometabolites. Our study suggests that alteration of microbiological flora could be one of the manifestations of “pulmonary and intestinal disease.” Modern medicine believes that various respiratory diseases can be prevented by regulating intestinal flora and immunity system, suggesting that the “gut-lung” axis could be the bridge between the lung and large intestine. MXSGD could alleviate bronchial asthma by improving the intestinal flora and has noticeable efficacy in the treatment of pediatric mycoplasma pneumonia with azithromycin. QJWJD has similar immune effects on the decomposition of intestinal flora and filamentous bacteria. Using network pharmacology, it has been possible to make multiple clarifications regarding the action mechanism of drugs, and molecular docking has helped calculate the affinity between receptors and ligands. Therefore, with the help of network pharmacology and molecular docking methods, this study preliminarily explored the specific mechanisms such as components, targets, and pathways involved in the treatment of intestinal flora disorders by XFBDG.

Based on the GO functional enrichment analysis, it was found that XFBDG has a therapeutic effect on intestinal flora disorder involving the regulation of response to oxidative stress, response to the drug, cellular response to chemical stress, and other functions. For instance, response to oxidative stress refers to the imbalance in the generation and metabolism of oxygen free radicals in tissues. This can cause oxidative damage induced by the accumulation of reactive oxygen species (ROS) and the ratio disproportion between antioxidant enzymes and lipid peroxides. ROS can activate/inhibit a series of signaling pathways which, in turn, can cause pathological changes such as the proliferation and migration of pulmonary vascular smooth muscle cells (PASMC), pulmonary endothelial cells (PAEC) disorder, in situ thrombosis, inflammation, pulmonary vascular remodeling, vasoconstriction response, and extracellular matrix deposition [15, 16]. According to the KEGG pathway enrichment analysis, XFBDG has proven effective in inhibiting the development of intestinal flora disorder by regulating the IL-17, TNF, and Th17 cell differentiation signaling pathways. Furthermore, stimulating the secretion of cytokines IL-17 can (i) increase the number of intestinal epithelium lymphocytes and enrich the availability and diversity of probiotics, (ii) lower the levels of pathogenic bacteria, (iii) enhance the intestinal mucosal immunity of rats, (iv) improve the intestinal inflammation and the intestinal flora disorders in barrier function and adjustment, and (v) especially promote the growth of beneficial intestinal flora, adjust the flora structure, and restore the intestinal immune function [11, 17, 18]. Hypoxia exposure can significantly aggravate the symptoms and pathological damage in rats. Downregulating the Th1 and Th17 responses in rats with colitis to affect the immune function and regulate Th17/Treg signaling pathway can both restore the homeostasis of intestinal flora in rats. Meanwhile, regulating the abundance, diversity, and composition of intestinal flora can also restore the balance of Th17/Treg to improve the survival status of rats [13, 18–20]. The growth and abundance of intestinal flora are correlated with the level of TNF-α. The stronger the expression of TNF-α, the larger the numbers of Escherichia coli, Enterococcus faecalis, and Bacteroides fragilis and the smaller the numbers of Bifidobacterium and Lactobacillus. Therefore, reducing the expression of proinflammatory factors can improve the intestinal flora of rats [12, 21–23].

The main components of XFBDG including quercetin, luteolin, and kaempferol are obtained through enriched core protein screening, pathway-target topology analysis, component-target topological analysis, and molecular docking; the above pathways are regulated by intervening core proteins such as IFNG, IL4, PTGS2, JUN, and IL1B. Modern pharmacological studies have shown that quercitrin is a member of the flavonoid family with antioxidant and anti-inflammatory effects and is also regarded as a prebiotic with antibacterial effects, which can significantly affect the intestinal environment and regulate intestinal flora. Flavonoid glycosides can be hydrolyzed by the intestinal flora, and quercetin can be transformed into corresponding aglycones under the metabolic action of human intestinal bacteria. Therefore, the content of flavonoid aglycone with strong anticomplement activity is significantly increased and thus can change the metabolic function of rat intestinal flora. In particular, the intestinal microbiota closely relates to human diseases (such as increasing the proportion of Clostridium and lactic acid bacteria and reducing the proportion of E. coli), affects the metabolic homeostasis of rat intestinal microbiota host, and helps to improve the enzyme system of human intestinal microbiota metabolism and response mechanism [24, 25]. Luteolin is a kind of flavonoid and studies about its effects on lipid metabolism disorder and intestinal flora composition in rats fed a high-fat diet shows that luteolin combined with metformin hydrochloride can decrease the proportion of Firmicute and Bacteroidetes (F/B), to increase the relative abundance of Lachnospiraceae, Helicobacteraceae, algae, and Peptococcaceae as well as alleviate lipid metabolism disorder and optimize the composition of intestinal flora in high-fat diet rats. In addition, luteolin can enhance the intestinal barrier by decreasing the level of reactive oxygen species (ROS), increasing the activity of superoxide dismutase (SOD) and glutathione (GSH), and inhibiting the secretion of proinflammatory cytokines [26, 27]. Kaempferol is a natural flavanol with multiple pharmacological activities. Metabolomic studies have shown that kaempferol treatment can significantly reverse the interference of energy production and metabolites that are involved in tryptophan, fatty acids, and secondary bile acids in the intestinal contents of rats, and can, to a large extent, restore the imbalance of intestinal flora and microbial metabolism of rats to achieve the regulation effects of anti-inflammatory and immune response [24, 28, 29]. Although this study only applies network pharmacology and molecular docking technology to analyze the capacity of drug active components in absorption and binding and have not considered the content and interaction of drug active components in the compound prescription, the results can still provide a general referential direction for clinical and experimental research.

5. Conclusion

XFBDG is advantageous in the treatment of intestinal flora disorder with multicomponents, multitargets, and multipathways. Using the network pharmacology method to analyze the molecular mechanism by which XFBDG can treat intestinal flora disorder, this study found that the main mechanism is likely via quercetin, luteolin, kaempferol, and other active components that act on IFNG, IL4, PTGS2, JUN, IL1B, and other core proteins to regulate the IL-17, TNF, and Th17 cell differentiation signaling pathways. This ensures balance of the intestinal flora and microbial metabolism, which helps to further fulfill the functions of antioxidation, anti-inflammation, and immune response regulation.

Data Availability

The data is available and will be provided upon request to the corresponding authors.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Authors’ Contributions

Yaodong Miao, Zeyu Zhang, and Yaoyuan Liu contributed to writing of the original draft. Yaodong Miao, Rui Chen, and Fengwen Yang contributed to writing-review and editing. Junhua Zhang contributed to study conception and design, investigation, and supervision.

Acknowledgments

The authors greatly appreciate the financial support from Foundation of State Key Laboratory of Component-Based Chinese Medicine (Grant No. CBCM2020203), which ensured the accomplishment of the work.

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