1. 1Department of Traditional Chinese Medicine, First Clinical Medical College, Jiangsu University, Zhenjiang, China
2. 2Department of Warm Disease, Basic Medical College, Nanjing University of Chinese Medicine, Nanjing, China Correspondence should be addressed to Minye Qu; [email protected] Received 28 March 2022; Accepted 22 June 2022; Published 9 July 2022 Academic Editor: Shih-Chao Lin

Copyright © 2022 Minye Qu et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Objective. To explore the potential mechanisms of Yupingfeng Powder (YPFP) in the treatment of allergic diseases by using network pharmacology and molecular docking technology. Methods. e active components and targets of YPFP were screened by the TCMSP database. e targets associated with atopic dermatitis, asthma, allergic rhinitis, and food allergy were obtained from GeneCards and OMIM databases, respectively. e intersection of the above disease-related targets was identified as allergyrelated targets. en, allergy-related targets and YPFP-related targets were crossed to obtain the potential targets of YPFP for allergy treatment. A protein-protein-interaction (PPI) network and a drug-target-disease topology network were constructed to screen hub targets and key ingredients. Next, GO and KEGG pathway enrichment analyses were performed separately on the potential targets and hub targets to identify the biological processes and signaling pathways involved. Finally, molecular docking was conducted to verify the binding affinity between key ingredients and hub targets. Results. In this study, 45 active ingredients were identified from YPFP, and 48 allergy-related targets were predicted by network pharmacology. IL6, TNF, IL1B, PTGS2, CXCL8, JUN, CCL2, IL10, IFNG, and IL4 were screened as hub targets by the PPI network. However, quercetin, kaempferol, wogonin, formononetin, and 7-O-methylisomucronulatol were identified as key ingredients by the drug-target-disease topological network. GO and KEGG pathway enrichment analysis indicated that the therapeutic effect of YPFP on allergy involved multiple biological processes and signaling pathways, including positive regulation of fever generation, positive regulation of neuroinflammatory response, vascular endothelial growth factor production, negative regulation of cytokine production involved in immune response, positive regulation of mononuclear cell migration, type 2 immune response, and negative regulation of lipid storage. Molecular docking verified that all the key ingredients had good binding affinity with hub targets. Conclusion. is study revealed the key ingredients, hub targets, and potential mechanisms of YPFP antiallergy, and these data can provide some theoretical basis for subsequent allergy treatment and drug development.

Allergies are a class of recurrent, chronic inflammatory diseases. Over the past few decades, the incidence of allergic diseases has continued to rise, especially in developing countries [1]. Many cross-sectional and longitudinal studies have shown that the occurrence of allergic diseases follows a natural process, including the time evolution from preschool atopic dermatitis and food allergy to school-age asthma and allergic rhinitis, as well as the spatial evolution from the skin and gastrointestinal tract to respiratory tract [2, 3]. With the consensus of the natural process of allergy, the whole-course

management of allergy has been advocated in recent years [4]. However, currently available therapeutic approaches against allergy, such as glucocorticoids, antihistamines, leukotriene inhibitors, and oral immunotherapy can only temporarily control symptoms, but cannot effectively control disease recurrence or inhibit the atopic progression [5, 6]. In addition, long-term use of these drugs has certain side effects [6–8].

Traditional Chinese medicine (TCM) has a long history of treating allergic diseases. e “holistic concept” of TCM emphasizes the correlation between the various components of the human body, which coincides with allergy whole-

course management concept of modern medicine. Due to the good clinical efficacy and few side effects, TCM treatment of allergy is widely used in China and has been gradually accepted worldwide as a major treatment for complementary and alternative medicine [9, 10].

Yupingfeng Powder (YPFP) originated from the ancient Chinese medicine book “Danxi Xinfa,” which is composed of three Chinese herbs: Huangqi, Fangfeng, and Baizhu. In allergic diseases, YPFP shows good effects on both improving symptoms and controlling recurrence [11–13]. It has been confirmed that the glycoside extract of YPFP exerts antiinflammatory and immunological functions by regulating T lymphocyte differentiation subtypes [14]. e Huangqi-Fangfeng drug pair prevents allergic airway remodeling by inhibiting the epithelial-mesenchymal transformation process via regulating the epithelial-derived TGF-β1 [15]. e polysaccharide isolated from Baizhu enhances immunity by promoting the proliferation of CD4, CD8, and Treg cells [16, 17]. However, the TCM compound has the characteristics of multiple components, multiple targets, and multiple pathways. e pharmacodynamic components, effective targets, and molecular mechanisms of YPFP on allergy remain to be further studied.

With the rapid development of system biology and system pharmacology, network pharmacology has transformed the drug research models from “single disease-single target” to “multiple disease-multiple target”, which provides a new way for us to systematically study the pharmacodynamic mechanism of TCM compounds [18, 19]. erefore, in this study, network pharmacology was conducted to predict the active ingredients of YPFP as well as its targets and pathways for allergy treatment. In addition, molecular docking techniques were used to verify the interactions between ingredients and targets. is study aimed to provide a theoretical basis for the potential mechanism of YPFP antiallergy. e workflow is shown in Figure 1.

1. 2.1. Active Ingredient Screening of YPFP. e active ingredients of YPFP were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) (https://tcmspw.com/tcmsp.php), which is a unique TCM systematic pharmacology platform that integrates TCM active ingredients, potential targets, associated diseases, and pharmacokinetic data. Using “Huangqi,” “Fangfeng,” and “Baizhu” as keywords, oral bioavailability (OB) ≥30% and drug-likeness (DL) ≥0.18 as screening conditions, a total of 45 active ingredients were obtained. Download the molecular structures of the screened active ingredients to prepare for subsequent molecular docking.
2. 2.2. Target Prediction of Active Ingredients. Targets corresponding to the active ingredients of YPFP were predicted from TCMSP and translated into gene names using UniProtKB (https://www.uniprot.org). After removing duplicate genes, 221 YPFP-related target genes were obtained.

1. 2.3. Allergy-Related Target Gene Collection. Allergy-related target genes were searched for the keywords “atopic dermatitis,” “atopic eczema,” “asthma,” “allergic rhinitis,” and “food allergy” by GeneCards (https://www. genecards.org) and OMIM (https://www.omim.org). e data from the two databases were merged to remove the duplicates, and the related genes for each keyword were obtained. Cross the five keyword-related genes by “UpSet” and “VennDiagram” R package to obtain allergy-related target genes.
2. 2.4. Clustering of YPFP and Allergy-Related Target Genes. Venny2.1 (https://bioinfogp.cnb.csic.es/tools/venny) was used to cluster YPFP-related target genes and allergy-related target genes, and the obtained overlaps were considered as potential target genes of YPFP therapy for allergy.
3. 2.5. PPI Network Construction and Hub Gene Extraction. e PPI network was plotted by entering the potential target genes into the STRING database (https://www.string-db. org), with the species set as “Homo sapiens” and a confidence score ≥0.4. Each node in the network represents a protein, and the connection lines between nodes represent functional associations. e relevant results were exported in TSV format and extracted by Cytoscape v_3.9.1, and the top 10 hub genes were identified by the McCreight (MCC) method using the “Cytohubba” plug-in.
4. 2.6. Construction of YPFP-Target-Allergy Topological Network. Cytoscape v_3.9.1 was used to analyze and visualize complex networks among herbs, active ingredients, potential targets, and diseases. By analyzing the network topology parameters, the key ingredients were screened.
5. 2.7. GO and KEGG Pathway Enrichment Analysis. KOBAS 3.0 (https://KOBAS.cbi.pku.edu.cn) was used for the KEGG and GO analyses of the potential genes and hub genes, respectively. e enrichment degree was calculated according to the input number/background number, with P value ≤0.05 and an input number ≥2 as the inclusion criteria. Based on descending order of enrichment degree, the top 15 KEGG pathway and top 15 GO items of potential genes and hub genes were separately plotted as bubble diagrams by the “ggplot2” R package. en Cytoscape v_3.9.1 was used to construct topological networks to identify the common biological functions and signaling pathways of hub genes and potential genes in the top 15 GO and KEGG results. In addition, the “ggalluvial” R package was used to draw the Sankey diagram of hub genes and enriched signal pathways. KEGG Mapper (https://www.genome.jp/kegg/ mapper) is a collection of tools for KEGG mapping, which visualizes the relevant pathways of acquired genes through “Search Pathway” and “Search & Color Pathway” tools. We input potential genes into KEGG Mapper and set different colors (the hub genes are red, the remaining potential genes are green), and then got the most relevant signaling pathway and displayed them.

atopic dermatitis atopic eczema asthma

allergic rhinitis food allergy

Baizhu

Huangqi

Fangfeng

YPFP-related targets

Common targets Allergy-related targets

GO / KEGG Enrichment PPI network YPFP-Target-Allergy network

CB-Dock

Hub genes

pathways and functions

1. 2.8. Molecular Docking of Hub Targets and Key Ingredients. To verify the binding affinity of the hub targets of the PPI network to the key ingredients of the topological network, we performed molecular docking. CB-Dock is an online molecular docking website (https://clab.labshare.cn/cbdock/php/). It predicts the binding region of a given protein, calculates the center and size using a curvation-based cavity detection method, connects with ligand binding sites queried by Autodock Vina, and then sorts binding patterns based on Vina scores and provides interactive 3D visualization of binding patterns. e 3D structures of the hub targets obtained by RSCB PDB and the 2D structures of the key ingredients obtained by TCMSP were uploaded to the CB-Dock website. After automatically identifying cavity size,

calculating center and size, molecular docking, and configurational scoring were performed. Cavity size is the protein-ligand interaction interface predicted by CB-Dock based on the concave surface of protein [20]. Generally, the larger the cavity size is, the higher the affinity between protein and ligand will be [20]. e center and size of the docking box are evaluated according to the cavity center, cavity size, and ligand size, which are key parameters in the process of molecular docking [21]. e binding affinity was evaluated according to the Vina score of the docking results. e greater the absolute value of the Vina score, the more stable the docking module is. e 3D conformation of the target-ingredient docking with a Vina score≤−8.5kcal/mol was downloaded for display.

Table 1: Characteristics of active ingredients in YPFP. Herb name Molecule ID Molecule name

Molecule weight

OB (%)

DL

MOL000211 Mairin 456.78 55.38 0.78 MOL000239 Jaranol 314.31 50.83 0.29 MOL000296 Hederagenin 414.79 36.91 0.75

(3S, 8S, 9S, 10R, 13R, 14S, 17R)-10, 13-Dimethyl-17-[(2R, 5S)-5-propan-2yloctan-2-yl]-2, 3, 4, 7, 8, 9, 11, 12, 14, 15, 16, 17-dodecahydro-1H-cyclopenta[a] phenanthren-3-ol

MOL000033

428.82 36.23 0.78

MOL000354 Isorhamnetin 316.28 49.6 0.31 MOL000371 3, 9-di-O-methylnissolin 314.36 53.74 0.48 MOL000374 5′-Hydroxyiso-muronulatol-2′, 5′-di-O-glucoside 642.67 41.72 0.69

1. MOL000378 7-O-Methylisomucronulatol 316.38 74.69 0.3
2. MOL000379 9,10-Dimethoxypterocarpan-3-O-β-D-glucoside 462.49 36.74 0.92
3. MOL000380

Huangqi (HQ)

(6aR, 11aR)-9, 10-Dimethoxy-6a, 11a-dihydro-6H-benzofurano[3, 2-c] chromen-3-ol

300.33 64.26 0.42

MOL000387 Bifendate 418.38 31.1 0.67 MOL000392 Formononetin 268.28 69.67 0.21 MOL000398 Isoflavanone 316.33 109.99 0.3 MOL000417 Calycosin 284.28 47.75 0.24 MOL000422 Kaempferol 286.25 41.88 0.24 MOL000433 FA 441.45 68.96 0.71

1. MOL000438 (3R)-3-(2-Hydroxy-3,4-dimethoxyphenyl)chroman-7-ol 302.35 67.67 0.26
2. MOL000439 Isomucronulatol-7, 2′-di-O-glucosiole 626.67 49.28 0.62 MOL000442 1, 7-Dihydroxy-3, 9-dimethoxy pterocarpene 314.31 39.05 0.48 MOL000098 Quercetin 302.25 46.43 0.28

(2R, 3R)-3-(4-Hydroxy-3-methoxy-phenyl)-5-methoxy-2-methylol-2, 3dihydropyrano[5, 6-h][1,4] benzodioxin-9-one

386.38 68.83 0.66

MOL000011

MOL011730 11-Hydroxy-sec-o-beta-d-glucosylhamaudol_qt 292.31 50.24 0.27 MOL011732 Anomalin 426.5 59.65 0.66 MOL011737 Divaricatacid 320.32 87 0.32 MOL011740 Divaricatol 334.35 31.65 0.38

1. MOL001941 Ammidin 270.3 34.55 0.22 MOL011747 Ledebouriellol 374.42 32.05 0.51 MOL011749 Phelloptorin 300.33 43.39 0.28 MOL011753 5-O-Methylvisamminol 290.34 37.99 0.25 MOL002644 Phellopterin 300.33 40.19 0.28 MOL000359 Sitosterol 414.79 36.91 0.75 MOL000173 Wogonin 284.28 30.68 0.23 MOL000358 Beta-sitosterol 414.79 36.91 0.75 MOL001494 Mandenol 308.56 42 0.19
2. MOL001942 Isoimperatorin 270.3 45.46 0.23 MOL003588 Prangenidin 270.3 36.31 0.22 MOL007514 Methyl icosa-11,14-dienoate 322.59 39.67 0.23 MOL013077 Decursin 328.39 39.27 0.38

Fangfeng (FF)

1. MOL000020 12-Senecioyl-2E, 8E, 10E-atractylentriol 312.39 62.4 0.22
2. MOL000021 14-Acetyl-12-senecioyl-2E, 8E, 10E-atractylentriol 355.44 60.31 0.31
3. MOL000022 14-Acetyl-12-senecioyl-2E, 8Z, 10E-atractylentriol 356.45 63.37 0.3 MOL000028 α-Amyrin 426.8 39.51 0.76

Baizhu (BZ)

(3S, 8S, 9S, 10R, 13R, 14S, 17R)-10, 13-Dimethyl-17-[(2R, 5S)-5-propan-2yloctan-2-yl]-2, 3, 4, 7, 8, 9, 11, 12, 14, 15, 16, 17-dodecahydro-1H-cyclopenta[a] phenanthren-3-ol

MOL000033

428.82 36.23 0.78

MOL000049 3β-Acetoxyatractylone 274.39 54.07 0.22 MOL000072 8β-Ethoxy atractylenolide III 276.41 35.95 0.21

1. 3.1. Active Ingredients and Targets Screening of YPFP. According to OB≥30% and DL≥0.18, a total of 45 active ingredients of YPFP were screened from the TCMSP database, including 20 from Huangqi, 18 from Fangfeng, and 7 from Baizhu (Table 1). By TCMSP target prediction and

UniProt gene name transformation, 221 YPFP-related target genes were obtained after removing duplicates (Supplementary Table S1).

3.2. Allergy-Related Target Gene Collection. e GeneCards and OMIM databases were searched with the keywords

800

759

452

600

150

12

47

40 20

12

17

10 4

192

62

460452

460

51

369

35

28

400

369

3318

345

59

22

326

78 67 122

23 17

326 20

65 345

759

192

200

150

122

78 67 65 62 59 51 47 40 35 33 28 23 22 20 20 18 17 17 12 12 10 4 0

atopic dermatitis

food allergy

asthma

atopic eczema

allergic rhinitis

2000 1500 1000 500 0 Set Size

1. Figure 2: Allergy-related target genes obtained by clustering target genes corresponding to “atopic dermatitis,” “atopic eczema,” “asthma,” “allergic rhinitis,” and “food allergy.”

“atopic dermatitis,” “atopic eczema,” “asthma,” “allergic rhinitis,” and “food allergy.” When the search results of the two databases were combined (if relevance score >1, duplicates were removed), the target genes corresponding to the 5 keywords were 1140, 1677, 1445, 1912, and 1241, respectively (Supplementary Table S2). By clustering the genes associated with the 5 keywords, 369 shared genes were obtained as allergy-related target genes (Figure 2).

1. 3.3. Potential Target Genes and PPI Network of YPFP erapy for Allergy. YPFP-related target genes and allergy-related target genes were intersected by Venny2.1 to obtain 48 potential genes (Figure 3(a)). ese 48 potential genes were imported into the STRING database to obtain the PPI network (Figure 3(b)). According to the node degree of each protein in the network, the importance priority was analyzed and a bar graph was drawn for visualization (Figure 3(c), Supplementary Table S3). In order to screen hub genes from the potential genes, PPI network files were imported into Cytoscape v_3.9.1, and the top 10 genes were identified as hub genes by the MCC method of the “CytoHubba” plug-in, including IL6, TNF, IL1B, PTGS2, CXCL8, JUN, CCL2, IL10, IFNG, and IL4 (Figure 3(d), Supplementary Table S4).
2. 3.4. YPFP-Target-Allergy Topological Network. Cytoscape v_3.9.1 was used to construct a topological network to

visualize the complex relationship between YPFP active ingredients and allergy-related targets. e YPFP-TargetAllergy network consists of 88 nodes and 478 interactions. ese nodes were 32 YPFP active ingredients, 48 potential targets, 5 keywords of allergy-related diseases, and 3 herbs (Figure 4). e active ingredients were sorted according to the descending order of degree value, and the top 5 were predicted to be the key ingredients, including quercetin, kaempferol, wogonin, formononetin, and 7-O-methylisomucronulatol (Table 2).

3.5. GO and KEGG Pathway Enrichment Analysis of Potential Genes and Hub Genes. To explore the regulatory mechanisms of potential target genes on allergies, we conducted GO and KEGG enrichment analyses and selected the top 15 remarkably enriched biological functions and signal pathways to generate bubble diagrams, respectively (Figure 5).

To further verify the dominant role of hub genes in potential genes, we also performed GO and KEGG enrichment analyses on hub genes and compared the results with those of potential genes. e GO and KEGG enrichment results of the top 15 hub genes were represented by bubble diagrams (Figure 6). In addition, the common enriched pathways and functions of hub genes and potential genes in the top 15 GO and KEGG analyses were displayed by topological networks (Figure 7).

TCM Disease

173 48 321

1. (a)
2. (b)

Figure 3: Continued.

SLC6A4 GSTM1 ADRB2

4

1. 9
2. 10 13

CYP3A4 PTGS1 GSTP1

1. 13
2. 14
3. 15 18 18 18 18

CYP1A1 ALOX5 AR

DPP4 MAPK1

PLAU IRF1 AHR

1. 18
2. 19 21

CD40LG MAPK14

23

1. 26
2. 27
3. 28 28 28

ERBB2 MMP1

NOS2

SELE CXCL10

1. 30

NOS3 ESR1 IL1A

CRP MPO

TGFB1 HMOX1

1. 34
2. 35
3. 36
4. 37
5. 38
6. 39 41

IL2 MMP2

EGFR

ICAM1 VCAM1 NFKBIA

IFNG

IL4 CCL2

IL10 MMP9

JUN PPARG CXCL8

1. 41
2. 42
3. 43

VEGFA

PTGS2 IL1B TP53

1. 43
2. 44
3. 45

TNF IL6

0

10 20 30 40 50

(c)

IL6 TNF

IFNG

IL1B

JUN

CCL2

IL4

PTGS2

IL10

CXCL8

1. Figure 3: Potential target genes and PPI network of YPFP therapy for allergy. (a) e Venny results of potential target genes of YPFP therapy for allergy. (b) e PPI network of 48 potential genes. (c) Count and list of the genes of the PPI network. (d) Hub genes from the PPI network.

GO enrichment analysis of hub genes and potential genes showed that 7 of the top 15 biological functions with the highest enrichment were identical, such as positive regulation of fever generation, positive regulation of neuroinflammatory response, vascular endothelial growth factor production, negative regulation of cytokine production

involved in immune response, positive regulation of mononuclear cell migration, type 2 immune response, and negative regulation of lipid storage.

KEGG enrichment analysis showed that 11 of the top 15 signaling pathways with significant enrichment of hub genes and potential genes were the same, including malaria,

CRP SELE MAPK1

MOL000049

IFNG

IL6

MPO

PLAU

VEGFA

MMP9

AR

BZ

MOL000072 MOL000022

CD40LG

TP53

CYP3A4

GSTM1

MOL000033

TNF

MOL002644

VCAM1

MOL011730

MOL013077

PTGS2

CXCL10

MOL001494

atopic dermatitis

MOL011753

CYP1A1

IRF1

MOL011740

food allergy

1. MOL001941
2. MOL001942

FF MOL000173

ADRB2

PPARG

MOL000358

NFKBIA

JUN

MOL011737

IL1A

MOL003588

MAPK14

asthma

MOL011732

atopic eczema

MOL011747

DPP4

NOS3

MOL000011

MMP1

ERBB2

MOL000371 MOL000392 MOL000296

allergic rhinitis

GSTP1

AHR

MOL000442

MOL000098

IL1B

IL4

MOL000239

HQ

MOL000422

MMP2

TGFB1

ESR1

IL2

MOL000380

MOL000379

CCL2

EGFR

MOL000417

MOL000354

ICAM1 CXCL8

HMOX1

MOL000387 MOL000378

IL10

PTGS1

SLC6A4 ALOX5 NOS2

1. Figure 4: YPFP-Target-Allergy network. e orange circles represent drugs; the green squares represent active ingredients; the yellow diamonds represent potential targets; and the blue triangles represent the diseases. e line between two nodes represents the interaction.

African trypanosomiasis, inflammatory bowel disease (IBD), allograft rejection, graft-versus-host disease, IL-17 signaling pathway, asthma, leishmaniasis, pertussis, chagas disease (American trypanosomiasis), and rheumatoid arthritis. Additionally, the Sankey diagram showed that most hub genes were enriched in the IL-17 pathway. e Sankey diagram and signal pathway diagram are shown in Figures 8 and 9.

Table 2: Top 5 high degree active ingredients in YPFP-TargetAllergy network.

No Molecule id Molecule name (active ingredients) Degree

1. 1 MOL000098 Quercetin 41
2. 2 MOL000422 Kaempferol 21
3. 3 MOL000173 Wogonin 17
4. 4 MOL000392 Formononetin 14
5. 5 MOL000378 7-O-Methylisomucronulatol 11

1. 3.6. Molecular Docking Verification. Molecular docking was used to evaluate the binding affinity between the hub targets of the PPI network and the key ingredients of the YPFPTarget-Allergy topological network. e results showed that the minimum vina score of each docking module was less than −5.0kcal/mol, indicating a good binding affinity of the hub targets to the key ingredients (Table 3, Supplementary Table S5). To better demonstrate the docking patterns of the targets and ingredients, only the docking modules with a vina score of less than −8.5kcal/mol were visualized (Figure 10).
2. 4. Discussion

Atopic dermatitis (also known as atopic eczema), food allergies, asthma, and allergic rhinitis are the most common allergy-related diseases with similar epigenetic and physiopathological characteristics [22, 23]. Numerous

experimental and clinical studies have shown that the poor prognosis of atopic dermatitis and food allergies in early life greatly exacerbates the occurrence of later asthma and allergic rhinitis [1–4, 24]. Although it is believed that the development of allergies is associated with genetic and environmental influences, the specific mechanisms remain unclear. erefore, it is necessary to conduct joint research on multiple allergy-related diseases to explore their common core mechanisms.

TCM has a unique theoretical system for the treatment of allergies. According to the theory of TCM, “qi deficiency” and “wind evil” are the two pathogenic bases of allergic diseases. erefore, invigorating qi and dispelling wind are the main treatment principles. YPFP, a TCM compound with the above dual effects, is considered an effective and safe complementary and alternative therapy for allergy. To reveal the underlying mechanism of YPFP for allergy treatment, we described the relationships between active ingredients,

positive regulation of fever generation negative regulation of lipid storage

vascular endothelial growth factor production positive regulation of neuroinflammatory response

-log10(pvalue)

8 7 6 5

type 2 immune response

regulation of immunoglobulin secretion positive regulation of mononuclear cell migration

positive regulation of vascular endothelial cell proliferation negative regulation of production of miRNAs involved in gene silencing by miRNA

count

2.0 2.5 3.0 3.5 4.0

negative regulation of gene silencing by miRNA negative regulation of cytokine production involved in immune response

membrane to membrane docking estrogen 2-hydroxylase activity connective tissue replacement involved in inflammatory response wound healing regulation of cytokine production involved in inflammatory response

0.40 0.45 0.50 0.55 0.60

(a)

Malaria

Bladder cancer African trypanosomiasis

-log10(pvalue)

Leishmaniasis IL-17 signaling pathway

30 25 20 15 10

AGE-RAGE signaling pathway in diabetic complications

Allogra rejection Inflammatory bowel disease (IBD) Gra -versus-host disease Pertussis Chagas disease (American trypanosomiasis) TNF signaling pathway Rheumatoid arthritis Fluid shear stress and atherosclerosis Asthma

count 4 8 12 16

0.125 0.150 0.1750.200 0.2250.250

(b)

1. Figure 5: e top 15 remarkably enriched GO and KEGG pathway analyses of potential genes. (a) e top 15 remarkably enriched GO analyses for biological function of potential target genes of YPFP in allergy. (b) e top 15 remarkably enriched KEGG analyses for signaling pathway of potential target genes of YPFP in allergy.

targets, and signaling pathways in combination with network pharmacology and molecular docking.

A PPI network was constructed with 48 genes coexpressed by allergy and YPFP. e 10 hub genes obtained by the PPI network all suggest the association of allergy and inflammatory response. IL6, TNF, CCL2, CXCL8, and IL1β

were pro-inflammatory genes, while IL4, IL10, and IFNG were antiinflammatory genes. In the acute phase of inflammation, IL-6 is an important mediator of host immunity, but its sustained release can induce chronic inflammation or even a “cytokine storm” [25]. Mast cells (MC) are key participants in IgE lazy allergy [26]. In local reactions, MC-mediated CCL2

positive regulation of fever generation

vascular endothelial growth factor production positive regulation of neuroinflammatory response

-log10(pvalue)

type 2 immune response positive regulation of mononuclear cell migration

9 8 7 6

negative regulation of cytokine production involved in immune response postive regulation of NMDA glutamate receptor activity positive regulation of MHC class II biosynthetic process

count

positive regulation of prostaglandin biosynthetic process response to molecule of bacterial origin regulation of establishment of endothelial barrier negative regulation of amyloid-beta clearance

2.00 2.25 2.50 2.75 3.00

endothelial cell apoptotic process negative regulation of lipid storage

positive regulation of membrane protein ectodomain proteolysis

0.2 0.3 0.4 0.5 0.6

(a)

Malaria

-log10(pvalue)

African trypanosomiasis

Inflammatory bowel disease (IBD)

Allograft rejection

Graft-versus-host disease

1. 3
2. 4
3. 5
4. 6
5. 7
6. 8
7. 9
8. 10

IL-17 signaling pathway

Asthma

Antifolate resistance

count

Leishmaniasis

Pertussis

Chagas disease (American trypanosomiasis)

Rheumatoid arthritis

Legionellosis

Type I diabetes mellitus

Amoebiasis

0.06 0.08 0.10 0.12 0.14

(b)

1. Figure 6: e top 15 remarkably enriched GO and KEGG pathway analyses of hub genes. (a) e top 15 remarkably enriched GO analyses for biological function of hub genes of YPFP in allergy. (b) e top 15 remarkably enriched KEGG analyses for signaling pathway of hub genes of YPFP in allergy.

promotes basophil migration, and MC-mediated CXCL8 and IL-1β participate in the recruitment of neutrophils [27–29]. Besides, TNF, as an important derivative of MC, plays a key role in promoting the induction of adaptive immunity [26]. TH2 type adaptive immunity is a common immunological manifestation of allergy-related diseases [30]. TH2 polarization leads to dysregulation of T lymphocyte subsets, such as TH1/TH2 imbalance and TH2/Treg imbalance [31, 32]. As the main secreted cytokines of TH2, TH1, and Treg, the expressions of IL-4, IFN-c, and IL-10 necessarily show

corresponding changes [31, 32]. PTGS2 is a cyclooxygenase involved in pain, inflammation, and tumor formation. Recent studies have found that PTGS2 participates in the induction of neovascularization and the promotion of TH2 polarization [33–35]. Furthermore, Jun regulates inflammatory processes at the transcriptional level. It was confirmed that Jun/AP-1 activation plays a key role in the expression of pro-inflammatory molecules such as IL-1, IL-6, and TNF-A [36]. us, anaphylaxis is essentially a chronic inflammatory response involving multiple cells and mediators.

negative regulation of amyloid-beta clearance regulation of establishment of endothelial barrier

positive regulation of membrane protein ectodomain proteolysis

positive regulation of prostaglandin biosynthetic process

response to molecule of bacterial origin

endothelial cell apoptotic process

positive regulation of NMDA glutamate receptor activity

hub genes

positive regulation of mononuclear cell migration

positive regulation of MHC class II biosynthetic process

positive regulation of fever generation

type 2 immune response negative regulation of lipid storage

vascular endothelial growth factor production

positive regulation of neuroinflammatory response

regulation of immunoglobulin secretion

negative regulation of cytokine production involved in immune response

estrogen 2-hydroxylase activity

membrane to membrane docking

potential genes

regulation of cytokine production involved in inflammatory response

connectivre tissue replacement involved in inflammatory response wound healing

negative regulation of production miRNAs involved in gene silencing by miRNA

negative regulation of vascular endothelial cell proliferation

negative regulation of gene silencing by miRNA

(a)

IL-17 signaling pathway Gra -versus-host disease

Type I diabetes mellitus

Antifolate resistance

Inflammatory bowel disease (IBD)

Legionellosis

Allogra rejection

Malaria

Amoebiasis

hub genes

African trypanosomiasis

Leishmaniasis

potential genes

Bladder cancer

Pertussis

AGE-RAGE signaling pathway in diabetic complications

Chagas disease (American trypanosomiasis)

TNF signaling pathway Fluid shear stress and

Rheumatoid arthritis

Asthma atherosclerosis

(b)

1. Figure 7: Co-enrichment functions and pathways of hub genes and potential genes in the top 15 GO and KEGG analyses. (a) e common enriched functions of hub genes and potential genes in the top 15 GO analyses. (b) e common enriched pathways of hub genes and potential genes in the top 15 KEGG analyses. e red square represents hub genes; the green square represents potential genes; the blue circles represent biological functions or pathways enriched by hub genes; the purple circles represent biological functions or pathways enriched by potential genes; and the yellow circles represent co-enrichment of biological functions or pathways of hub genes and potential genes.

CCL2 CXCL8

African trypanosomiasis Allogra rejection

Amoebiasis Antifolate resistance

IFNG

Asthma Chagas disease Gra -versus-host disease

IL10

IL-17 signaling pathway

IL1B

Inflammatory bowel disease Legionellosis Leishmaniasis

IL4

IL6

JUN PTGS2

Malaria

Pertussis

TNF

Rheumatoid arthritis Type I diabetes mellitus

IL-17 SIGNALING PATHWEAY

IL-17E IL-17E targeting cells producing cells

T cell, Macrophage, Nuocyte, Ih2 cell, MMP-type2 cell, Epithelial cell.

CD4+T cell, Mast cell, Eosinophil Basophil, Epithelial cell

1. IL-17RA TRADD FADD
2. IL-17RB Act1 TRAF6

IL-17E

IL-17A and IL-17F targeting cells CD4+T cell, CD8+T cell, yST cell, NKT cell, LTi-like cell, Epithelial cell

IL-17A and IL-17F producing cells

Epithelial cell, Keratinocyte, Endothelial cell, Macrophage, T cell, B cell, Fibroblast

+p

1. IL-17A IL-17RA
2. IL-17B

+u IL-17F

Act1

+p

17 cell differentiation

Cytokine-cytokine receptor interaction

USP25

IL-17C producing cells

IL-17C targeting cells

Monocyte CD4+T cell, DC,

Macrophage, Keratinocyte

IL-17B producing cells

IL-17B targeting cells

Monocyte, Endothelial cell

Condrocyte, Neuron

IL-17RB IL-17RB

Act1 TRAF6

Casp

NF-kB AP-1

Apoptosis Apoptosis

+p +p

MAPK signaling pathway

mRNA stability

+p

IL-17D producing cells

CD4+T cell, B cell

IL-17D ?

IL-17D targeting cells

Endothelial cell, Myeloid progenitor

2 cytokines DNA IL-4 IL-5 IL-13 Chemokines TARC Eotaxin

Induces 2 cell responses and suppresses 17 cell responses

DNA

Chemokines

CXCL2 CXCL5 CXCL8 CCL2 CCL7 CCL20

CXCL1 CXCL10

Cytokines

COX2

IL-6 TNFα

G-CSF GM-CSF

Anti-microbial

defensin MUC5AC MUC5B

S100A7 S100A8 S100A9 LCN2

Tissue remodeling

MMP1 MMP3 MMP9 MMP13

Autoimmune pathology Neutrophil recruitment Immunity to extracellular pathogens

DNA

DNA

Inflammatory genes

IL-6 IFN-y

TNFα

Antibacterial peptides 17 cytokines

IL-1B

Inflammatory genes

TNFα

Inflammation Host defence Autoimmune

Proinflammatory activities?

DNA

Proinflammatory activities?

04657 1/12/21 (c) Kanehisa Laboratories

According to the screening conditions (OB≥ 30%, DL≥0.18), a total of 45 active ingredients and 221 targets related to YPFP were identified, indicating that YPFP exerts

its pharmacological effects in the treatment of allergies via multiple targets. e top five active ingredients obtained by the YPFP-Target-Allergy topological network were quercetin,

Table 3: Molecular docking parameters and results of key ingredients binding to hub targets.

Center Size x y z x y z

Key ingredients Target Vina score Cavity size

PTGS2 −9.4 4392 13.702 49.228 64.724 21 30 29 TNF −8.9 10384 29.389 −21.424 41.646 35 35 35

O H

IL6 −9.1 2422 −28.73 32.674 41.7 27 21 21 JUN −8 1710 −2.548 −5.371 20.862 21 21 32 IL1B −6.9 145 −15.895 9.344 −14.260 21 21 21 CCL2 7.3 195 3.977 17.987 4.759 21 21 21 IFNG −7 932 7.332 35.436 22.884 31 21 35

O

H

O O

H

O Quercetin O O

H

IL4 −6.9 70 9.769 34.813 −0.368 21 21 21 IL10 −6.6 73 13.752 61.149 41.144 21 21 21

H

CXCL8 −6.2 92 18.369 −13.86 −17.202 21 21 21

PTGS2 −9.5 5179 11.893 52.644 16.694 33 21 29 TNF −9 10384 29.389 −21.424 41.646 35 35 35

H

IL6 8.8 2422 28.73 32.674 41.7 27 21 21 JUN −7.9 1710 −2.548 −5.371 20.862 21 21 32 IL1B −6.6 154 −22.700 21.788 −13.997 21 21 21 CCL2 −7.1 195 −3.977 −17.987 4.759 21 21 21 IFNG −7.1 932 7.332 35.436 22.884 31 21 35

O

O O

H

O

H

O O

Kaempferol

IL4 −6.4 70 9.769 34.813 −0.368 21 21 21

H

IL10 −6.7 162 42.705 34.512 43.604 21 21 21 CXCL8 −6.2 114 17.866 −9.064 −0.582 21 21 21

PTGS2 9.1 5179 11.893 52.644 16.694 33 26 29 TNF −9 10384 29.389 −21.424 41.646 35 35 35

IL6 −8.3 2422 −28.73 32.674 41.7 27 20 20 JUN −8.4 1710 −2.548 −5.371 20.862 20 26 32 IL1B −6.4 154 −22.700 21.788 −13.997 20 20 20 CCL2 −6.4 195 −3.977 −17.987 4.759 20 20 20 IFNG −6.8 932 7.332 35.436 22.884 31 20 35

H

O O

H

O O

O

Wogonin

IL4 −6.2 397 30.6 32.102 12.819 20 20 20 IL10 −7.1 262 5.253 57.499 35.389 20 20 20 CXCL8 −6.3 114 17.866 −9.064 −0.582 20 20 20

PTGS2 −9.3 5179 11.893 52.644 16.694 33 21 29 TNF −8.2 703 32.132 −11.15 −7.15 21 21 21

IL6 −8 608 −58.308 −3.426 17.841 21 21 21 JUN −7.2 1710 −2.548 −5.371 20.862 21 21 32 IL1B −6.5 111 −18.334 4.585 5.997 21 21 21 CCL2 −6.9 195 −3.977 −17.987 4.759 21 21 21 IFNG −7.2 932 7.332 35.436 22.884 31 21 35

O O

H

O O

Formononetin

IL4 −5.8 70 9.769 34.813 −0.368 21 21 21

IL10 6.9 262 5.253 57.499 35.389 21 21 21 CXCL8 6.6 114 17.866 9.064 0.582 21 21 21

PTGS2 −8.5 5179 11.893 52.644 16.694 33 21 29 TNF −8.1 703 32.132 −11.15 −7.15 21 21 21

IL6 −8.2 2422 −28.73 32.674 41.7 27 21 21 JUN −7.2 1710 −2.548 −5.371 20.862 21 21 32 IL1B −6.2 145 −15.895 9.344 14.260 21 21 21 CCL2 −6.1 195 −3.977 −17.987 4.759 21 21 21 IFNG −6.5 3791 −2.13 29.796 34.129 21 35 21

O O H

H

O O

O

7-O-Methylisomucronulatol

IL4 −5.6 70 9.769 34.813 −0.368 21 21 21

IL10 −6.9 162 42.705 34.512 43.604 21 21 21 CXCL8 −5.6 114 17.866 −9.064 −0.582 21 21 21

kaempferol, wogonin, formononetin, and 7-O-methylisomucronulatol. As for quercetin, existing studies have indicated that quercetin relieves asthmatic tracheal spasm by inhibiting the expression of MUC5AC in airway epithelial cells and improves allergic inflammation by regulating TH1/ TH2 balance and reducing antigen-specific IgE antibodies [37, 38]. Kaempferol, a biological flavonoid, has been reported

to block airway inflammation by interfering with TyK-STAT signaling in the airway epithelial cells of asthmatic mice [39]. Formononetin, a phytoestrogen extracted from Huangqi, has been demonstrated to ameliorate IL-13-induced inflammation and mucus formation in human nasal epithelial cells by activating the SIRT1/Nrf2 signaling pathway [40]. With regard to wogonin, it has been proved to reduce allergic

PTGS2-quercetin

PTGS2-kaempferol

PTGS2-wogonin

PTGS2-formononetin

IL6-quercetin

IL6-kaempferol

TNF-quercetin

TNF-kaempferol

TNF-wogonin

airway inflammation by inducing eosinophil apoptosis and regulating T lymphocyte differentiation [41–43]. On the whole, YPFP is a compound with a multitarget therapeutic effect. e potential association of its active ingredients with allergies should be further investigated.

GO analysis revealed that the main biological processes of YPFP (significantly enriched by both potential genes

and hub genes) included neuroinflammation, fever regulation, vascular endothelial growth, lipid storage, and inflammatory regulation. e pathogenesis of neuroinflammation in allergic diseases has long been reported. Patients with chronic allergic inflammation have similar patterns of neuroinflammatory gene expression, which may be associated with the outcome of neuroimmune

interactions [44, 45]. Fever is regulated by hypothalamic temperature-sensitive neurons. Although infection is the primary cause of fever, endogenous heat sources such as IL-1β, TNF, IL-6, and PTGS2-induced prostaglandins also act on the thermoregulatory centers of allergic diseases [46, 47]. Obesity is thought to be a major environmental factor in promoting allergies [48, 49]. Adipose tissue synthesizes and secretes a variety of cytokines and adipokines such as IL-6, TNF, TGF-β, and leptin that drive hypoinflammatory responses and have been proven to contribute to the pathogenesis of allergy [50, 51]. Angiogenesis has been observed with the development of allergic inflammation. Vascular endothelial growth factor (VEGF) is one of the most important angiogenesis inducing factors, which contributes to allergic reactions by increasing vascular permeability and promoting local tissue fluid exudation [26, 52]. As for inflammatory regulation, specifically including negative regulation of cytokine production involved in immune response, positive regulation of mononuclear cell migration, and type 2 immune response, the relevant mechanisms have been mentioned in the previous paragraph. erefore, it is speculated that the effect of YPFP on allergy may be related to the above biological processes.

KEGG pathway analysis revealed that YPFP treatment of allergy involves multiple signaling pathways. Examples include malaria, African trypanosomiasis, leishmaniasis, and Chagas disease (American trypanosomiasis), which are associated with parasitic infections. Numerous epidemiological and immunological studies have supported parasite expose-mediated host defense as a potential risk factor for allergy [53–55]. Inflammatory bowel disease (IBD) and rheumatoid arthritis are both autoimmune diseases, and pertussis is an acute respiratory infectious disease. It is currently believed that allergy is a nonlocalized chronic inflammatory disease, which can lead to systemic immune dysfunction and further increase the risk of irritable bowel syndrome, rheumatoid arthritis, and pertussis [56–59]. e IL-17 signaling pathway, which enriches most of the central targets, is presumed to be the most relevant pharmacodynamic pathway of YPFP. It has been confirmed that IL-17 plays a key role in host defense, allergic reactions, autoimmune diseases, and other inflammatory responses [60–64]. TH2 polarization-induced eosinophil infiltration was thought to be the core mechanism of hypersensitivity. However, IL-17 in combination with IL-23 amplifies the inflammatory effects of eosinophils by activating NF-κB, ERK, and P38 MAPK signaling pathways [65]. Even in non 2 allergies, IL-17 induces airway epithelial cells to produce chemokines CXCL1 and CXCL8 to promote neutrophil recruitment while stimulating fibroblasts and macrophages to secrete cytokines such as GM-CSF, TNF, IL-1, IL-8, and IL-6 to enhance inflammatory responses [61, 66, 67]. Besides, corticosteroids are one of the effective means of allergy control, but steroid resistance is the main cause of refractory allergy [68]. Recent studies have suggested that IL-17 induces steroid hyporesponsiveness in obese asthmatic patients by mediating dysregulation of glucocorticoid receptor α/β [69]. In conclusion, IL-17 may

be a key pathway for YPFP to exert its inflammatory regulatory role in allergic diseases. Investigation of the relevant drug-target action mechanism may be the direction of further exploration.

Molecular docking verified the good binding effect of key ingredients and hub targets. e binding scores of PTGS2 to quercetin, kaempferol, wogonin, and formononetin, IL-6 to kaempferol and formononetin, and TNF to kaempferol, wogonin, and formononetin were all less than −8.5kcal/mol, indicating that the bound molecular structure was more stable. PTGS2 (COX-2) is an important mediator in promoting inflammation and tumor growth. Il-6 is involved in inducing the transition from acute to chronic inflammation. TNF-α mediates the inflammatory response in the early stages of anaphylaxis. Studies have shown that quercetin inhibits the production of COX-2 and delays angiogenesis by inactivating P300 histone acetyltransferase (HAT) [70]. Kaempferol targets STAT3 and NF-κB signaling pathways to reduce inflammatory responses associated with PTGS2 expression [71]. Formononetin reduces the release of inflammatory mediators such as TNF-α, IL-1β, and IL-6 by inhibiting caspase-1 activity and regulating NF-κB activation and translocation [72]. e above studies partially validated our findings.

However, there are still some limitations to this study. For example, the database information may be incomplete, and the interaction between active ingredients is not considered. Nonetheless, this study provides a new approach for further exploring the molecular mechanism of YPFP in allergies and a new idea for the study of targeted therapy mechanisms.

In this study, we combined network pharmacology and molecular docking technology to study the molecular mechanism of YPFP in the treatment of allergy. According to the research, YPFP plays an antiallergic role mainly through inhibiting inflammatory infiltration, regulating neuroinflammation, regulating fever, inhibiting vascular endothelial growth, and improving lipid storage, involving malaria, African trypanosomiasis, inflammatory bowel disease (IBD), allograft rejection, graft-versus-host disease, IL-17 signaling pathway, asthma, leishmaniasis, pertussis, Chagas disease (American Trypanosomiasis) and Rheumatoid arthritis and other signaling pathways. Quercetin, Kaempferol, Wogonin, Formononetin, and 7-o-methylisomucronulatol are the key active ingredients of YPFP. IL6, TNF, IL1β, PTGS2, CXCL8, JUN, CCL2, IL10, IFNG, and IL4 are the main therapeutic targets. is study indicates that YPFP has the characteristics of multicomponent, multitarget, and multipathway in allergy treatment, which provides more evidence for the further application of YPFP in allergy.