# Identified the Synergistic Mechanism ofDrynariae Rhizoma for Treating Fracture Based on Network Pharmacology

Authors: Haixiong Lin; Xiaotong Wang; Ligang Wang; Hang Dong; Peizhen Huang; Qunbin Cai; Yingjie Mo; Feng Huang; Ziwei Jiang
Journal: Evidence-Based Complementary and Alternative Medicine
 (2019)

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## Abstract

Background. Drynariae Rhizoma (DR) has been widely used in the prevention and treatment of various fractures. However, the specific mechanisms of DR’s active ingredients have not been elucidated. The purpose of this study was to explore the synergistic mechanisms of DR for treating fracture. Methods. A network pharmacology approach integrating ingredient screening, target exploration, active ingredients-gene target network construction, protein-protein interaction network construction, molecular docking, gene-protein classification, gene ontology (GO) functional analysis, KEGG pathway enrichment analysis, and signaling pathway integration was used. Results. This approach identified 17 active ingredients of DR, interacting with 144 common gene targets and 143 protein targets of DR and fracture. NCOA1, GSK3B, TTPA, and MAPK1 were identified as important gene targets. Five most important protein targets were also identified, including MAPK1, SRC, HRAS, RXRA, and NCOA1. Molecular docking found that DR has a good binding potential with common protein targets. GO functional analysis indicated that common genes involve multiple processes, parts and functions in biological process, cellular component, and molecular function, including positive regulation of transcription from RNA polymerase II promoter, signal transduction, cytosol, extracellular exosome, cytoplasm, and protein binding. The KEGG pathway enrichment analysis indicated that common gene targets play a role in repairing fractures in multiple signaling pathways, including MAPK, PI3K/AKT, Ras, and VEGF signaling pathways. MAPK and PI3K/AKT signaling pathways were involved in osteoblast formation, Ras signaling pathway was involved in enhancing mesenchymal stromal cell migration, and VEGF signaling pathway was involved in angiogenesis. Conclusion. The study revealed the correlation between DR and fracture and the potential synergistic mechanism of different targets of DR in the treatment of fractures, which provides a reference for the development of new drugs.


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## Body

## 1. Introduction

Fracture is a common and frequent disease that occurs in patients with various injuries or osteoporosis [1]. In China, the population-weighted incidence of traumatic fractures of the legs, arms, or trunk in 2014 was 3.21 per 1,000 people (95% CI 2.83–3.59) [2]. Osteoporotic fractures are estimated to account for half of all fractures by 2050, and the estimated cost of osteoporotic hip fractures worldwide may reach $131 billion [3]. Therefore, the study of drugs for the prevention and treatment of fractures plays an important role in promoting patient health and reducing family economic pressure.Recently, DR, one of the plants from Davalliaceae and Davallia Sm., has been widely used in the prevention and treatment of various fractures due to excellent treatment, low side effects, extensive use, and safety [4]. Animal experiments have confirmed that DR could alter the bone histomorphology and increase the number of trabeculae by 10% [5], and its osteogenesis is related to Runx2 and BMP-2 signaling pathways [6]. In addition, it is believed that the various ingredients contained in an herb could regulate multiple targets in different signaling pathways and produce synergistic therapeutic effects [7]. However, such research has not been carried out in the treatment of fractures with DR.Network pharmacology based on systems biology and polypharmacology has achieved a paradigm shift from “one drug, one goal” to “multi-ingredient therapy, biological network,” which has attracted the attention of Chinese medicine researchers and has been recognized as an effective tool for elucidating multiple components, targets, synergistic effects, and mechanisms of Chinese medicine [8–10]. It is reported that network pharmacology predicts the clinical efficacy, pathways, and side effects of drugs by constructing drug-drug networks, disease-drug networks, and disease-disease networks, providing valuable information for improving the clinical efficacy, reducing toxicity, and elucidating multimechanisms of drugs [11]. For example, Wang Nani found that Er-Xian Decotion has 13 main components closely related to 65 osteoporosis-related targets by using network pharmacology, thereby constructing Er-Xian Decotion component-osteoporosis target network and potential antiosteoporosis mechanism [12]. Yueying et al. identified 108 compounds, 86 potential targets, and 47 signal transduction pathways that Danshiliuhao Granule regulates liver fibrosis by the network pharmacology method, which reflects the multicomponent, multitarget, and multichannel characteristics of Chinese herbal medicine in antiliver fibrosis [13]. Therefore, in order to reveal the relationship between fracture and the active ingredients involved in the DR, we conducted network pharmacology to achieve this goal from protein and gene level. We collected the information of targets from active ingredients in DR and targets of fracture from several databases, respectively, and used network pharmacology to explore the potential synergistic mechanisms of DR for treating fracture.


## 2. Materials and Methods

### 2.1. Screening of Active Ingredients ofDrynariae Rhizoma

Traditional Chinese Medicine Systems Pharmacology (TCMSP,http://lsp.nwu.edu.cn/, Version 2.3) Database and Analysis Platform includes chemicals, targets, and drug-target-disease networks, as well as pharmacokinetic properties involving oral bioavailability, druglikeness, blood-brain-barrier, and so on [14]. There were 71 compounds of DR which were obtained from the TCMSP. The potential active ingredients of DR for treating fracture were screened according to their oral bioavailability (OB) ≥30% and druglikeness (DL) ≥0.18 recommended by TCMSP.


### 2.2. Obtaining the Chemical Structure of Active Ingredients

The structure of the potential active ingredients of DR was downloaded from TCMSP and stored in mol2 format. If there was no chemical structure, the PubChem compound was put into the PubChem (https://pubchem.ncbi.nlm.nih.gov/) to download a chemical structure and save it in sdf format, or the PubChem compound was put into the Zinc database (https://zinc.docking.org/) to download a chemical structure and save it in mol2 format. The related SMILES of potential active ingredients was received from TCMSP or PubChem or Zinc database. Then, the SMILES was put into the Swiss Target Prediction database (http://www.swisstargetprediction.ch/) to obtain the related drug target and save it.


### 2.3. Gene Targets ofDrynariae Rhizoma

The DRAR-CPI server (http://cpi.bio-x.cn/drar, update in 2017-7-26) has a collection of drug molecules and targetable human proteins [15]. When submitting a drug molecule, the server docks the drug uploaded by users with the three-dimensional structure of all protein targets in the database, scores, and ranks them with the affinity scoring function based on the protein-ligand interaction, thereby predicting the potential protein targets of human-targetable drugs [15, 16]. This affinity score is called Z-score in the DRAR-CPI server [17]. Protein-ligand interaction with Z-score <−0.5 was recommended by DRAR-CPI as a potential protein target for human-targetable drugs [16]. We uploaded the potential active ingredients of DR in mol2 or sdf format and used Z-score <−0.5 to select potential protein targets for DR. A total of 1760 proteins with Z-score <−0.5 and 355 protein targets were obtained after deletion of the duplicate data. The PDB ID of the protein targets were inputted into UniProt KB (http://www.uniprot.org/uniprot/) of the UniProt database, and the “popular organisms” was selected as human to obtain the gene targets associated with the potential active ingredient of DR.


### 2.4. Gene Target Prediction forDrynariae Rhizoma to Treat Fractures

The following electronic databases were searched to identify the genes related to fractures: Genetic Association Database (https://geneticassociationdb.nih.gov/), Therapeutic Targets Database (http://bidd.nus.edu.sg/BIDD-Databases/TTD/TTD.asp), PharmGkb database (https://www.pharmgkb.org/), GeneCards database (http://www.genecards.org/), and OMIM database (http://www.ncbi.nlm.nih.gov/omim). Then, the duplicate data and false-positive genes were deleted. Finally, the Venny tool (http://bioinfogp.cnb.csic.es/tools/venny/index.html, Version 2.1) was used to identify the common gene targets of DR and fracture, which may be the potential targets for DR to treat fractures.


### 2.5. Constructing the Ingredient-Target Network ofDrynariae Rhizoma

The common gene targets of DR and fracture were introduced into the Cytoscape software (Version 3.4.0) to construct an ingredient-target network ofDrynariae Rhizoma and analyze the topology properties of the network, including degree, betweenness centrality, and closeness centrality [18]. The degree describes the number of connections to a node in the network, indicating interaction with other nodes in the network. Betweenness centrality measures the proportion of a node between shortest paths among other nodes, suggesting the importance of nodes in maintaining network tightness. Closeness centrality indicates the degree of nodes close to the “center” of the network. A node with high degree, betweenness centrality, and closeness centrality values means that it plays a very important role in the network [18].


### 2.6. Constructing Protein-Protein Interaction (PPI) ofDrynariae Rhizoma

The String database (https://string-db.org/, Version 10.5) is a database containing known and predicted PPIs, which collect and integrate a large number of protein interactions involving 9,643,763 proteins and 1,380,838,440 interactions, including experimental data and interactive prediction data derived from bioinformatic methods [19]. Common gene targets of DR and fracture were imported into the STRING database, and the species were set to humans for PPIs. Then, the highest confidence was set to 0.9 in the minimum required interaction score and the results were updated. The TSV format of the updated results were downloaded. Then, node1, node2, and combined scores were extracted and imported into the Cytoscape software to create a PPI network, and the network was analyzed as follows: Step 1: analyze the topology properties of the network: cytoscape ⟶ tools ⟶ network analyzer ⟶ network analysis ⟶ analyze network, save the CSV format of the network result and extract the degree value. Step 2: create a network map according to the degree: cytoscape ⟶ tool ⟶ network analyzer ⟶ network analysis ⟶ generate style from statistics ⟶ map node size to degree ⟶ map node color to degree  and save the PPI network map.


### 2.7. Molecular Docking

SystemsDock (http://systemsdock.unit.oist.jp, Version 2.0) is a web server for network pharmacology-based prediction and analysis that could be used to illustrate the role of ligands on a complex molecular network [20]. It evaluates the protein-ligand binding potential of molecular docking by combining docking with the intelligence (dock-IN) score. The dock-IN score is the negative logarithm of the experimental dissociation/inhibition constant (pKd/pKi), which ranges from 0 to 10, indicating weak to strong binding [20]. It is believed that the docK-IN score above 4.25 indicates a slight binding potential between the protein and ligand; a value greater than 5.0 indicates a moderate binding potential, and a value greater than 7.0 indicates a strong binding potential [16]. We extracted the top 5 proteins with the highest degree value in the PPI network. The proteins that were recognized by systemsDock docked with the potential active ingredients of DR to receive the dock-IN score. The results were saved, and their dock-IN score was analyzed to assess the binding potentials between the potential active ingredients of DR and protein targets.


### 2.8. GO Functional Analysis and KEGG Pathway Enrichment Analysis

GO (http://www.geneontology.org) is widely used for annotation of gene function, providing detailed annotations of gene function in terms of biological process (BP), cellular component (CC), and molecular function (MF), respectively [21]. Database for annotation, visualization, and integrated discovery (David, https://david.ncifcrf.gov/, Version 6.8) is a functional genomic annotation database that provides bioinformatics annotation for genes or proteins based on the gene annotation function of the GO database and the signaling pathway information of the KEGG database [22]. We performed GO functional analysis and KEGG pathway enrichment analysis in the David database. The procedure was as follows: Step 1: paste the common gene targets of DR and fracture list. Step 2: select “OFFICIAL_GENE_SYMBOL” in “Select Identifier.” Step 3: select “Gene List” in “List Type.” Step 4: select “Homo sapiens” in species. Step 5: submit list. Step 6: download the results of BP, CC, and MF in the gene ontology. Step 7: download the results of KEGG pathway in the pathways. Step 8: targets with P<0.05 were screened and sorted by count (number of targets), and the top-ranked biological processes or KEGG pathways were extracted. Step 9: BP, CC, and MF were designed using GraphPad Prism 5.0 software. The KEGG pathways were designed by the advanced bubble chart of the omicshare tool (http://omicshare.com/tools/Home/Soft/getsoft/type/index).


### 2.9. Collect Protein Class Corresponding to Common Gene Targets

DisGeNET (http://www.disgenet.org/web/DisGeNET/menu, Version 5.0) is a discovery platform that contains one of the largest publicly available genes and variants associated with human disease. It could be used to analyze the properties of disease genes and investigate the molecular basis of specific diseases and their comorbidities, as well as adverse drug reactions [23]. We used the search function of the DisGeNET platform to retrieve the protein class corresponding to common gene targets.


### 2.10. Pathway Integration

We used the KEGG Mapper tool in the KEGG database (http://www.kegg.jp/) to retrieve some pathways of DR for fractures and then integrate into a final pathway map. The procedure was as follows: Step 1: used the UniProt KB search function of the UniProt database to retrieve the UniprotID of the common gene targets. Step 2: import the UniProt ID of the common gene targets. Step 3: set the parameters: search against: hsa, primary ID: NCBI-UniProt ID, and examples: Homo sapiens pathway. Step 4: download the PI3K-AKT, MAPK, Ras, and VEGF signaling pathways. Step 5: integrate the signal path.


## 2.1. Screening of Active Ingredients ofDrynariae Rhizoma

Traditional Chinese Medicine Systems Pharmacology (TCMSP,http://lsp.nwu.edu.cn/, Version 2.3) Database and Analysis Platform includes chemicals, targets, and drug-target-disease networks, as well as pharmacokinetic properties involving oral bioavailability, druglikeness, blood-brain-barrier, and so on [14]. There were 71 compounds of DR which were obtained from the TCMSP. The potential active ingredients of DR for treating fracture were screened according to their oral bioavailability (OB) ≥30% and druglikeness (DL) ≥0.18 recommended by TCMSP.


## 2.2. Obtaining the Chemical Structure of Active Ingredients

The structure of the potential active ingredients of DR was downloaded from TCMSP and stored in mol2 format. If there was no chemical structure, the PubChem compound was put into the PubChem (https://pubchem.ncbi.nlm.nih.gov/) to download a chemical structure and save it in sdf format, or the PubChem compound was put into the Zinc database (https://zinc.docking.org/) to download a chemical structure and save it in mol2 format. The related SMILES of potential active ingredients was received from TCMSP or PubChem or Zinc database. Then, the SMILES was put into the Swiss Target Prediction database (http://www.swisstargetprediction.ch/) to obtain the related drug target and save it.


## 2.3. Gene Targets ofDrynariae Rhizoma

The DRAR-CPI server (http://cpi.bio-x.cn/drar, update in 2017-7-26) has a collection of drug molecules and targetable human proteins [15]. When submitting a drug molecule, the server docks the drug uploaded by users with the three-dimensional structure of all protein targets in the database, scores, and ranks them with the affinity scoring function based on the protein-ligand interaction, thereby predicting the potential protein targets of human-targetable drugs [15, 16]. This affinity score is called Z-score in the DRAR-CPI server [17]. Protein-ligand interaction with Z-score <−0.5 was recommended by DRAR-CPI as a potential protein target for human-targetable drugs [16]. We uploaded the potential active ingredients of DR in mol2 or sdf format and used Z-score <−0.5 to select potential protein targets for DR. A total of 1760 proteins with Z-score <−0.5 and 355 protein targets were obtained after deletion of the duplicate data. The PDB ID of the protein targets were inputted into UniProt KB (http://www.uniprot.org/uniprot/) of the UniProt database, and the “popular organisms” was selected as human to obtain the gene targets associated with the potential active ingredient of DR.


## 2.4. Gene Target Prediction forDrynariae Rhizoma to Treat Fractures

The following electronic databases were searched to identify the genes related to fractures: Genetic Association Database (https://geneticassociationdb.nih.gov/), Therapeutic Targets Database (http://bidd.nus.edu.sg/BIDD-Databases/TTD/TTD.asp), PharmGkb database (https://www.pharmgkb.org/), GeneCards database (http://www.genecards.org/), and OMIM database (http://www.ncbi.nlm.nih.gov/omim). Then, the duplicate data and false-positive genes were deleted. Finally, the Venny tool (http://bioinfogp.cnb.csic.es/tools/venny/index.html, Version 2.1) was used to identify the common gene targets of DR and fracture, which may be the potential targets for DR to treat fractures.


## 2.5. Constructing the Ingredient-Target Network ofDrynariae Rhizoma

The common gene targets of DR and fracture were introduced into the Cytoscape software (Version 3.4.0) to construct an ingredient-target network ofDrynariae Rhizoma and analyze the topology properties of the network, including degree, betweenness centrality, and closeness centrality [18]. The degree describes the number of connections to a node in the network, indicating interaction with other nodes in the network. Betweenness centrality measures the proportion of a node between shortest paths among other nodes, suggesting the importance of nodes in maintaining network tightness. Closeness centrality indicates the degree of nodes close to the “center” of the network. A node with high degree, betweenness centrality, and closeness centrality values means that it plays a very important role in the network [18].


## 2.6. Constructing Protein-Protein Interaction (PPI) ofDrynariae Rhizoma

The String database (https://string-db.org/, Version 10.5) is a database containing known and predicted PPIs, which collect and integrate a large number of protein interactions involving 9,643,763 proteins and 1,380,838,440 interactions, including experimental data and interactive prediction data derived from bioinformatic methods [19]. Common gene targets of DR and fracture were imported into the STRING database, and the species were set to humans for PPIs. Then, the highest confidence was set to 0.9 in the minimum required interaction score and the results were updated. The TSV format of the updated results were downloaded. Then, node1, node2, and combined scores were extracted and imported into the Cytoscape software to create a PPI network, and the network was analyzed as follows: Step 1: analyze the topology properties of the network: cytoscape ⟶ tools ⟶ network analyzer ⟶ network analysis ⟶ analyze network, save the CSV format of the network result and extract the degree value. Step 2: create a network map according to the degree: cytoscape ⟶ tool ⟶ network analyzer ⟶ network analysis ⟶ generate style from statistics ⟶ map node size to degree ⟶ map node color to degree  and save the PPI network map.


## 2.7. Molecular Docking

SystemsDock (http://systemsdock.unit.oist.jp, Version 2.0) is a web server for network pharmacology-based prediction and analysis that could be used to illustrate the role of ligands on a complex molecular network [20]. It evaluates the protein-ligand binding potential of molecular docking by combining docking with the intelligence (dock-IN) score. The dock-IN score is the negative logarithm of the experimental dissociation/inhibition constant (pKd/pKi), which ranges from 0 to 10, indicating weak to strong binding [20]. It is believed that the docK-IN score above 4.25 indicates a slight binding potential between the protein and ligand; a value greater than 5.0 indicates a moderate binding potential, and a value greater than 7.0 indicates a strong binding potential [16]. We extracted the top 5 proteins with the highest degree value in the PPI network. The proteins that were recognized by systemsDock docked with the potential active ingredients of DR to receive the dock-IN score. The results were saved, and their dock-IN score was analyzed to assess the binding potentials between the potential active ingredients of DR and protein targets.


## 2.8. GO Functional Analysis and KEGG Pathway Enrichment Analysis

GO (http://www.geneontology.org) is widely used for annotation of gene function, providing detailed annotations of gene function in terms of biological process (BP), cellular component (CC), and molecular function (MF), respectively [21]. Database for annotation, visualization, and integrated discovery (David, https://david.ncifcrf.gov/, Version 6.8) is a functional genomic annotation database that provides bioinformatics annotation for genes or proteins based on the gene annotation function of the GO database and the signaling pathway information of the KEGG database [22]. We performed GO functional analysis and KEGG pathway enrichment analysis in the David database. The procedure was as follows: Step 1: paste the common gene targets of DR and fracture list. Step 2: select “OFFICIAL_GENE_SYMBOL” in “Select Identifier.” Step 3: select “Gene List” in “List Type.” Step 4: select “Homo sapiens” in species. Step 5: submit list. Step 6: download the results of BP, CC, and MF in the gene ontology. Step 7: download the results of KEGG pathway in the pathways. Step 8: targets with P<0.05 were screened and sorted by count (number of targets), and the top-ranked biological processes or KEGG pathways were extracted. Step 9: BP, CC, and MF were designed using GraphPad Prism 5.0 software. The KEGG pathways were designed by the advanced bubble chart of the omicshare tool (http://omicshare.com/tools/Home/Soft/getsoft/type/index).


## 2.9. Collect Protein Class Corresponding to Common Gene Targets

DisGeNET (http://www.disgenet.org/web/DisGeNET/menu, Version 5.0) is a discovery platform that contains one of the largest publicly available genes and variants associated with human disease. It could be used to analyze the properties of disease genes and investigate the molecular basis of specific diseases and their comorbidities, as well as adverse drug reactions [23]. We used the search function of the DisGeNET platform to retrieve the protein class corresponding to common gene targets.


## 2.10. Pathway Integration

We used the KEGG Mapper tool in the KEGG database (http://www.kegg.jp/) to retrieve some pathways of DR for fractures and then integrate into a final pathway map. The procedure was as follows: Step 1: used the UniProt KB search function of the UniProt database to retrieve the UniprotID of the common gene targets. Step 2: import the UniProt ID of the common gene targets. Step 3: set the parameters: search against: hsa, primary ID: NCBI-UniProt ID, and examples: Homo sapiens pathway. Step 4: download the PI3K-AKT, MAPK, Ras, and VEGF signaling pathways. Step 5: integrate the signal path.


## 3. Results

### 3.1. Active Ingredients ofDrynariae Rhizoma

A total of 71 ingredients of DR were retrieved from TCMSP, and 18 active ingredients were screened according to the biological functions of DR. However, marioside_qt (Molecule ID: MOL009087) was removed because it could not be recognized by the PubChem or Zinc database. The remaining 17 active ingredients are shown in Table1, including (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one, aureusidin, eriodictyol (flavanone), stigmasterol, beta-sitosterol, kaempferol, naringenin, (+)-catechin, eriodictyol, digallate, luteolin, 22-stigmasten-3-one, cyclolaudenol acetate, cycloartenone, cyclolaudenol, davallioside A_qt, and xanthogalenol.Table 1
Main active ingredients inDrynariae Rhizoma.
No.
Molecule ID
Molecule name
Chemical formula
Structure
OB (%)
DL
1
MOL001040
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
C15H12O5
42.36
0.21
2
MOL001978
Aureusidin
C15H10O6
53.42
0.24
3
MOL002914
Eriodictyol (flavanone)
C15H12O6
41.35
0.24
4
MOL000449
Stigmasterol
C29H48O
43.83
0.76
5
MOL000358
β-Sitosterol
C29H50O
36.91
0.75
6
MOL000422
Kaempferol
C15H10O6
41.88
0.24
7
MOL004328
Naringenin
C15H12O5
59.29
0.21
8
MOL000492
(+)-Catechin
C15H14O6
54.83
0.24
9
MOL005190
Eriodictyol
C15H12O6
71.79
0.24
10
MOL000569
Digallate
C14H10O9
61.85
0.26
11
MOL000006
Luteolin
C15H10O6
36.16
0.25
12
MOL009061
22-Stigmasten-3-one
C29H48O
39.25
0.76
13
MOL009063
Cyclolaudenol acetate
C33H54O2
41.66
0.79
14
MOL009075
Cycloartenone
C30H48O
40.57
0.79
15
MOL009076
Cyclolaudenol
C31H52O
39.05
0.79
16
MOL009078
Davallioside A_qt
C25H29NO12
62.65
0.51
17
MOL009091
Xanthogalenol
C21H22O5
41.08
0.32


### 3.2. Gene Target Prediction

A total of 303 gene targets associated with the potential active ingredients of DR were retrieved in the UniProt database. A total of 3,173 fracture-related genes were received, and 3,054 genes remained after deletion of the duplicate and false-positive genes. Common gene target screening for fracture and DR are shown in Figure1. A total of 144 common gene targets of DR and fracture were received, indicating the potential targets for DR to treat fractures, as shown in Table 2.Figure 1
Venn diagram of common gene target screening for fracture andDrynariae Rhizoma.Table 2
Information of potential gene targets for treating fracture fromDrynariae Rhizoma.
No.
PDB ID
Gene target
1
1HSZ
ADH1B
2
1HT0
ADH1C
3
1D1T
ADH7
4
1H0C
AGXT
5
3CQW
AKT1
6
1O6L
AKT2
7
2GLQ
ALPP
8
1ANG
ANG
9
1HAK
ANXA5
10
1E3G
AR
11
2NZ2
ASS1
12
1ONQ
B2M
13
1XLV
BCHE
14
1ES7
BMP2
15
1M4U
BMP7
16
1ES7
BMPR1A
17
1UWJ
BRAF
18
1A42
CA2
19
1ICE
CASP1
20
1K86
CASP7
21
2C2Z
CASP8
22
2HRB
CBR3
23
1JBQ
CBS
24
1ONQ
CD1A
25
1POZ
CD44
26
2OBD
CETP
27
1XMI
CFTR
28
3DRB
CKB
29
1NN6
CMA1
30
3BWY
COMT
31
1NM8
CRAT
32
1C8P
CSF2RB
33
1BYG
CSK
34
1CSB
CTSB
35
1LYW
CTSD
36
1CGH
CTSG
37
1JKL
DAPK1
38
2HHA
DPP4
39
1M17
EGFR
40
1H1B
ELANE
41
1R5K
ESR1
42
1QKM
ESR2
43
2PJL
ESRRA
44
1F0R
F10
45
1A3B
F2
46
1Z6J
F3
47
1Z6J
F7
48
1RFN
F9
49
2FGI
FGFR1
50
2PVY
FGFR2
51
2BH9
G6PD
52
1ZNQ
GAPDH
53
1OGS
GBA
54
1J78
GC
55
1PUB
GM2A
56
1J1B
GSK3B
57
1GRE
GSR
58
1XWK
GSTM1
59
11GS
GSTP1
60
2C3Q
GSTT1
61
2VQM
HDAC4
62
1GMN
HGF
63
1HWL
HMGCR
64
1S8C
HMOX1
65
5P21
HRAS
66
1DHT
HSD17B1
67
1ZBQ
HSD17B4
68
1YET
HSP90AA1
69
2OJ9
IGF1R
70
1ZT3
IGFBP1
71
2ILK
IL10
72
1G0Y
IL1R1
73
2CYK
IL4
74
1TYL
INS
75
2AUH
INSR
76
1QCY
ITGA1
77
2B7A
JAK2
78
1ZSX
KCNAB2
79
1QPC
LCK
80
1I0Z
LDHB
81
1KJL
LGALS3
82
1TVO
MAPK1
83
1JNK
MAPK10
84
1A9U
MAPK14
85
1UKI
MAPK8
86
2DFD
MDH2
87
1GCZ
MIF
88
1DMT
MME
89
1HFC
MMP1
90
1QIA
MMP3
91
1JAP
MMP8
92
1SD2
MTAP
93
2P54
NCOA1
94
1MVC
NCOA2
95
2IIP
NNMT
96
1M4U
NOG
97
1NSI
NOS2
98
1KBQ
NQO1
99
1UPV
NR1H2
100
3FXV
NR1H4
101
1NRL
NR1I2
102
1P93
NR3C1
103
2A3I
NR3C2
104
1YOW
NR5A1
105
1WWA
NTRK1
106
1WWB
NTRK2
107
1OTH
OTC
108
1WOK
PARP1
109
2QYK
PDE4A
110
1PTW
PDE4D
111
1ZUC
PGR
112
2VGB
PKLR
113
1VJA
PLAU
114
2PK4
PLG
115
1NRG
PNPO
116
1V04
PON1
117
1B1C
POR
118
2P54
PPARA
119
2J14
PPARD
120
1ZEO
PPARG
121
1CYN
PPIB
122
1QMV
PRDX2
123
2GU8
PRKACA
124
1LQV
PROCR
125
1HDR
QDPR
126
1QAB
RBP4
127
2G1N
REN
128
1MVC
RXRA
129
1OLM
SEC14L2
130
1F5F
SHBG
131
1I92
SLC9A3R1
132
2C9V
SOD1
133
1YOL
SRC
134
1P49
STS
135
1J99
SULT2A1
136
1NAV
THRA
137
1NAX
THRB
138
1A8M
TNF
139
1HTI
TPI1
140
1D0A
TRAF2
141
1OIZ
TTPA
142
1QAB
TTR
143
1UOU
TYMP
144
3CS4
VDR


### 3.3. Ingredient-Target Network ofDrynariae Rhizoma

The active ingredients and gene targets of DR was inputted into Cytoscape software to construct the ingredient-target network, as shown in Figure2. In the network, the pink oval nodes represent the main active ingredients of DR, and the light green rectangle nodes represent the potential gene targets for DR to treat fractures. The line represents the correlation between the active ingredients of DR and the gene targets. There are 161 nodes and 774 lines in the network. An active ingredient could be linked to different gene targets, and a gene target could be linked to different active ingredients, suggesting the multicomponent and multitarget characteristics of DR. The topology properties of active ingredients of DR are shown in Supplementary Table 1. Both cyclolaudenol and cycloartenone were linked to a maximum number of gene targets, with 70 (48.61%) different gene targets. Cyclolaudenol acetate was linked to 54 (37.5%) different gene targets. Xanthogalenol was linked to a minimum number of gene targets for a total of 29 (20.14%). In addition, there were four gene targets with the top four degree values, betweenness centrality, and closeness centrality at the same time (Table 3), which were NCOA1, GSK3B, TTPA, and MAPK1.Figure 2
Ingredient-target network ofDrynariae Rhizoma. Note. The pink oval nodes () are the main active ingredients of Drynariae Rhizoma, and the light green rectangle () is the potential target for treating fracture of Drynariae Rhizoma.Table 3
Gene targets with the top 4 degree values, betweenness centrality, and closeness centrality.
No.
Gene targets
Degree (rank)
Betweenness centrality (rank)
Closeness centrality (rank)
1
NCOA1
15 (1)
0.038 (1)
0.505 (1)
2
MAPK1
13 (2)
0.023 (3)
0.464 (4)
3
GSK3B
12 (3)
0.028 (2)
0.502 (2)
4
TTPA
12 (4)
0.022 (4)
0.466 (3)


### 3.4. Protein-Protein Interaction ofDrynariae Rhizoma

The PPI network of DR is shown in Figure3. In the network, the node represents the protein, and the size and color of the node represent the value of the degree. The larger the node and the brighter the color (yellow to blue), the greater the value of the degree. The line indicates the association between proteins. Results showed that there were 143 nodes and 315 lines.Figure 3
Protein-protein interaction network ofDrynariae Rhizoma. Note. The size and the color of the node represents the value of the degree (yellow ⟶ orange ⟶ blue indicates that the degree value is from low to high, and the small circle represents a low degree value).Degree in the network indicates the number of proteins that a protein has interacting with. In other words, top-degree protein targets screened in PPI plays a pivotal role in the treatment of fractures with DR. Five important protein targets with top degree of DR were identified in the PPI network and are shown in Table4. They were MAPK1, SRC, HRAS, RXRA, and NCOA1.Table 4
Five important protein targets with top degree ofDrynariae Rhizoma.
No.
Degree
PDB ID
Protein target name
1
27
1TVO
MAPK1
2
23
1YOL
SRC
3
22
5P21
HRAS
4
20
1MVC
RXRA
5
18
2P54
NCOA1


### 3.5. Molecular Docking

Three important protein targets with top degree of DR were identified by SystemsDock, including SRC, RXRA, and NCOA1. Dock-IN score of these three proteins docked with 17 active ingredients of DR are shown in Table5. Molecular docking results showed that there were 17 (33.33%) with a dock-IN score greater than 7.0, 24 (47.06%) with a dock-IN score between 7.0 and 5.0, 8 (15.69%) with a dock-IN score between 5.0 and 4.25, and 2 (3.92%) with a dock-IN score less than 4.25.Table 5
Molecular docking of three important protein targets fromDrynariae Rhizoma.
Protein target
PDB ID
Ingredients
Dock-IN score
NCOA1
1NQ7
(+)-Catechin
7.111
RXRA
1DSZ
(+)-Catechin
4.624
SRC
1O4R
(+)-Catechin
5.908
NCOA1
1NQ7
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
6.694
RXRA
1DSZ
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
4.605
SRC
1O4R
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
5.783
NCOA1
1NQ7
22-Stigmasten-3-one
8.422
RXRA
1DSZ
22-Stigmasten-3-one
5.553
SRC
1O4R
22-Stigmasten-3-one
5.425
NCOA1
1NQ7
Aureusidin
7.153
RXRA
1DSZ
Aureusidin
4.622
SRC
1O4R
Aureusidin
5.861
NCOA1
1NQ7
Beta-sitosterol
8.34
RXRA
1DSZ
Beta-sitosterol
5.587
SRC
1O4R
Beta-sitosterol
5.374
NCOA1
1NQ7
Cycloartenone
8.427
RXRA
1DSZ
Cycloartenone
5.658
SRC
1O4R
Cycloartenone
5.693
NCOA1
1NQ7
Cyclolaudenol
8.376
RXRA
1DSZ
Cyclolaudenol
5.534
SRC
1O4R
Cyclolaudenol
5.376
NCOA1
1NQ7
Cyclolaudenol acetate
8.422
RXRA
1DSZ
Cyclolaudenol acetate
7.052
SRC
1O4R
Cyclolaudenol acetate
6.364
NCOA1
1NQ7
Davallioside A_qt
7.904
RXRA
1DSZ
Davallioside A_qt
5.779
SRC
1O4R
Davallioside A_qt
5.58
NCOA1
1NQ7
Digallate
4.313
RXRA
1DSZ
Digallate
3.789
SRC
1O4R
Digallate
3.671
NCOA1
1NQ7
Eriodictyol
7.109
RXRA
1DSZ
Eriodictyol
4.628
SRC
1O4R
Eriodictyol
5.821
NCOA1
1NQ7
Eriodictyol (flavanone)
7.113
RXRA
1DSZ
Eriodictyol (flavanone)
4.633
SRC
1O4R
Eriodictyol (flavanone)
5.824
NCOA1
1NQ7
Kaempferol
7.125
RXRA
1DSZ
Kaempferol
4.613
SRC
1O4R
Kaempferol
5.929
NCOA1
1NQ7
Luteolin
7.089
RXRA
1DSZ
Luteolin
4.621
SRC
1O4R
Luteolin
5.847
NCOA1
1NQ7
Naringenin
7.12
RXRA
1DSZ
Naringenin
6.016
SRC
1O4R
Naringenin
5.883
NCOA1
1NQ7
Stigmasterol
8.376
RXRA
1DSZ
Stigmasterol
5.918
SRC
1O4R
Stigmasterol
5.3
NCOA1
1NQ7
Xanthogalenol
5.387
RXRA
1DSZ
Xanthogalenol
7.093
SRC
1O4R
Xanthogalenol
7.142


### 3.6. Gene Ontology (GO) Functional Analysis and KEGG Pathway Enrichment Analysis

Enriched gene ontology terms for BP, CC, and MF of potential therapeutic fracture targets from the main active ingredients of DR are shown in Figure4. In the BP (Figure 4(a)), positive regulation of transcription from RNA polymerase II promoter involved 33 (22.92%) potential therapeutic fracture targets, signal transduction involved 30 (20.84%) potential therapeutic fracture targets, negative regulation of transcription from RNA polymerase II promoter involved 20 (13.89%) potential therapeutic fracture targets, positive regulation of transcription and DNA-template involved 19 (13.19%) potential therapeutic fracture targets, and transcription initiation from RNA polymerase II promoter involved 18 (12.5%) potential therapeutic fracture targets. In the CC (Figure 4(b)), cytosol involved 63 (43.75%) potential therapeutic fracture targets, extracellular exosome involved 60 (41.67%) potential therapeutic fracture targets, cytoplasm involved 58 (40.28%) potential therapeutic fracture targets, nucleus involved 56 (38.89%) potential therapeutic fracture targets, and plasma membrane involved 53 (36.81%) potential therapeutic fracture targets. In the MF (Figure 4(c)), protein binding involved 110 (76.39%) potential therapeutic fracture targets, zinc ion binding involved 31 (21.53%) potential therapeutic fracture targets, identical protein binding involved 29 (20.14%) potential therapeutic fracture targets, ATP binding involved 27 (18.75%) potential therapeutic fracture targets, and enzyme binding involved 23 (15.97%) potential therapeutic fracture targets.Figure 4
Enriched gene ontology terms of potential therapeutic fracture targets from main active ingredients ofDrynariae Rhizoma. Note. (a) Biological process (BP), (b) cellular component (CC), and (c) molecular function (MF).
(a)
(b)
(c)Enriched KEGG pathways of potential targets for treating fracture from the main active ingredients of DR are shown in Figure5. The MAPK signaling pathway was identified as an important signaling pathway involving 17 (11.81%) potential therapeutic fracture targets with P=7.82×10−6. The PI3K-Akt signaling pathway involved 17 (11.81%) potential therapeutic fracture targets, the Rap1 signaling pathway involved 14 (9.72%) potential therapeutic fracture targets, the Ras signaling pathway involved 14 (9.72%) potential therapeutic fracture targets, and the signaling pathways regulating pluripotency of stem cells involved 12 (9.03%) potential therapeutic fracture targets.Figure 5
Enriched KEGG pathways of potential targets for treating fracture from main active ingredients ofDrynariae Rhizoma.


### 3.7. Protein Class Corresponding to Common Gene Targets

The protein class corresponding to potential targets for treating fracture from the main active ingredients of DR is presented in Table6. The results showed that DR treatment of the fracture process involved a variety of substances, such as signaling molecule, transcription factor, receptor, enzyme modulator, chaperone, cell adhesion molecule, protein (transporter, transfer protein, carrier protein, calcium-binding protein, defense protein, and immune protein), enzyme modulator, and enzymes (oxidoreductase, kinase, phosphatase, hydrolase, ligase, protease, isomerase, lyase, enzyme regulator, and transferase).Table 6
The protein class corresponding to potential targets for treating fracture from main active ingredients ofDrynariae Rhizoma.
No.
Gene name
Protein class
1
ADH1B
Oxidoreductase
2
ADH1C
Oxidoreductase
3
ADH7
Oxidoreductase
4
AGXT
Transferase
5
AKT1
Calcium-binding protein; kinase; transfer/carrier protein; transferase
6
AKT2
Calcium-binding protein; kinase; transfer/carrier protein; transferase
7
ALPP
Hydrolase; phosphatase
8
ANG
None
9
ANXA5
None
10
AR
Nucleic acid binding; receptor; transcription factor
11
ASS1
Ligase
12
B2M
Defense/immunity protein
13
BCHE
None
14
BMP2
Signaling molecule
15
BMP7
Signaling molecule
16
BMPR1A
Kinase; receptor; transferase
17
BRAF
None
18
CA2
None
19
CASP1
Enzyme modulator; hydrolase; protease
20
CASP7
Enzyme modulator; hydrolase; protease
21
CASP8
Enzyme modulator; hydrolase; protease
22
CBR3
None
23
CBS
Hydrolase; isomerase; lyase
24
CD1A
None
25
CD44
None
26
CETP
None
27
CFTR
Transporter
28
CKB
Kinase; transferase
29
CMA1
Hydrolase; protease
30
COMT
Transferase
31
CRAT
Transferase
32
CSF2RB
Receptor
33
CSK
None
34
CTSB
Enzyme modulator; hydrolase; protease
35
CTSD
Hydrolase; protease
36
CTSG
Hydrolase; protease
37
DAPK1
Kinase; transferase
38
DPP4
Enzyme modulator; hydrolase; protease
39
EGFR
None
40
ELANE
Hydrolase; protease
41
ESR1
Nucleic acid binding; receptor; transcription factor
42
ESR2
Nucleic acid binding; receptor; transcription factor
43
ESRRA
Nucleic acid binding; receptor; transcription factor
44
F10
Hydrolase; protease
45
F2
Hydrolase; protease
46
F3
Defense/immunity protein; receptor
47
F7
Hydrolase; protease
48
F9
Hydrolase; protease
49
FGFR1
None
50
FGFR2
None
51
G6PD
Oxidoreductase
52
GAPDH
Oxidoreductase
53
GBA
None
54
GC
Transfer/carrier protein
55
GM2A
Transfer/carrier protein
56
GSK3B
Kinase; transferase
57
GSR
Oxidoreductase
58
GSTM1
None
59
GSTP1
None
60
GSTT1
None
61
HDAC4
None
62
HGF
Hydrolase; protease
63
HMGCR
None
64
HMOX1
Oxidoreductase
65
HRAS
Enzyme modulator
66
HSD17B1
Oxidoreductase
67
HSD17B4
None
68
HSP90AA1
Chaperone
69
IGF1R
None
70
IGFBP1
Enzyme modulator
71
IL10
None
72
IL1R1
Receptor
73
IL4
None
74
INS
None
75
INSR
None
76
ITGA1
None
77
JAK2
None
78
KCNAB2
Oxidoreductase; transporter
79
LCK
None
80
LDHB
Oxidoreductase
81
LGALS3
Cell adhesion molecule; signaling molecule
82
MAPK1
Kinase; transferase
83
MAPK10
Kinase; transferase
84
MAPK14
Kinase; transferase
85
MAPK8
Kinase; transferase
86
MDH2
Oxidoreductase
87
MIF
None
88
MME
Hydrolase; protease
89
MMP1
Hydrolase; protease
90
MMP3
Hydrolase; protease
91
MMP8
Hydrolase; protease
92
MTAP
Transferase
93
NCOA1
Transcription factor; transferase
94
NCOA2
Transcription factor; transferase
95
NNMT
Transferase
96
NOG
None
97
NOS2
None
98
NQO1
None
99
NR1H2
Nucleic acid binding; receptor; transcription factor
100
NR1H4
Nucleic acid binding; receptor; transcription factor
101
NR1I2
Nucleic acid binding; receptor; transcription factor
102
NR3C1
Nucleic acid binding; receptor; transcription factor
103
NR3C2
Nucleic acid binding; receptor; transcription factor
104
NR5A1
Transcription factor
105
NTRK1
None
106
NTRK2
None
107
OTC
None
108
PARP1
None
109
PDE4A
None
110
PDE4D
None
111
PGR
Nucleic acid binding; receptor; transcription factor
112
PKLR
None
113
PLAU
Hydrolase; protease
114
PLG
Hydrolase; protease
115
PNPO
Oxidoreductase
116
PON1
None
117
POR
None
118
PPARA
Nucleic acid binding; receptor; transcription factor
119
PPARD
Nucleic acid binding; receptor; transcription factor
120
PPARG
Nucleic acid binding; receptor; transcription factor
121
PPIB
None
122
PRDX2
Oxidoreductase
123
PRKACA
None
124
PROCR
Enzyme modulator; receptor
125
QDPR
Oxidoreductase
126
RBP4
Transfer/carrier protein
127
REN
Hydrolase; protease
128
RXRA
Nucleic acid binding; receptor; transcription factor
129
SEC14L2
None
130
SHBG
None
131
SLC9A3R1
None
132
SOD1
Oxidoreductase
133
SRC
None
134
STS
Hydrolase
135
SULT2A1
None
136
THRA
Nucleic acid binding; receptor; transcription factor
137
THRB
Nucleic acid binding; receptor; transcription factor
138
TNF
Signaling molecule
139
TPI1
Isomerase
140
TRAF2
Signaling molecule
141
TTPA
Transfer/carrier protein
142
TTR
Transfer/carrier protein; transporter
143
TYMP
Transferase
144
VDR
Nucleic acid binding; receptor; transcription factor


### 3.8. Signaling Pathway Integration

Four pathways associated with the potential targets of DR main active ingredients for treating fracture are presented in Figure6. The arrow (⟶) indicates the promoting effect, the T-arrows (⊣) indicate the inhibition, and the arrows of different colors represent different signaling pathways. The targets of the signaling pathway were marked as light blue, and the potential targets of DR main active ingredients for treating fracture were marked as dark blue. There were 21 (14.58%) potential targets of main active ingredients of DR for treating fracture in the PI3K-AKT, MAPK, Ras, and VEGF signaling pathways, indicating that the fracture targets play a role in these signaling pathways. In addition, some targets play a role in a variety of signaling pathways, such as Ras, RafB, AKT/PKB, PI3K, ERK, and JNK.Figure 6
Antifracture pathways of potential targets for treating fracture from main active ingredients ofDrynariae Rhizoma. Note. The arrow (⟶) indicates the promoting effect, the T-arrows (⊣) indicate the inhibition, and the arrows of different colors represent different signaling pathways. The targets of the signaling pathway were marked as light blue, and the potential targets of main active ingredients of DR for treating fracture were marked as dark blue.


## 3.1. Active Ingredients ofDrynariae Rhizoma

A total of 71 ingredients of DR were retrieved from TCMSP, and 18 active ingredients were screened according to the biological functions of DR. However, marioside_qt (Molecule ID: MOL009087) was removed because it could not be recognized by the PubChem or Zinc database. The remaining 17 active ingredients are shown in Table1, including (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one, aureusidin, eriodictyol (flavanone), stigmasterol, beta-sitosterol, kaempferol, naringenin, (+)-catechin, eriodictyol, digallate, luteolin, 22-stigmasten-3-one, cyclolaudenol acetate, cycloartenone, cyclolaudenol, davallioside A_qt, and xanthogalenol.Table 1
Main active ingredients inDrynariae Rhizoma.
No.
Molecule ID
Molecule name
Chemical formula
Structure
OB (%)
DL
1
MOL001040
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
C15H12O5
42.36
0.21
2
MOL001978
Aureusidin
C15H10O6
53.42
0.24
3
MOL002914
Eriodictyol (flavanone)
C15H12O6
41.35
0.24
4
MOL000449
Stigmasterol
C29H48O
43.83
0.76
5
MOL000358
β-Sitosterol
C29H50O
36.91
0.75
6
MOL000422
Kaempferol
C15H10O6
41.88
0.24
7
MOL004328
Naringenin
C15H12O5
59.29
0.21
8
MOL000492
(+)-Catechin
C15H14O6
54.83
0.24
9
MOL005190
Eriodictyol
C15H12O6
71.79
0.24
10
MOL000569
Digallate
C14H10O9
61.85
0.26
11
MOL000006
Luteolin
C15H10O6
36.16
0.25
12
MOL009061
22-Stigmasten-3-one
C29H48O
39.25
0.76
13
MOL009063
Cyclolaudenol acetate
C33H54O2
41.66
0.79
14
MOL009075
Cycloartenone
C30H48O
40.57
0.79
15
MOL009076
Cyclolaudenol
C31H52O
39.05
0.79
16
MOL009078
Davallioside A_qt
C25H29NO12
62.65
0.51
17
MOL009091
Xanthogalenol
C21H22O5
41.08
0.32


## 3.2. Gene Target Prediction

A total of 303 gene targets associated with the potential active ingredients of DR were retrieved in the UniProt database. A total of 3,173 fracture-related genes were received, and 3,054 genes remained after deletion of the duplicate and false-positive genes. Common gene target screening for fracture and DR are shown in Figure1. A total of 144 common gene targets of DR and fracture were received, indicating the potential targets for DR to treat fractures, as shown in Table 2.Figure 1
Venn diagram of common gene target screening for fracture andDrynariae Rhizoma.Table 2
Information of potential gene targets for treating fracture fromDrynariae Rhizoma.
No.
PDB ID
Gene target
1
1HSZ
ADH1B
2
1HT0
ADH1C
3
1D1T
ADH7
4
1H0C
AGXT
5
3CQW
AKT1
6
1O6L
AKT2
7
2GLQ
ALPP
8
1ANG
ANG
9
1HAK
ANXA5
10
1E3G
AR
11
2NZ2
ASS1
12
1ONQ
B2M
13
1XLV
BCHE
14
1ES7
BMP2
15
1M4U
BMP7
16
1ES7
BMPR1A
17
1UWJ
BRAF
18
1A42
CA2
19
1ICE
CASP1
20
1K86
CASP7
21
2C2Z
CASP8
22
2HRB
CBR3
23
1JBQ
CBS
24
1ONQ
CD1A
25
1POZ
CD44
26
2OBD
CETP
27
1XMI
CFTR
28
3DRB
CKB
29
1NN6
CMA1
30
3BWY
COMT
31
1NM8
CRAT
32
1C8P
CSF2RB
33
1BYG
CSK
34
1CSB
CTSB
35
1LYW
CTSD
36
1CGH
CTSG
37
1JKL
DAPK1
38
2HHA
DPP4
39
1M17
EGFR
40
1H1B
ELANE
41
1R5K
ESR1
42
1QKM
ESR2
43
2PJL
ESRRA
44
1F0R
F10
45
1A3B
F2
46
1Z6J
F3
47
1Z6J
F7
48
1RFN
F9
49
2FGI
FGFR1
50
2PVY
FGFR2
51
2BH9
G6PD
52
1ZNQ
GAPDH
53
1OGS
GBA
54
1J78
GC
55
1PUB
GM2A
56
1J1B
GSK3B
57
1GRE
GSR
58
1XWK
GSTM1
59
11GS
GSTP1
60
2C3Q
GSTT1
61
2VQM
HDAC4
62
1GMN
HGF
63
1HWL
HMGCR
64
1S8C
HMOX1
65
5P21
HRAS
66
1DHT
HSD17B1
67
1ZBQ
HSD17B4
68
1YET
HSP90AA1
69
2OJ9
IGF1R
70
1ZT3
IGFBP1
71
2ILK
IL10
72
1G0Y
IL1R1
73
2CYK
IL4
74
1TYL
INS
75
2AUH
INSR
76
1QCY
ITGA1
77
2B7A
JAK2
78
1ZSX
KCNAB2
79
1QPC
LCK
80
1I0Z
LDHB
81
1KJL
LGALS3
82
1TVO
MAPK1
83
1JNK
MAPK10
84
1A9U
MAPK14
85
1UKI
MAPK8
86
2DFD
MDH2
87
1GCZ
MIF
88
1DMT
MME
89
1HFC
MMP1
90
1QIA
MMP3
91
1JAP
MMP8
92
1SD2
MTAP
93
2P54
NCOA1
94
1MVC
NCOA2
95
2IIP
NNMT
96
1M4U
NOG
97
1NSI
NOS2
98
1KBQ
NQO1
99
1UPV
NR1H2
100
3FXV
NR1H4
101
1NRL
NR1I2
102
1P93
NR3C1
103
2A3I
NR3C2
104
1YOW
NR5A1
105
1WWA
NTRK1
106
1WWB
NTRK2
107
1OTH
OTC
108
1WOK
PARP1
109
2QYK
PDE4A
110
1PTW
PDE4D
111
1ZUC
PGR
112
2VGB
PKLR
113
1VJA
PLAU
114
2PK4
PLG
115
1NRG
PNPO
116
1V04
PON1
117
1B1C
POR
118
2P54
PPARA
119
2J14
PPARD
120
1ZEO
PPARG
121
1CYN
PPIB
122
1QMV
PRDX2
123
2GU8
PRKACA
124
1LQV
PROCR
125
1HDR
QDPR
126
1QAB
RBP4
127
2G1N
REN
128
1MVC
RXRA
129
1OLM
SEC14L2
130
1F5F
SHBG
131
1I92
SLC9A3R1
132
2C9V
SOD1
133
1YOL
SRC
134
1P49
STS
135
1J99
SULT2A1
136
1NAV
THRA
137
1NAX
THRB
138
1A8M
TNF
139
1HTI
TPI1
140
1D0A
TRAF2
141
1OIZ
TTPA
142
1QAB
TTR
143
1UOU
TYMP
144
3CS4
VDR


## 3.3. Ingredient-Target Network ofDrynariae Rhizoma

The active ingredients and gene targets of DR was inputted into Cytoscape software to construct the ingredient-target network, as shown in Figure2. In the network, the pink oval nodes represent the main active ingredients of DR, and the light green rectangle nodes represent the potential gene targets for DR to treat fractures. The line represents the correlation between the active ingredients of DR and the gene targets. There are 161 nodes and 774 lines in the network. An active ingredient could be linked to different gene targets, and a gene target could be linked to different active ingredients, suggesting the multicomponent and multitarget characteristics of DR. The topology properties of active ingredients of DR are shown in Supplementary Table 1. Both cyclolaudenol and cycloartenone were linked to a maximum number of gene targets, with 70 (48.61%) different gene targets. Cyclolaudenol acetate was linked to 54 (37.5%) different gene targets. Xanthogalenol was linked to a minimum number of gene targets for a total of 29 (20.14%). In addition, there were four gene targets with the top four degree values, betweenness centrality, and closeness centrality at the same time (Table 3), which were NCOA1, GSK3B, TTPA, and MAPK1.Figure 2
Ingredient-target network ofDrynariae Rhizoma. Note. The pink oval nodes () are the main active ingredients of Drynariae Rhizoma, and the light green rectangle () is the potential target for treating fracture of Drynariae Rhizoma.Table 3
Gene targets with the top 4 degree values, betweenness centrality, and closeness centrality.
No.
Gene targets
Degree (rank)
Betweenness centrality (rank)
Closeness centrality (rank)
1
NCOA1
15 (1)
0.038 (1)
0.505 (1)
2
MAPK1
13 (2)
0.023 (3)
0.464 (4)
3
GSK3B
12 (3)
0.028 (2)
0.502 (2)
4
TTPA
12 (4)
0.022 (4)
0.466 (3)


## 3.4. Protein-Protein Interaction ofDrynariae Rhizoma

The PPI network of DR is shown in Figure3. In the network, the node represents the protein, and the size and color of the node represent the value of the degree. The larger the node and the brighter the color (yellow to blue), the greater the value of the degree. The line indicates the association between proteins. Results showed that there were 143 nodes and 315 lines.Figure 3
Protein-protein interaction network ofDrynariae Rhizoma. Note. The size and the color of the node represents the value of the degree (yellow ⟶ orange ⟶ blue indicates that the degree value is from low to high, and the small circle represents a low degree value).Degree in the network indicates the number of proteins that a protein has interacting with. In other words, top-degree protein targets screened in PPI plays a pivotal role in the treatment of fractures with DR. Five important protein targets with top degree of DR were identified in the PPI network and are shown in Table4. They were MAPK1, SRC, HRAS, RXRA, and NCOA1.Table 4
Five important protein targets with top degree ofDrynariae Rhizoma.
No.
Degree
PDB ID
Protein target name
1
27
1TVO
MAPK1
2
23
1YOL
SRC
3
22
5P21
HRAS
4
20
1MVC
RXRA
5
18
2P54
NCOA1


## 3.5. Molecular Docking

Three important protein targets with top degree of DR were identified by SystemsDock, including SRC, RXRA, and NCOA1. Dock-IN score of these three proteins docked with 17 active ingredients of DR are shown in Table5. Molecular docking results showed that there were 17 (33.33%) with a dock-IN score greater than 7.0, 24 (47.06%) with a dock-IN score between 7.0 and 5.0, 8 (15.69%) with a dock-IN score between 5.0 and 4.25, and 2 (3.92%) with a dock-IN score less than 4.25.Table 5
Molecular docking of three important protein targets fromDrynariae Rhizoma.
Protein target
PDB ID
Ingredients
Dock-IN score
NCOA1
1NQ7
(+)-Catechin
7.111
RXRA
1DSZ
(+)-Catechin
4.624
SRC
1O4R
(+)-Catechin
5.908
NCOA1
1NQ7
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
6.694
RXRA
1DSZ
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
4.605
SRC
1O4R
(2R)-5,7-Dihydroxy-2-(4-hydroxyphenyl)chroman-4-one
5.783
NCOA1
1NQ7
22-Stigmasten-3-one
8.422
RXRA
1DSZ
22-Stigmasten-3-one
5.553
SRC
1O4R
22-Stigmasten-3-one
5.425
NCOA1
1NQ7
Aureusidin
7.153
RXRA
1DSZ
Aureusidin
4.622
SRC
1O4R
Aureusidin
5.861
NCOA1
1NQ7
Beta-sitosterol
8.34
RXRA
1DSZ
Beta-sitosterol
5.587
SRC
1O4R
Beta-sitosterol
5.374
NCOA1
1NQ7
Cycloartenone
8.427
RXRA
1DSZ
Cycloartenone
5.658
SRC
1O4R
Cycloartenone
5.693
NCOA1
1NQ7
Cyclolaudenol
8.376
RXRA
1DSZ
Cyclolaudenol
5.534
SRC
1O4R
Cyclolaudenol
5.376
NCOA1
1NQ7
Cyclolaudenol acetate
8.422
RXRA
1DSZ
Cyclolaudenol acetate
7.052
SRC
1O4R
Cyclolaudenol acetate
6.364
NCOA1
1NQ7
Davallioside A_qt
7.904
RXRA
1DSZ
Davallioside A_qt
5.779
SRC
1O4R
Davallioside A_qt
5.58
NCOA1
1NQ7
Digallate
4.313
RXRA
1DSZ
Digallate
3.789
SRC
1O4R
Digallate
3.671
NCOA1
1NQ7
Eriodictyol
7.109
RXRA
1DSZ
Eriodictyol
4.628
SRC
1O4R
Eriodictyol
5.821
NCOA1
1NQ7
Eriodictyol (flavanone)
7.113
RXRA
1DSZ
Eriodictyol (flavanone)
4.633
SRC
1O4R
Eriodictyol (flavanone)
5.824
NCOA1
1NQ7
Kaempferol
7.125
RXRA
1DSZ
Kaempferol
4.613
SRC
1O4R
Kaempferol
5.929
NCOA1
1NQ7
Luteolin
7.089
RXRA
1DSZ
Luteolin
4.621
SRC
1O4R
Luteolin
5.847
NCOA1
1NQ7
Naringenin
7.12
RXRA
1DSZ
Naringenin
6.016
SRC
1O4R
Naringenin
5.883
NCOA1
1NQ7
Stigmasterol
8.376
RXRA
1DSZ
Stigmasterol
5.918
SRC
1O4R
Stigmasterol
5.3
NCOA1
1NQ7
Xanthogalenol
5.387
RXRA
1DSZ
Xanthogalenol
7.093
SRC
1O4R
Xanthogalenol
7.142


## 3.6. Gene Ontology (GO) Functional Analysis and KEGG Pathway Enrichment Analysis

Enriched gene ontology terms for BP, CC, and MF of potential therapeutic fracture targets from the main active ingredients of DR are shown in Figure4. In the BP (Figure 4(a)), positive regulation of transcription from RNA polymerase II promoter involved 33 (22.92%) potential therapeutic fracture targets, signal transduction involved 30 (20.84%) potential therapeutic fracture targets, negative regulation of transcription from RNA polymerase II promoter involved 20 (13.89%) potential therapeutic fracture targets, positive regulation of transcription and DNA-template involved 19 (13.19%) potential therapeutic fracture targets, and transcription initiation from RNA polymerase II promoter involved 18 (12.5%) potential therapeutic fracture targets. In the CC (Figure 4(b)), cytosol involved 63 (43.75%) potential therapeutic fracture targets, extracellular exosome involved 60 (41.67%) potential therapeutic fracture targets, cytoplasm involved 58 (40.28%) potential therapeutic fracture targets, nucleus involved 56 (38.89%) potential therapeutic fracture targets, and plasma membrane involved 53 (36.81%) potential therapeutic fracture targets. In the MF (Figure 4(c)), protein binding involved 110 (76.39%) potential therapeutic fracture targets, zinc ion binding involved 31 (21.53%) potential therapeutic fracture targets, identical protein binding involved 29 (20.14%) potential therapeutic fracture targets, ATP binding involved 27 (18.75%) potential therapeutic fracture targets, and enzyme binding involved 23 (15.97%) potential therapeutic fracture targets.Figure 4
Enriched gene ontology terms of potential therapeutic fracture targets from main active ingredients ofDrynariae Rhizoma. Note. (a) Biological process (BP), (b) cellular component (CC), and (c) molecular function (MF).
(a)
(b)
(c)Enriched KEGG pathways of potential targets for treating fracture from the main active ingredients of DR are shown in Figure5. The MAPK signaling pathway was identified as an important signaling pathway involving 17 (11.81%) potential therapeutic fracture targets with P=7.82×10−6. The PI3K-Akt signaling pathway involved 17 (11.81%) potential therapeutic fracture targets, the Rap1 signaling pathway involved 14 (9.72%) potential therapeutic fracture targets, the Ras signaling pathway involved 14 (9.72%) potential therapeutic fracture targets, and the signaling pathways regulating pluripotency of stem cells involved 12 (9.03%) potential therapeutic fracture targets.Figure 5
Enriched KEGG pathways of potential targets for treating fracture from main active ingredients ofDrynariae Rhizoma.


## 3.7. Protein Class Corresponding to Common Gene Targets

The protein class corresponding to potential targets for treating fracture from the main active ingredients of DR is presented in Table6. The results showed that DR treatment of the fracture process involved a variety of substances, such as signaling molecule, transcription factor, receptor, enzyme modulator, chaperone, cell adhesion molecule, protein (transporter, transfer protein, carrier protein, calcium-binding protein, defense protein, and immune protein), enzyme modulator, and enzymes (oxidoreductase, kinase, phosphatase, hydrolase, ligase, protease, isomerase, lyase, enzyme regulator, and transferase).Table 6
The protein class corresponding to potential targets for treating fracture from main active ingredients ofDrynariae Rhizoma.
No.
Gene name
Protein class
1
ADH1B
Oxidoreductase
2
ADH1C
Oxidoreductase
3
ADH7
Oxidoreductase
4
AGXT
Transferase
5
AKT1
Calcium-binding protein; kinase; transfer/carrier protein; transferase
6
AKT2
Calcium-binding protein; kinase; transfer/carrier protein; transferase
7
ALPP
Hydrolase; phosphatase
8
ANG
None
9
ANXA5
None
10
AR
Nucleic acid binding; receptor; transcription factor
11
ASS1
Ligase
12
B2M
Defense/immunity protein
13
BCHE
None
14
BMP2
Signaling molecule
15
BMP7
Signaling molecule
16
BMPR1A
Kinase; receptor; transferase
17
BRAF
None
18
CA2
None
19
CASP1
Enzyme modulator; hydrolase; protease
20
CASP7
Enzyme modulator; hydrolase; protease
21
CASP8
Enzyme modulator; hydrolase; protease
22
CBR3
None
23
CBS
Hydrolase; isomerase; lyase
24
CD1A
None
25
CD44
None
26
CETP
None
27
CFTR
Transporter
28
CKB
Kinase; transferase
29
CMA1
Hydrolase; protease
30
COMT
Transferase
31
CRAT
Transferase
32
CSF2RB
Receptor
33
CSK
None
34
CTSB
Enzyme modulator; hydrolase; protease
35
CTSD
Hydrolase; protease
36
CTSG
Hydrolase; protease
37
DAPK1
Kinase; transferase
38
DPP4
Enzyme modulator; hydrolase; protease
39
EGFR
None
40
ELANE
Hydrolase; protease
41
ESR1
Nucleic acid binding; receptor; transcription factor
42
ESR2
Nucleic acid binding; receptor; transcription factor
43
ESRRA
Nucleic acid binding; receptor; transcription factor
44
F10
Hydrolase; protease
45
F2
Hydrolase; protease
46
F3
Defense/immunity protein; receptor
47
F7
Hydrolase; protease
48
F9
Hydrolase; protease
49
FGFR1
None
50
FGFR2
None
51
G6PD
Oxidoreductase
52
GAPDH
Oxidoreductase
53
GBA
None
54
GC
Transfer/carrier protein
55
GM2A
Transfer/carrier protein
56
GSK3B
Kinase; transferase
57
GSR
Oxidoreductase
58
GSTM1
None
59
GSTP1
None
60
GSTT1
None
61
HDAC4
None
62
HGF
Hydrolase; protease
63
HMGCR
None
64
HMOX1
Oxidoreductase
65
HRAS
Enzyme modulator
66
HSD17B1
Oxidoreductase
67
HSD17B4
None
68
HSP90AA1
Chaperone
69
IGF1R
None
70
IGFBP1
Enzyme modulator
71
IL10
None
72
IL1R1
Receptor
73
IL4
None
74
INS
None
75
INSR
None
76
ITGA1
None
77
JAK2
None
78
KCNAB2
Oxidoreductase; transporter
79
LCK
None
80
LDHB
Oxidoreductase
81
LGALS3
Cell adhesion molecule; signaling molecule
82
MAPK1
Kinase; transferase
83
MAPK10
Kinase; transferase
84
MAPK14
Kinase; transferase
85
MAPK8
Kinase; transferase
86
MDH2
Oxidoreductase
87
MIF
None
88
MME
Hydrolase; protease
89
MMP1
Hydrolase; protease
90
MMP3
Hydrolase; protease
91
MMP8
Hydrolase; protease
92
MTAP
Transferase
93
NCOA1
Transcription factor; transferase
94
NCOA2
Transcription factor; transferase
95
NNMT
Transferase
96
NOG
None
97
NOS2
None
98
NQO1
None
99
NR1H2
Nucleic acid binding; receptor; transcription factor
100
NR1H4
Nucleic acid binding; receptor; transcription factor
101
NR1I2
Nucleic acid binding; receptor; transcription factor
102
NR3C1
Nucleic acid binding; receptor; transcription factor
103
NR3C2
Nucleic acid binding; receptor; transcription factor
104
NR5A1
Transcription factor
105
NTRK1
None
106
NTRK2
None
107
OTC
None
108
PARP1
None
109
PDE4A
None
110
PDE4D
None
111
PGR
Nucleic acid binding; receptor; transcription factor
112
PKLR
None
113
PLAU
Hydrolase; protease
114
PLG
Hydrolase; protease
115
PNPO
Oxidoreductase
116
PON1
None
117
POR
None
118
PPARA
Nucleic acid binding; receptor; transcription factor
119
PPARD
Nucleic acid binding; receptor; transcription factor
120
PPARG
Nucleic acid binding; receptor; transcription factor
121
PPIB
None
122
PRDX2
Oxidoreductase
123
PRKACA
None
124
PROCR
Enzyme modulator; receptor
125
QDPR
Oxidoreductase
126
RBP4
Transfer/carrier protein
127
REN
Hydrolase; protease
128
RXRA
Nucleic acid binding; receptor; transcription factor
129
SEC14L2
None
130
SHBG
None
131
SLC9A3R1
None
132
SOD1
Oxidoreductase
133
SRC
None
134
STS
Hydrolase
135
SULT2A1
None
136
THRA
Nucleic acid binding; receptor; transcription factor
137
THRB
Nucleic acid binding; receptor; transcription factor
138
TNF
Signaling molecule
139
TPI1
Isomerase
140
TRAF2
Signaling molecule
141
TTPA
Transfer/carrier protein
142
TTR
Transfer/carrier protein; transporter
143
TYMP
Transferase
144
VDR
Nucleic acid binding; receptor; transcription factor


## 3.8. Signaling Pathway Integration

Four pathways associated with the potential targets of DR main active ingredients for treating fracture are presented in Figure6. The arrow (⟶) indicates the promoting effect, the T-arrows (⊣) indicate the inhibition, and the arrows of different colors represent different signaling pathways. The targets of the signaling pathway were marked as light blue, and the potential targets of DR main active ingredients for treating fracture were marked as dark blue. There were 21 (14.58%) potential targets of main active ingredients of DR for treating fracture in the PI3K-AKT, MAPK, Ras, and VEGF signaling pathways, indicating that the fracture targets play a role in these signaling pathways. In addition, some targets play a role in a variety of signaling pathways, such as Ras, RafB, AKT/PKB, PI3K, ERK, and JNK.Figure 6
Antifracture pathways of potential targets for treating fracture from main active ingredients ofDrynariae Rhizoma. Note. The arrow (⟶) indicates the promoting effect, the T-arrows (⊣) indicate the inhibition, and the arrows of different colors represent different signaling pathways. The targets of the signaling pathway were marked as light blue, and the potential targets of main active ingredients of DR for treating fracture were marked as dark blue.


## 4. Discussion

In order to reveal the relationship between fracture and the active ingredients involved in the DR, we predicted the mechanism of DR treatment fractures by constructing a biological network of interactions between active ingredients and common gene targets and common protein targets from a molecular level. A total of 17 active ingredients of DR were received in our study, including (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one, aureusidin, eriodictyol (flavanone), stigmasterol, beta-sitosterol, kaempferol, naringenin, (+)-catechin, eriodictyol, digallate, luteolin, 22-stigmasten-3-one, cyclolaudenol acetate, cycloartenone, cyclolaudenol, davallioside A_qt, and xanthogalenol. Most of them were polyphenolic compounds, which are also called flavonoids. Flavonoids are considered to be the main active ingredients of DR and have been reported to reduce bone loss in ovariectomized rats [24]. In addition, Kang Suk-Nam finds that the total phenolics and flavonoids of DR are better extracted with 70% ethanol instead of water, and this ethanol extraction method also makes these extracts have higher antioxidant activity and in vitro antiosteoporosis effect [25]. In the ingredient-target network, all active ingredients were also identified to bind well to the fracture gene targets, binding to at least 29 (20.14%) different gene targets. Therefore, the 17 active ingredients of DR may have the effect of reducing bone loss and promoting fracture healing.In our study, 144 common gene targets of DR and fracture were received, and 774 interactions between the active ingredients of DR and common gene targets were found. Some gene targets have been confirmed by clinical trials or animal experiments. For example, Guimarães et al. found that polymorphisms in the FGFR1 and BMP4 genes were associated with fracture nonunion in patients [26]. And our team's previous study also found that the total flavonoids of DP could promote osteogenesis and mineralization in rats with tibial defects by increasing the gene expression of BMP2, BMP4, BMPR1A, and Smadl [27]. In the ingredient-target network, NCOA1, GSK3B, TTPA, and MAPK1 were identified as important gene targets based on degree values, betweenness centrality, and closeness centrality. Qin et al. found that NCOA1 promotes angiogenesis by upregulating HIF1α- and AP-1-mediated VEGFa transcription [28]. Galli et al. demonstrated by cell experiments that inhibition of GSK3B could increase cytoplasmic availability of b-catenin, thereby enhancing Wnt classical signaling and osteoblastic differentiation [29]. Fujita et al. found that mice deficient in TTPA developed a high bone mass phenotype in vertebrae and long bones due to lower bone resorption [30]. Matsushita et al. confirmed that MAPK1 (also called ERK2) plays an important role in osteoblast differentiation and osteoclastogenesis [31]. These gene targets are involved in vascularization, osteoblast differentiation, and osteoclastogenesis in fracture repair. Besides, we found that one active ingredient can interact with different gene targets, and one gene target can interact with different active ingredients, which is consistent with the modern drug theory of “multi-ingredient, multitarget” [9].To identify the interactions of proteins corresponding to common genes, we conducted a PPI network. A total of 143 common protein targets for DR and fracture were received, with 315 PPIs. In addition, MAPK1, SRC, HRAS, RXRA, and NCOA1 were identified as the five most important target proteins. Previous studies have found that MAPK1 and SRC could promote proliferation and differentiation of myeloid cells and inhibit apoptosis [32, 33]. Clinical cases have found that elevated levels of fibroblast growth factor 23 in patients with dysplasia are associated with HRAS mutations [34]. RXRA is an essential cofactor in the action of 1,25-dihydroxyvitamin D, and umbilical cord RXRA methylation was inversely related to offspring bone mineral content [35]. Coronnello et al. found that NCOA1 modulate the estrogen effects in bone, and miR-488-5p overexpression reduces NCOA1 protein levels, thereby reducing bone mineral density [36]. These protein targets are associated with bone growth and angiogenesis in fracture repair. At the same time, we docked SRC, RXRA, and NCOA1 with 17 potential active ingredients of DR and found that 41 (80.39%) had moderate binding potential, suggesting that DR could bind well to fracture-related protein targets.In order to identify the function of the common gene, we performed GO functional analysis on these genes. The results showed that the common gene involves multiple processes, parts and functions in BP, CC, and MF, which was consistent with existing studies about DR and fracture repair. For example, in the BP, 33 (22.92%) gene targets were involved in positive regulation of transcription from the RNA polymerase II promoter, and 30 (20.84%) gene targets were involved in signal transduction. Previous studies have shown that the promoter activates the polymerase to bind precisely to the template DNA and has the specificity of transcription initiation [37]. The RNA polymerase II promoter responsible for mRNA transcription is the largest and most important class of promoters [37]. This provides conditions for DR to initiate osteogenic targets. Besides, some signal transduction genes have been found in experiments. Song Nan found that VEGFR-2 may play a signal transduction role for naringin, one ingredient of DR, to stimulate angiogenesis and promote fracture healing [38]. In the CC, 63 (43.75%) gene targets were involved in cytosol, 60 (41.67%) gene targets were involved in extracellular exosome, and 58 (40.28%) gene targets were involved in cytoplasm. This indicates that the recovery of the fracture requires the support of various components in the cell, which is consistent with previous studies [39]. In the MF, 110 (76.39%) gene targets were involved in protein binding, suggesting that mutual recognition between proteins has good gene regulation conditions. This is consistent with the protein class corresponding to the potential target. These results were further validated in the protein class corresponding to the common gene. In the protein class, all of these common genes have been found to regulate a variety of fracture-related molecules, such as transcription factors, receptors, enzyme regulators, molecular chaperones, cell adhesion molecules, enzyme, and so on.In order to identify the synergistic mechanism of DR for fracture, we performed KEGG pathway enrichment analysis and summarized some important signaling pathways, which provides direction for future research. In the KEGG pathway enrichment analysis, 17 (11.81%) gene targets were involved in MAPK signaling pathway, 17 (11.81%) gene targets were involved in PI3K-Akt signaling pathway, 14 (9.72%) gene targets were involved in Ras signaling pathway, and 6 (4.17%) gene targets were involved in VEGF signaling pathway, which suggest that common gene targets play a role in repairing fractures in multiple signaling pathways. MAPK and PI3K/AKT signaling pathways have been demonstrated to promote osteoblastic bone formation [40]. Zhang et al. confirmed that total flavonoids from DR promote the osteogentic differentiation of ciliary neurotrophic factor-modified myoblasts by activating p38 MAPK signaling pathway [41]. Moreover, total flavonoids of DR could promote osteogenic differentiation of rat dental pulp stem cells via the PI3K/Akt pathway [42]. Lin et al. found that the effect of naringin on the healing of fracture may be related to the promotion of the synthesis and secretion of cellular chemokines (CXCL5, CXCL6) and enhancement of mesenchymal stromal cell migration through Ras signaling pathway [43]. In addition, naringin stimulates angiogenesis by regulating the VEGF/VEGFR-2 signaling pathway in rats, thereby promoting fracture healing [38]. However, the mechanism of some active ingredients of DR in the treatment of fractures has not yet been verified. Therefore, we integrated MAPK, PI3K/AKT, Ras, and VEGF signaling pathways to provide a reference for researchers to verify the mechanism of other DR active ingredients in the treatment of fractures.


## 5. Conclusion

We collected the gene and protein targets of fractures and active ingredients of DR and then used network pharmacology to reveal the correlation between drugs and diseases and the potential synergistic mechanism of different targets of DR in the treatment of fractures, which provides a reference for the development of new drugs.



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*Source: 7342635-2019-10-20.xml*