Network pharmacological analysis on the mechanism of Coix seed decoction for osteoarthritis of the knee

Abstract

Based on network pharmacology methods, we explored the mechanism of the classic Chinese medicine formula Coix seed decoction (CSD) in treating knee osteoarthritis (KOA). We searched each single drug in the CSD in the traditional Chinese medicine systematic pharmacology database in turn to obtain information on the active ingredients and target proteins of the CSD, and obtain the name of the genes corresponding to the target proteins through the UniProt database. We collected KOA-related genes from DisGeNET, GeneCards, comparative toxicogenomics database, and MalaCards database. The Venny online tool identified potential therapeutic targets by intersecting CSD and KOA target genes, while gene ontology and Kyoto encyclopedia of genes and genomes analysis was performed using the Oebiotech Cloud Platform. A protein-protein interaction network was established using the String database; a “CSD-active ingredient-target gene-KOA” network plot was constructed using Cytoscape 3.9.1 software and screened for key targets and hub targets. Finally, molecular docking was performed for hub genes with high Degree values. A total of 227 effective target genes for CSD and 8816 KOA-related target genes were obtained, as well as 191 cross-target genes for CSD and KOA. We screened 37 key gene targets and identified the top 10 hub target genes in descending order of Degree value using protein-protein interaction and Cytoscape 3.9.1 software (TNF, IL-6, MMP-9, IL-1β, AKT-1, VEGFα, STAT-3, PTGS-2, IL-4, TP53). Gene ontology analysis showed that the biological process of CSD treatment of KOA mainly involves cytokine-mediated signaling pathway, negative regulation of apoptotic process, cellular response to hypoxia, cellular response to cadmium ion, response to estradiol, and extrinsic apoptotic signaling pathway in absence of ligand. Kyoto encyclopedia of genes and genomes analysis revealed major signaling pathways including Cellular senescence, TNF signaling pathway, and PI3K-Akt signaling pathway. The molecular docking results show that the core components bind well to the core targets. In conclusion, CSD may exert therapeutic effects on KOA by inhibiting pathological processes such as inflammatory response, apoptosis, cellular senescence, and oxidative stress.

1. Introduction

Knee osteoarthritis (KOA) is a common degenerative joint disease characterized by histopathological changes such as degeneration of articular cartilage, subchondral bone remodeling, inflammation and fibrosis of the synovial membrane and infrapatellar fat pad, and degeneration of the meniscus,^[1–6] and belongs to the category of “Bi Syndrome” in traditional Chinese medicine (TCM). The main signs and symptoms in the early stages include knee pain, edema, and restricted joint movement. Joint pain and mobility difficulties are progressively worse with the development of cartilage loss and the development of synovial and subpatellar fat pad fibrosis,^[7,8] and in severe and advanced cases, even the whole loss of knee function may be seen. At this point in time, it is believed that a range of variables contribute to the occurrence of KOA, with age, obesity, heredity, and joint wear and tear all having been linked to the condition risk factors.^[9,10] As modern lifestyles change and the world population ages, the proportion of people exposed to high-risk factors is increasing globally each year, driving the rising global incidence of osteoarthritis of the knee.^[11] According to Global Burden of Disease data, the worldwide incidence of imaging-confirmed symptomatic KOA reached 3.8% globally as of 2010, and the prevalence of osteoarthritis has climbed by 9% over the course of 28 years, from 1990 to 2017, and is continuing to rise.^[12] Oral NSAIDs, joint cavity injections, and surgical procedures make up the majority of the existing KOA therapeutic options.^[13,14] However, pharmacological side effects, infections, and financial burden make it difficult to successfully focus KOA long-term therapy and prevention.^[15,16] Therefore, to lessen the health burden linked to KOA, the search for a more affordable and effective treatment approach has become essential. Based on the basic theories of Chinese medicine, TCM advocates the use of the corresponding treatment methods for different types of diseases through the method of diagnosis and treatment, and the use of oral Chinese medicine, external application, electro-acupuncture, massage and other characteristic treatment methods to achieve the purpose of treating diseases, and its efficacy and safety have been widely recognized in clinical practice.^[17] Currently, studies on the mechanisms related to KOA treatment in Chinese medicine mainly involve oxidative stress, inflammatory response, cell differentiation, proliferation, and apoptosis.^[17–21] For instance, Coixenolide can decrease inflammatory response by increasing peripheral serum Foxp3 + CD4 + CD25 + Treg ratio, which in turn controls immunological function in collagen-induced arthritic mice.^[18] Artemisinin, the active ingredient in Artemisia annua, was shown to have significant inhibitory effects on the expression of IL-1β, IL-6, and TNF-α in in vitro cellular assays, and could effectively inhibit IL-1β-induced inflammatory responses in rat osteoarthritis (OA) chondrocytes.^[22]

Coix seed decoction (CSD) is a classical formula for the treatment of “Bi Syndrome” in TCM recorded in the Chinese medical text “Lei Zheng Zhi Cai.” It is written in “Lei Zheng Zhi Cai” that CSD consists of Yi Yiren (Coix seed/Seed of Job tears), Dang Gui (Angelicae Sinensis Radix), Chuan Xiong (Ligusticum Chuanxiong Rhizoma), Sheng Jiang (Ginger), Gui Zhi (Cinnamomi ramulus), Qiang Huo (Notopterygium incisum), Du Huo (Doubleteeth Pubescent Angelica Root), Fang Feng (Saposhnikovia divaricata), Bai Zhu (Atractylodes macrocephala), Gan Cao (Glycyrrhiza uralensis), Chuan Wu (Aconitum carmichaelii), Ma Huang (Ephedra sinica). In this formula, Coix seed strengthens the spleen and permeates dampness;^[23] Chuan Wu,^[24–26] Gui Zhi,^[27,28] Ma Huang,^[29] Sheng Jiang^[30,31] warming the meridians and relieving pain. In addition, it has the function of nourishing and energizing the circulation when Chuanxiong is combined with Dang Gui.^[32,33] The combination of all the drugs in the formula can dispel wind and dampness, disperse cold and relieve pain, which has good effect on “Bi Syndrome.” However, although clinical observational studies on the treatment of KOA with CSD have been reported in China,^[34–37] there is still a lack of higher quality articles describing its clinical effectiveness and mechanism of action. With this in mind, we aimed to investigate potential targets, pathways, and biological processes (BP) of CSD for the treatment of KOA through a network pharmacological approach, and to establish the groundwork for further promotion in the clinic and research into its mechanism of action.

2. Materials and methods

2.1. Compound drug-active ingredient-target gene database establishment

Each individual herbal medicine in CSD was searched sequentially in the traditional Chinese medicine systematic pharmacology database (TCMSP, https://old.tcmsp-e.com/tcmsp.php). Based on the absorption, distribution, metabolism, and excretion criteria, we screened for active compounds with oral bioavailability ≥30 and drug-likeness ≥0.18, and collected their target information (see Supplemental Table 1, http://links.lww.com/MD/J363, Supplemental Content, which illustrates the active ingredient-target protein correspondence of the GSD compound in the database),^[38,39] and the active ingredients with no corresponding target proteins in the database were excluded. Using the UniProt database (https://www.uniprot.org/), we searched the obtained target proteins sequentially to obtain the corresponding gene names. After replacing the target protein names with the corresponding gene names, we obtained the CSD compound drug-active ingredient-target gene database (see Supplemental Table 2, http://links.lww.com/MD/J364, Supplemental Content, which illustrates the correspondence of GSD compounded drugs, active ingredients and target genes).

2.2. Disease related target gene database establishment

The keywords “KOA” were searched in GeneCards (https://www.genecards.org/), MalaCards (https://www.malacards.org/). DisGeNetdatabase (https://www.disgenet.org/), CTD (http://ctdbase.org/) databases to obtain KOA-related target gene information for each disease database (see Supplemental Table 3, http://links.lww.com/MD/J365, Supplemental Content, which illustrates the search results of KOA-related target genes in various databases). The search results of each database were aggregated and de-duplicated to create a database of KOA disease-related target genes.

2.3. CSD-drug-active ingredient-potential therapeutic target-disease network construction

The intersection of the CSD target gene set and the KOA target gene set was taken by the Venny online tool (https://bioinfogp.cnb.csic.es/tools/venny/), and the obtained intersection data were the potential therapeutic targets of CSD for KOA. The data was organized to obtain the corresponding relationship data of “CSD-Drug-Active Ingredient-Potential Therapeutic Gene-KOA,” and the data was imported into Cytoscape software (version 3.9.1) in “.xlsx” file format. Finally, the network interaction plot of “YYRD-Drug-Active Ingredient-Potential Therapeutic Gene-KOA” was constructed.

2.4. Protein interaction network graph construction

After importing the set of potential therapeutic genes into the String database (http://string-db.org/) and completing the setup (species selection “Homo sapiens,” confidence value >0.4), protein-protein interaction network analysis was performed. After downloading the potential therapeutic gene protein interaction network data from the String database into Cytoscape software (version 3.9.1) and using the function of CytoHubba plug-in, the data were sorted by MCC, DMNC, maximum neighborhood component, degree, edge percolated component, bottle neck, eceentricity, closeness, radiality, betweenness, stress, clustering coefficient were sorted in descending order and the top ten nodes were filtered out, and then combined and de-weighted to key genes were obtained (see Supplemental Table 4, http://links.lww.com/MD/J366, Supplemental Content, which illustrates the information about each of the above screening conditions for the key genes). The key genes were imported into the String database again according to the above steps to obtain the key gene protein interaction network map. The key genes were arranged in descending order by Degree value using Cytoscape software (version 3.9.1), and the top 10 nodes were the hub genes.

2.5. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis

GO and KEGG enrichment analysis of potential therapeutic gene sets for CSD treatment of KOA using the Cloud Platform of Oebiotech (https://cloud.oebiotech.cn/task/). In the enrichment analysis interface of the Cloud Platform, the species is limited to “H. sapiens,” and the potential therapeutic gene set ID is entered in the common parameters and submitted. After the analysis, we obtained the GO and KEGG database pathway analysis charts of potential therapeutic genes, respectively (see Supplemental Tables 5, http://links.lww.com/MD/J367 and 6, http://links.lww.com/MD/J368 Supplemental Content, which illustrate GO functional class and KEGG enrichment analysis data, respectively).

2.6. Molecular docking validation of predicted targets

We obtained the 3D structure of the proposed docking target in mol2 format from the Pubchem database (https://pubchem.ncbi.nlm.nih.gov/), opened the small ligand molecule with AutodockTools 1.5.6, hydrogenated, charged, detected the ligand root, searched and defined the rotatable bond, and then saved as a pdbqt file. From the RCSB Protein Data Bank (www.rcsb.org), we downloaded the target protein primary 3D structure as a docking protein. Every hydrogen atom was added to AutodockTools 1.5.6 for opening, Gasteiger charge estimation, binding non-polar hydrogen, receptor definition, and saving as pdbqt file. The level of detail parameter was set to 15 and the Vina molecule docking coordinates and box size, while using the default values for the other inputs. The semi-flexible docking procedure was carried out using Autodockvina 1.1.2, and the final docking conformation was chosen based on its affinity.

3. Results

3.1. CSD active ingredient and target information

By searching the TCMSP database, we obtained 9 active ingredients of Coix seed, 2 active ingredients of Dang Gui, 7 active ingredients of Chuan Xiong, 5 active ingredients of Sheng Jiang, 7 active ingredients of Gui Zhi, 15 active ingredients of Qiang Huo, 9 active ingredients of Du Huo, 18 active ingredients of Fang Feng, 7 active ingredients of Bai Zhu, 92 active ingredients of Gan Cao, 3 active ingredients of Chuan Wu, and 23 active ingredients of Ma Huang, of which Fifteen active ingredients were present in multiple drugs at the same time (Table 1). The active ingredients of each drug were combined and de-weighted to obtain 167 active ingredients. The TCMSP database was used again to retrieve 167 active ingredients corresponding to the targets, and after merging and de-duplication and target protein name correction, 227 active targets were finally included. Among the included targets, Coix seed contains 26 species, Dang Gui contains 40 species, Chuanxiong contains 24 species, Sheng Jiang contains 41 species, Gui Zhi contains 32 species, Qiang Huo contains 35 species, Du Huo contains 33 species, Fang Feng contains 66 species, Bai Zhu contains 17 species, Gan Cao contains 206 species, Chuan Wu contains 4 species, and Ma Huang contains 201 species.

Table 1.

Basic information of repeat active ingredient.

Code	Repeat active ingredient	Related drugs
A	Quercetin	Gan Cao, Ma Huang
B	Beta-sitosterol	Dang Gui, Sheng Jiang, Gui Zhi, Qiang Huo, Du Huo, Fang Feng, Ma Huang
C	Sitosterol	Yi Yiren, Chuanxiong, Gui Zhi, Qiang Huo, Fang Feng, Gan Cao
D	Kaempferol	Gan Cao, Ma Huang
E	STIGMASTEROL	Yi Yiren, Dang Gui, Sheng Jiang, Ma Huang
F	(+)-Catechin	Gui Zhi, Ma Huang
G	Mandenol	Yi Yiren, Chuanxiong, Fang Feng, Ma Huang
H	Poriferast-5-en-3beta-ol	Sheng Jiang, Ma Huang
I	Ammidin	Qiang Huo, Du Huo, Fang Feng
J	Isoimperatorin	Qiang Huo, Du Huo, Fang Feng
K	Phellopterin	Qiang Huo, Fang Feng
L	Diosmetin	Qiang Huo, Ma Huang
M	Naringenin	Gan Cao, Ma Huang
N	Taxifolin	Gui Zhi, Ma Huang
O	Nodakenin	Qiang Huo, Du Huo

3.2. KOA disease target data

Searching the KOA action targets by disease-related databases, we retrieved 80 in GeneCards, 68 in MalaCards, 368 in DisGeNet database, and 7953 in CTD. The search results of each database were combined and de-duplicated to obtain 8116 KOA disease action targets (Fig. 1A).

Figure 1.

(A) This figure shows the Veen plots of KOA-related target proteins obtained based on MalaCards, GeneCards, DisGeNetdatabase, CTD databases; (B) This figure shows the Veen plots of drug targets and KOA-related targets based on Coix seed decoction (CSD) complexes. CTD = comparative toxicogenomics database, KOA = knee osteoarthritis.

3.3. CSD-drug-active ingredient-potential therapeutic target-disease network construction

A total of 191 intersecting genes for CSD treatment of KOA were obtained by analysis of the Vine online tool (Fig. 1B). Network tables were constructed based on CSD drug, active ingredient, potential therapeutic target (intersecting gene), and disease information, and then the data attributes are categorized and named in Type tables. The Network file and Type file were imported into Cytoscope software to construct the “CSD-Drug-Active Ingredient-Potential Therapeutic Target-Disease” network diagram (Fig. 2).

Figure 2.

Coix seed decoction (CSD) network diagram of “compound-drug-active-ingredient-potential-target-disease” for KOA. The orange color represents the drug in the compound; the blue hexagon represents the active ingredient; the green hexagon represents the duplicate active ingredient co-existing in multiple drugs; the “V” symbol represents the potential therapeutic target of CSD for KOA, with the dark purple part representing the core target. KOA = knee osteoarthritis.

3.4. Results of gene screening and enrichment analysis

The 191 potential therapeutic targets were analyzed by string online data analysis tool to construct a protein interaction network map (Fig. 3). Using the function of CytoHubba, a plug-in for Cytoscape software, the top ten nodes were filtered by different parameters in descending order, respectively. The first ten nodes of each data were combined and de-weighted to obtain 37 key genes. The key genes were again imported into string online data analysis tool to obtain the key gene protein interaction network map (Fig. 4A). The key genes were imported into Cytoscape software for Degree value descending arrangement, and the top 10 nodes were screened as the hub genes (Table 2), namely TNF, IL-6, MMP-9, IL-1β, AKT-1, VEGFα, STAT-3, PTGS-2, IL-4, TP53 (Fig. 4B). We performed GO and KEGG enrichment analysis on the 37 key targets screened, expecting to further elucidate the pathways of action of CSD for KOA treatment in terms of pathways of action and BP. GO analysis showed 2834 analyzed entries, including 2103 for BP, 444 for molecular function (MF), and 288 for cellular component (CC). The top 10 entries of BP, CC, and MF were filtered by P value calculation ranking (Table 3). The results of the BP screen involve exogenous apoptotic signaling pathway in the absence of ligand (GO:0097192), cellular response to cadmium ion (GO:0071276), response to estradiol (GO:0032355), cellular response to hypoxia (GO:0071456), cytokine-mediated signaling pathway (GO:0019221), gene expression positive regulation of (GO:0010628), negative regulation of apoptotic process (GO:0043066), response to drugs (GO:0042493), positive regulation of transcription by RNA polymerase II (GO:0045944), positive regulation of transcription, DNA-induced (GO:0045893). MF screening results include enzyme binding (GO:0019899), nuclear receptor activity (GO:0004879), homologous protein binding (GO:0042802), protein binding (GO:0005515), protein kinase binding (GO:0019901), DNA binding transcription factor activity (GO:0003700), protein homolog dimerization activity (GO:0042803), transcription factor binding (GO:0008134), protein-containing complex binding (GO:0044877), protease binding (GO:0002020); CC mainly involves extracellular space (GO:0005615), membrane raft (GO:0045121), extracellular region (GO:0005576), cytosol (GO:0005829), chromatin (GO:0000785), cyclin-dependent protein kinase holoenzyme complex (GO:0000307), nucleoplasm (GO:0005654), protein-containing complex (GO:0032991), caveola (GO:0005901), cyptoplasm (GO:0005737) (Fig. 5). KEGG data analysis yielded a total of 267 related pathways, and the top 20 most highly associated pathways were obtained in descending order of enrichment score, namely cellular senescence, TNF signaling pathway, PI3K- Akt signaling pathway, IL-17 signaling pathway, bladder cancer, AGE-RAGE signaling pathway in diabetic complications, pancreatic cancer, prostate cancer, non-small cell lung cancer, small cell lung cancer, endocrine resistance, fluid shear stress and atherosclerosis, hepatitis B, toxoplasmosis, hepatitis C, MicroRNAs in cancer, Kaposi sarcoma-associated herpesvirus infection, human cytomegalovirus infection, proteoglycans in cancer, and pathways in cancer (Fig. 6, Table 4).

Figure 3.

Protein interaction network map of 191 potential therapeutic genes.

Figure 4.

(A) The figure shows the protein interaction network map of 37 key targets; (B) The figure shows the protein interaction network map of the top 10 core targets in terms of Degree value.

Table 2.

The degree value sequence of some key targets of Coix seed decoction (CSD) against knee osteoarthritis (KOA).

UniProt ID	Gene symbol	Protein names	Degree
P01375	TNF	Tumor necrosis factor	32
P05231	IL6	Interleukin-6	32
P14780	MMP9	Matrix metalloproteinase-9	31
P01584	IL1B	Interleukin-1 beta	31
P31749	AKT1	RAC-alpha serine/threonine-protein kinase	29
P15692	VEGFA	Vascular endothelial growth factor A	28
P40763	STAT3	Signal transducer and activator of transcription 3	28
P35354	PTGS2	Prostaglandin G/H synthase 2	27
P05112	IL4	Interleukin-4	27
P04637	TP53	Cellular tumor antigen p53	26
P01579	IFNG	Interferon gamma	26
P03956	MMP1	Interstitial collagenase	25
P42574	CASP3	Caspase-3	25
P01100	FOS	Protein c-Fos	25
P00533	EGFR	Epidermal growth factor receptor	25
P01106	MYC	Myc proto-oncogene protein	24
P01583	IL1A	Interleukin-1 alpha	24
P10451	SPP1	Osteopontin	23
Q14790	CASP8	Caspase-8	23
P19438	TNFRSF1A	Tumor necrosis factor receptor superfamily member 1A	23
P03372	ESR1	Estrogen receptor	22
P16581	SELE	E-selectin	22
P24385	CCND1	G1/S-specific cyclin-D1	22
P02778	CXCL10	C-X-C motif chemokine 10	21
P04040	CAT	Catalase	20
P19875	CXCL2	C-X-C motif chemokine 2	18
P10914	IRF1	Interferon regulatory factor 1	18
O14625	CXCL11	C-X-C motif chemokine 11	14
P06401	PGR	Progesterone receptor	14
P07204	THBD	Thrombomodulin	8
P02461	COL3A1	Collagen alpha-1 (III) chain	7
P78380	OLR1	Oxidized low-density lipoprotein receptor 1	6
P03973	SLPI	Antileukoproteinase	5
Q14209	E2F2	Transcription factor E2F2	5

Table 3.

The top 10 gene ontology (GO) enrichment items.

ID	Term	Category
GO:0097192	Extrinsic apoptotic signaling pathway in absence of ligand	BP
GO:0032355	Response to estradiol	BP
GO:0071276	Cellular response to cadmium ion	BP
GO:0071456	Cellular response to hypoxia	BP
GO:0045893	Positive regulation of transcription, DNA-templated	BP
GO:0045944	Positive regulation of transcription by RNA polymerase II	BP
GO:0043066	Negative regulation of apoptotic process	BP
GO:0042493	response to drug	BP
GO:0010628	Positive regulation of gene expression	BP
GO:0019221	Cytokine-mediated signaling pathway	BP
GO:0005737	Cytoplasm	CC
GO:0005901	Caveola	CC
GO:0032991	Protein-containing complex	CC
GO:0005654	Nucleoplasm	CC
GO:0000307	Cyclin-dependent protein kinase holoenzyme complex	CC
GO:0000785	Chromatin	CC
GO:0005829	Cytosol	CC
GO:0005576	Extracellular region	CC
GO:0045121	Membrane raft	CC
GO:0005615	Extracellular space	CC
GO:0002020	Protease binding	MF
GO:0044877	Protein-containing complex binding	MF
GO:0008134	Transcription factor binding	MF
GO:0042803	Protein homodimerization activity	MF
GO:0003700	DNA-binding transcription factor activity	MF
GO:0019901	Protein kinase binding	MF
GO:0005515	Protein binding	MF
GO:0042802	Identical protein binding	MF
GO:0004879	Nuclear receptor activity	MF
GO:0019899	Enzyme binding	MF

BP = biological process, CC = cellular component, MF = molecular function.

Figure 5.

The gene ontology (GO) pathway enrichment analysis.

Figure 6.

The Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis.

Table 4.

The top 20 Kyoto encyclopedia of genes and genomes (KEGG) enrichment items.

ID	Term	P value
hsa05200	Pathways in cancer	1.23E-38
hsa04933	AGE-RAGE signaling pathway in diabetic complications	1.10E-31
hsa05215	Prostate cancer	5.95E-28
hsa05161	Hepatitis B	2.46E-26
hsa05219	Bladder cancer	1.97E-24
hsa05160	Hepatitis C	3.08E-23
hsa05212	Pancreatic cancer	5.16E-23
hsa05418	Fluid shear stress and atherosclerosis	6.95E-23
hsa05167	Kaposi sarcoma-associated herpesvirus infection	2.35E-22
hsa05163	Human cytomegalovirus infection	4.54E-22
hsa05223	Non-small cell lung cancer	6.64E-21
hsa04657	IL-17 signaling pathway	1.91E-20
hsa04668	TNF signaling pathway	1.35E-19
hsa05206	MicroRNAs in cancer	1.42E-19
hsa05222	Small cell lung cancer	1.92E-19
hsa04151	PI3K-Akt signaling pathway	1.98E-19
hsa01522	Endocrine resistance	7.46E-19
hsa05145	Toxoplasmosis	1.98E-18
hsa04218	Cellular senescence	7.40E-18
hsa05205	Proteoglycans in cancer	1.20E-17

3.5. Molecular docking results

From the CSD compound drug-active ingredient-target gene database, we screened 4 active ingredients (quercetin, kaempferol, luteolin, and wogonin) as key active compounds for molecular docking with the first 4 hub genes (TNF, IL-6, MMP-9, and IL-1). These key active compounds not only act on the proteins expressed by the 4 hub genes mentioned above, but also have as many proteins expressed by other genes as possible as targets. Small molecule ligands can spontaneously bind to protein receptors when the binding energy is <0 kJ mol. If the binding energy is <−5.0 kJ mol or lower, it indicates a better binding ability of both. 16 docking results were generated by the docking simulation (Table 5). They both have binding energies <−5 kJ mol, which means that they both bind well. This chemical docking result raises the prospect that substances like quercetin may be essential in the way CSD treats KOA. Finally, Pymol software was employed to visualize the complexes of the 4 groups of docked proteins and chemicals (Fig. 7).

Table 5.

The binding energy of Molecular docking (kJ mol).

Hub gens Active chemicals	TNF	IL6	MMP-9	IL-1β
Quercetin	−6.3	−6.3	−9.8	−6.2
Kaempferol	−6.0	−6.1	−9.4	−6.1
Luteolin	−6.4	−6.3	−10.1	−6.5
Wogonin	−6.0	−5.8	−9.3	−6.1

Figure 7.

Molecular docking diagram and local enlargement. (A) TNF-luteolin; (B) MMP9-luteolin; (C) IL1β-quercetin; (D) IL6-quercetin.

4. Discussion

KOA is a common clinical condition that is now a major health threat affecting the global middle-aged and elderly population, driven by an aging population and changes in modern lifestyles.^[40] However, due to its complex etiology and wide range of lesion sites, the specific pathogenesis of KOA is not yet fully understood.^[41] Therefore, it is important to explore the pathogenesis of KOA and seek convenient, effective and economical treatment methods to alleviate the health crisis caused by KOA. Due to its convenience, effectiveness, affordability, and low side effects, TCM is emerging as a new approach for treating KOA. However, the fact that TCM contains a sizable number of active ingredients and is associated with multiple pathways of combined action has made it challenging to thoroughly research the therapeutic mechanisms of TCM compounding. In contrast, network pharmacology has shed light on the synergistic effects and potential mechanisms of multi-compound and multi-target drugs by examining the various intricate interaction networks in Chinese medicine, which are now frequently used in the investigation of the workings of Chinese medicine monomeric drugs and compounding.^[42,43] Therefore, this study was conducted to capture the relevant target information of CSD for the treatment of KOA by searching relevant literature and databases, aiming to analyze the BPs and related pathways involved by means of network pharmacology, to analyze the mechanism of CSD for the treatment of KOA at the molecular level, and to reveal its multi-component and multi-target mechanism of action.

We captured the active ingredients of CSD drugs and KOA disease-related targets respectively, and obtained 191 potential therapeutic targets by taking the intersection, from which 37 key genes with high influence were screened and arranged in descending order by Degree value, and the top ten core targets were: TNF, IL-6, MMP-9, IL-1β, AKT-1, VEGFα, STAT-3, PTGS-2, IL-4, TP53. Meanwhile, we performed GO and KEGG enrichment analysis with 37 key genes. GO analysis showed that the BPs associated with CSD treatment of KOA mainly involved the exogenous apoptotic signaling pathway of ligand deletion, cellular response to cadmium ion, response to estradiol, cellular response to hypoxia, negative regulation of apoptotic process, and cytokine-mediated signaling pathway. The results of KEGG enrichment analysis showed that cellular senescence, TNF signaling pathway, and PI3K-Akt signaling pathway were the main relevant enrichment pathways. The molecular docking results between 4 important active ingredients and the related proteins of the first 4 hub genes showed that all 16 obtained results were <−5.0 kJ/mol, indicating that these active ingredients can bind well with the hub genes and may be an important potent substance basis for the therapeutic effects of CSD. For instance,^[44] Fei et al found that luteolin could effectively reduce the expression of MMP-9 and TNF-α in mouse chondrocytes induced by LI-1β, and further demonstrated its inhibitory effects on the degradation of type II collagen through in vivo experiments. Meanwhile, Wu et al^[45] discovered that the inhibitory effect of luteolin on MMP-9 expression may be associated with the Akt-mTOR signaling pathway. This finding is intriguing to us, as it is consistent with our network pharmacology analysis despite not having been confirmed in studies related to OA. Furthermore, studies have demonstrated varying degrees of inhibition in extracellular matrix degradation and inflammatory responses during OA progression for quercetin, wogonin, and kaempferol.^[46–50]

IL-6 itself is a cytokine that activates the systemic immune system and enhances the inflammatory response, and in KOA acts on articular cartilage to inhibit type II collagen production and promote the expression of MMPs group.^[51] In KOA-related studies, IL-6 has often been noted as an indicator of inflammation because of its positive correlation between synovial fluid concentration and the severity of KOA imaging.^[52,53] And the increase in IL-6 concentration in synovial fluid is thought to be closely related to TNF-α and IL-1β. It was shown that TNF-α and IL-1β induced IL-6 production by chondrocytes, synovial fibroblasts, macrophages, osteoblasts, and adipocytes, and also stimulated the upregulation and expression of chemokines such as IL-8, MCP-1, Rantes, and some inflammatory factors in joints, thus participating in regulating the inflammatory pathological process of KOA.^[54] In addition, these 2 cytokines can lead to the production of reactive oxygen species and the down-regulation of reactive oxygen antioxidant enzymes, thereby promoting oxidative stress and apoptosis, thereby accelerating cartilage destruction.^[55] Moreover, cyclooxygenase 2 (COX-2) is an important element in the inflammatory response. On the one hand, COX-2 is compiled by the gene PTGS-2, which is difficult to detect in normal tissues and can be induced to be expressed by inflammatory factors (e.g., IL-1β, TNFα) and is often used as a test for inflammatory responses in OA.^[44,56–58] On the other hand, COX-2 is one of the important catalysts in the conversion of arachidonic acid to prostaglandin E2 (PGE2), and its metabolite PGE2 can increase vascular permeability and exacerbate inflammatory tissue edema, therefore it is also an important target of current anti-inflammatory and analgesic drugs for OA (e.g., non-steroidal anti-inflammatory drugs, COX-2 specific inhibitors).^[58,59]

The combined action of multiple factors leads to the overexpression and aggregation of pro-inflammatory factors represented by these inflammatory factors and mediators in KOA, inducing adverse events such as chondrocyte apoptosis and extracellular matrix degradation, and accelerating the progression of KOA. In response to the threat posed by these pro-inflammatory factors, the body will also initiate corresponding anti-inflammatory mechanisms for intervention. IL-4 is an important representative of anti-inflammatory factors involved in the inflammatory response of OA. It can not only effectively inhibit the secretion of the above inflammatory factors such as TNFα, IL-6, and inflammatory mediators COX-2, PGE2, but also reduce the secretion of MMPs in articular cartilage and the degradation of proteoglycans, inhibit the apoptosis of chondrocytes and synovial fibroblasts, and delay the progression of KOA.^[54] On the other hand, the overexpression of inflammatory factors can also activate corresponding pathways in the human body to inhibit inflammatory responses. For example,^[60–62] IL-6 can activate JAK-STAT signaling pathway, which is one of the few multi-effect cascades. IL-6 first binds to the receptor on the cell membrane to activate the receptor, and the activated receptor induces JAK phosphorylation to further phosphorylate STAT-3, and the activated STAT-3 dimerizes into the nucleus to regulate the expression of anti-apoptotic genes such as Bcl-2, MCL1, and cell cycle-related genes such as c-Myc and p21.

As mentioned above, TNF-α can mediate inflammation, immunity, apoptosis, oxidative stress and other processes, and is one of the important signaling molecules for KOA, and one of the important targets we screened for the treatment of KOA by CSD. And through enrichment analysis, we speculate that CSD may mediate the activation of its downstream NF-κB signaling pathway via the TNF signaling pathway to promote cell proliferation, inhibit apoptosis, and reduce the occurrence of inflammatory reactions in order to treat KOA. There are 2 types of receptors in the TNF signaling pathway, TNFR1 and TNFR2, the former has a death structure domain in the inner cell membrane and plays a dominant role in the TNF signaling pathway.^[63] The TNF signaling pathway activates the downstream pathway NF-κ B signaling pathway mainly through the TNFR1 signaling complex (TNFR1-SC) composed of TRAF-2/5 combined with the N-terminal non-dead structural domain part of TRADD, which activates the IκB kinase complex to promote the detachment of IκB from the NF-κB trimer, thus allowing the NF-κB dimer to enter the nucleus and bind to DNA-specific sequences, inducing the expression of pro-inflammatory factor-related genes such as TNF-α, IL-6, and cell proliferation-related genes such as VEGF, MMP-9.^[64] VEGF-α mainly acts on endothelial cells, promoting angiogenesis by activating receptors on them. Multiple studies have shown that angiogenesis can induce osteophyte formation, deep bone calcification in articular cartilage, and is one of the important mechanisms for the pathogenesis and progression of OA.^[65,66] In addition, studies have shown that VEGF-α can also promote capillary permeability and promote inflammatory response in OA.^[67] MMP-9 belongs to the family of matrix metalloproteinases, which are induced and activated in inflammatory environments. They promote leukocyte infiltration by cutting and degrading extracellular matrix, which is beneficial for clearing infections. However, in the pathological process of OA, the degradation of extracellular matrix is an important cause of cartilage degeneration.

Unlike the pro-inflammatory effect mediated by TNFR-1, activation of TNFR-2 pathway promotes cell proliferation and has anti-inflammatory effects.^[68,69] TNFR-2 can still activate the downstream NF-κB pathway despite the absence of the death structural domain, which is closely linked to its involvement in the regulation of PI3K-Akt-related pathways. And by searching the KEGG database and reviewing the literature, we also found that TNFR-2 can inactivate the TSC1/2 complex by promoting Akt phosphorylation of TSC2, which in turn activates mTORC1 to promote cell growth, protein synthesis and other processes.^[69–71]

In addition, among the 3 subtypes of AKT that have been discovered so far, AKT1, AKT2, and AKT3. AKT1 is widely distributed and mainly expressed in tissues, with an anti-apoptotic effect, which may be the result of the inhibition of p53 after activation of the PI3K-Akt signaling pathway.^[72] P53, a protein transcription factor encoded by the TP53 gene, has a role in inducing cell cycle termination and apoptosis, and is one of the major regulators of cell growth and apoptosis.^[73] In the PI3K-Akt-p53 signaling pathway, the activation of the PI3K-Akt pathway leads to the phosphorylation of Mdm2 oncoprotein at serine 166 and serine 186 sites. Consequently, Mdm2 trans-locates from the cytoplasm to the nucleus where it inhibits the expression and transcription of p53. This ultimately results in a negative regulation of apoptosis and cell cycle termination.^[74]

While we were able to obtain results on the therapeutic mechanism of CSD for KOA, our network pharmacology analysis was limited by the data available in our selected database. Specifically, the analysis did not take into account factors such as drug concentration, and there may be drug targets and disease-associated genes that have not yet been identified or entered into the database. As such, the results we obtained should be interpreted with caution as they may only reflect a portion of the therapeutic mechanism of CSD. Moreover, the interactions between various cytokines and signaling pathways in the body form a complex network structure, and we have only been able to analyze and reason about a small part of this complex network. Nonetheless, this also provides a preliminary direction for subsequent experimental validation of the relevant pathways, which is crucial for exploring the mechanism underlying CSD efficacy in treating KOA.

5. Conclusion

In summary, we believe that CSD reduces apoptosis, inflammatory cytokine secretion, and neoangiogenesis in the development of KOA by inhibiting the expression of caspase-8 mediated by the TNFR1 pathway in the TNF signaling pathway, as well as the activation of downstream NF-κB signaling pathway. On the other hand, CSD enhances the expression of anti-inflammatory cytokines such as IL-4, which in turn reduces the secretion and aggregation of inflammatory factors such as TNF-α, IL-6, COX-2, PGE2, and their related oxidative stress reactions. Additionally, CSD activates TNFR2-mediated cell proliferation and PI3K-Akt pathway-related anti-apoptotic and anti-inflammatory effects, thereby achieving therapeutic effects for KOA.

Author contributions

Data curation: Rui Chen.

Formal analysis: Chao Song.

Methodology: Xiaoqiang Wang, Wei Xiang.

Resources: Sanjun Huang, Qifan Su, Guanghui Deng.

Software: Jiaqi Wu.

Writing – original draft: Junjie Qiu.

Writing – review & editing: Xiaojun Chen.