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ORIGINAL ARTICLE Table of Contents  
Ahead of print publication
Exploring the mechanism of Tripterygium wilfordii against cancer using network pharmacology and molecular docking


1 Obstetrics and Gynecology, Shenzhen Longhua District Central Hospital, Shenzhen 518110, Guangdong, China
2 Medical Laboratory, Shenzhen Longhua District Central Hospital, Shenzhen 518110, Guangdong, China
3 Research Department, Guangzhou Darui Biotechnology Co., Ltd., Guangzhou 510670, Guangdong, China
4 Department of Pharmacy, Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, Guangdong, China
5 Department of Clinical Laboratory Medicine, Guangdong Second Provincial Central Hospital, Guangzhou 510317, Guangdong, China
6 College of Pharmacy, Jinan University, Guangzhou 510632, Guangdong, China

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Date of Submission29-Oct-2020
Date of Acceptance08-Jul-2021
 

  Abstract 


Background: The root of Tripterygium wilfordii (Tripterygii radix), a natural powerful traditional Chinese medicine (TCM) for various diseases treatment, has been used for centuries in the Asian countries as anti-rheumatoid arthritis (RA) agent, antioxidant agent, and anti-inflammatory agent. Its combination with other herbs in treating RA has been explored. The anti-RA effect of T. wilfordii for cancer treatment has been supported by some evidence. Aims and Objectives: To investigate the anticancer mechanism of T. wilfordii, bioinformatics databases were used to identify its active ingredients. Materials and Methods: Target proteins associated with cancer were determined using a network pharmacology analysis platform, and 25 key active compounds and 55 key targets of T. wilfordii were identified in our study. A common potential mechanism of T. wilfordii involvement in cancer was disclosed by in-depth network analysis of diseases, functions, and pathways. Finally, the analysis results of the TCM-disease target protein interaction network revealed 5 potential targets; subsequently, a total of 30 targets (these 5 targets, as well as 25 previously identified compounds) were subjected to molecular docking. Results: Our results showed that the therapeutic effect of T. wilfordii in cancer is characterized by multiple components, targets, and pathways. The regulation of signaling pathways such as Kaposi sarcoma-associated herpes virus infection, colorectal cancer, small-cell lung cancer, and prostate cancer may be the important pharmacodynamic basis of anticancer therapy. Conclusion: Triptonoditerpenic acid inhibited proliferation and induced apoptosis in SW480 cells. The mechanism may be related to the downregulation of Bcl-2 expression, upregulation of Bax mRNA expression, and expression inhibition of PTGS2.

Keywords: Tripterygium wilfordii; cancer; network pharmacology; molecular docking


How to cite this URL:
Xiao SX, Li SJ, Fang WX, Chen J, Li HJ, Situ YL. Exploring the mechanism of Tripterygium wilfordii against cancer using network pharmacology and molecular docking. World J Tradit Chin Med [Epub ahead of print] [cited 2022 Aug 8]. Available from: https://www.wjtcm.net/preprintarticle.asp?id=344544





  Introduction Top


Cancer is one of the leading causes of death and a major public health problem worldwide. According to the global cancer epidemic statistics, there were 18.1 million new cancer cases and 9.7 million cancer deaths worldwide in 2018.[1] The World Health Organization estimates that the incidence and death rates of cancer are on the rise worldwide.[2] There is no specific medicine available for the treatment of cancer. However, there are some disadvantages of using Western medicine in clinical practice, such as drug toxicity and drug resistance, which limit its clinical application. Therefore, it is necessary to identify effective and safe anticancer drugs.

Colorectal cancer (CRC) is one of the primary causes of morbidity and mortality worldwide. Since the early symptoms of CRC patients are not obvious, or only accompanied by mild diarrhea and other routine symptoms, most of them have been in the advanced stage and have missed the best opportunity for surgical treatment. Furthermore, with radiation and conventional chemotherapy, the 5-year survival rate for locally advanced CRC is 49%–80%, and for metastatic CRC is ~10% (www.cancer.org/). Similarly, there is a need to find effective and safe anti- CRC drugs.

Tripterygium wilfordii is an annual liana of the Tripterygium genus, Celastraceae family, bitter in flavor, cold in nature, extremely poisonous, with efficacy of dispelling wind, eliminating dampness, and relieving swelling and pain in the Chinese medicine. Notably, it has a unique curative effect in the treatment of autoimmune refractory diseases.[3],[4],[5] In recent years, an increasing amount of research evidence.[6],[7] indicate that T. wilfordii has a good therapeutic effect on cancers including stomach cancer, skin cancer, nasopharyngeal cancer, and breast cancer. T. wilfordii has strong pharmacological activity and remarkable curative effects, but its anticancer mechanism has not been fully elucidated. Traditional Chinese medicine (TCM) has multi-component and multi-target comprehensive regulatory effects in the treatment of diseases. However, it is difficult to reflect the characteristics of TCM using the monomer research method of Western medicine. Network pharmacology shifts the study of TCM pharmacology to the mode of multi-gene-multi-target-complex disease, and molecular docking can be used to verify the effect of the effective components of TCM on important targets. Therefore, this study adopted network pharmacology and molecular docking to explore the anticancer mechanism of T. wilfordii and carried out pharmacodynamic and mechanistic verification through cell experiments.


  Materials and Methods Top


Acquisition of active components of Tripterygium wilfordii

The TCM Systems Pharmacology Database and Analysis Platform (TCMSP, http://lsp.nwu.edu.cn/tcmsp.php) were searched to obtain the chemical components of T. wilfordii and to conduct a preliminary screening of its active components. The selection criteria[8] as follows, drug likeness (DL) >0.18, oral bioavailability (OB) >30%, to construct the chemical composition database of T. wilfordii.

Acquisition of potential targets of Tripterygium wilfordii

All potential targets of T. wilfordii were obtained by searching the TCMSP. Perl software and UniProt Knowledgebase were used to add gene names to the selected targets.

Acquisition of cancer genes

Use OMIM database (http://www.ncbi.nlm.nih.gov/omim) and GeneCards database (https://www.genecards.org/) by typing keywords “cancer” for genes involved in cancer. The data obtained from the two databases were combined to delete duplicate and false-positive genes. To obtain the common genes, R software (Version 3.5.3) was used to match and map the targets of T. wilfordii and cancer, and a Venn diagram was drawn.

Construction of traditional Chinese medicine - component - disease - gene network

Cytoscape software (Version 3.6.1, http://www.cytoscape.org) was used to construct the TCM-Component-Disease-Gene regulation network. The nodes in the network represent the drug, active ingredients, and key target, respectively. Edges are used to connect the drugs with active components, active components, and key targets. The components of T. wilfordii shown in this network are related to cancer genes as the key components in anti-cancer therapy. The whole network showed the relationship between drugs, active ingredients, and targets, and the mechanism of anticancer action of T. wilfordii was explored by constructing a regulatory network.

Construction of traditional Chinese medicine - disease target protein interaction network and screening of core targets

The TCM - disease genes were input into the software using STRING online software (Version 11.0, http://string-db.org/cgi/input.pl), with the selection criteria of species being Homo sapiens and a minimum interaction score of 0.4. The resulting files were saved as TSV and were added into R software (Version 3.5.3) for the calculation to obtain the bar diagram of the core target of the protein interaction network.

The enrichment analysis of gene ontology function and Kyoto encyclopedia of genes and genomes pathway

ClueGO plug-in of Cytoscape software (Version 3.6.1, http://www.cytoscape.org) was used for the cluster analysis, with Homo sapiens as the selection criteria for species. The Kappa Score was 0.4, and only the gene ontology (GO) function (P < 0.05) was displayed to obtain the result of GO function enrichment analysis. Enrichment analysis of Kyoto encyclopedia of genes and genomes (KEGG) pathway was performed using R software (Version 3.5.3) to calculate TCM - disease genes. The statistical significance was set at P < 0.05.

Molecular docking

The top five target proteins in the number of TCM - disease target protein interaction network were selected for molecular docking with the active components of T. wilfordii. The experimental method was as follows: The protein crystal structure was downloaded from Protein Database (https://www.rcsb.org/), and the protein with ligands was selected to ensure the docking accuracy. Then, the 3D structure of the active ingredient of T. wilfordii was downloaded from Pubchem (https://pubchem.ncbi.nlm.nih.gov/) and Vina software (Version 1.1.2) was used for the molecular docking analysis. Finally, the conformation with the lowest vina score was selected and plotted using PyMOL (Version 2.4) for the analysis.

Effect of triptonoditerpenic acid on the proliferation inhibition rate of human colorectal cancer cells (SW480 cells)

SW480 cells at the logarithmic growth stage were digested with a 0.25% trypsin solution. RPMI-1640 culture medium containing 10% fetal bovine serum and double antibody was used to adjust the cell concentration to 1 × 105/mL. The cells were seeded in a 96-well culture plate at a volume of 100 μL per well and cultured in a 37°7 cell incubator containing 5% CO2 for 24 h. Then, the gradient concentration of triptonoditerpenic acid was added to obtain a final concentration of 20, 40, 80, and 160 nmol/L, respectively. Among them, 0 nmol/L was set as the control group, and six replicate wells were made for each group. After 24, 48, 72, and 96 h, 10 μL Cell Counting Kit-8 was added to each well and incubated for 4 h. The optical density, D(λ), was determined to be 450 nm. The cell proliferation inhibition rates were calculated using the formula: Cell proliferation inhibition rate (%) =(1 − D(λ) drug treatment group/D(λ) control group) × 100%.

Effect of Triptonoditerpenic acid on Bcl-2 and Bax gene expression in SW480 cells

SW480 cells with final concentrations of 20, 40, 80, and 160 nmol/L were treated with triptonoditerpenic acid for 48 h and rinsed with phosphate-buffered saline (PBS) gently three times. Total cell RNA was extracted using the TRIzol method, and cDNA was synthesized by reverse transcription polymerase chain reaction (PCR). The expression levels of Bcl-2 and Bax genes were measured by PCR. The primer sequences for Bcl-2 and Bax were as follows:

Bcl-2:F-5'-GACTGAGTACCTGAACCGGCATC-3', R-5'-CTGAGCAGCGTCTTCAGAGACA-3'; Bax:F-5'-CGAATTGGCGATGAACTGGA-3', R-5'-CAAACATGTCAGCTGCCACAC-3'; GAPDH: F-5'-GCACAGTCAAGGCTGAGAATG-3', R-5'-ATGGTGGTGAAGACGCCAGTA-3'.

Effect of triptonoditerpenic acid on PTGS2 protein expression in SW480 cells

SW480 cells with final concentrations of 20, 40, 80, and 160 nmol/L were treated with triptonoditerpenic acid for 48 h, collected via centrifugation (1000 rpm, 5 min), and had their the total cell protein extracted routinely. Protein concentration was detected using a protein quantitative kit (BCA). Proteins (50 μg) were separated via Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis, transferred to polyvinylidene difluoride membranes, and blocked with 5% skim milk solution for 2 h at the room temperature. The PTGS2 primary antibody was added to the refrigerator at 4°t overnight. The membrane was washed with PBS five times, followed by the addition of secondary antibodies and incubated at the room temperature for 3 h. For the development, the membrane was washed with PBS five times and treated with enhanced chemiluminescence reagent for chemiluminescence. Image J software (version 1.8.0, https://imagej.nih.gov/ij/) was used for Grayscale analysis of images, using GAPDH as a reference. Protein expression level was computed using the following equation: Protein expression level = gray value of protein band/GAPDH band gray value.


  Results Top


Active components in Tripterygium wilfordii and target prediction

By screening all active components and targets in the TCMSP database, 144 active components and 1055 targets were identified. The active components of T. wilfordii were screened again according to the parameters of of OB and DL. A total of 51 active components and 494 targets were identified [Table 1].
Table 1: Hemogram parameters between the patient and control groups

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Traditional Chinese medicine - disease gene construction

A total of 920 disease-related genes of cancer and 121 targets of T. wilfordii were identified, and the genes related to cancer and T. wilfordii were intersected by R software. A Venn diagram containing 55 common targets was obtained thereafter [Figure 1] and [Table 2].
Figure 1: Traditional Chinese medicine - Disease genes. Disease represented cancer, Drug represented Tripterygium wilfordii

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Table 2: Receiver operating characteristic analysis

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The network construction of TCM - component - disease - gene network

The 25 active components of T. wilfordii mainly affected 55 cancer genes, forming a complex network of interactions that may affect the occurrence and development of cancer [Figure 2].
Figure 2: The regulatory network of traditional Chinese medicine – component – disease – gene. The red rhomboid represents cancer, the green oval represents the active component of Tripterygium wilfordii, the yellow oval represents the active component, and the purple hexagon represents the common genes

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Construction of traditional Chinese medicine- disease target protein interaction network and screening of core targets

The TCM - disease target protein interaction network had a total of 55 nodes and 545 edges, forming a complex network. According to the number of adjacent nodes, the top three TCM disease core targets were AKT1, PTGS2, VEGFA, CXCL8, and JUN. These may be the core targets of the interaction network [Figure 3].
Figure 3: Traditional Chinese medicine-Disease target protein protein interaction network. (a) Protein protein interaction network; (b) Barplot of traditional Chinese medicine-Disease core targets. On the left is the name of the targets, while the number corresponds to the number of adjacent nodes of the targets

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GO functional enrichment analysis

The GO functions of the core targets of T. wilfordii against cancer are mainly as follows: positive regulation of reactive oxygen species metabolic process, positive regulation of lymphocyte proliferation, positive regulation of phosphorylation of STAT protein, extrinsic apoptotic signaling pathway, TRIF-dependent toll-like receptor signaling pathway, nuclear receptor activity, regulation of blood vessel endothelial cell migration, response to lipopolysaccharide, long-chain fatty acid biosynthetic process, etc. [Figure 4]. The anticancer function of T. wilfordii may be mainly related to the regulation of reactive oxygen metabolism, regulation of cancer cell proliferation, cancer cell apoptosis, and regulation of blood vessel growth.
Figure 4: Clustering diagram of gene ontology functional enrichment analysis

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Kyoto encyclopedia of genes and genomes pathway enrichment analysis

The KEGG pathways of the core targets of T. wilfordii against cancer are mainly involved in the following: Interleukin (IL-17) signaling pathway, Kaposi sarcoma-associated herpes virus infection, fluid shear stress and atherosclerosis, tumor necrosis factor (TNF) signaling pathway, toxoplasmosis, Advanced Glycation End product-Receptor of Advanced Glycation End product (AGE-RAGE) signaling pathway in diabetic complications, hepatitis B, measles, Epstein − Barr virus infection, platinum drug resistance, Chagas disease (American trypanosomiasis), apoptosis, Th17 cell differentiation, human cytomegalovirus infection, CRC, and small cell lung cancer [Figure 5].
Figure 5: Kyoto encyclopedia of genes and genomes pathway enrichment analysis. (a) Barplot of Kyoto encyclopedia of genes and genomes pathway enrichment analysis; (b) Dotplot of Kyoto encyclopedia of genes and genomes pathway enrichment analysis. On the left of barplot is the name of Kyoto encyclopedia of genes and genomes, and the number below corresponds to the number of genes enriched on Kyoto encyclopedia of genes and genomes. The histogram represents genes enriched on Kyoto encyclopedia of genes and genomes, P represents the significance of enrichment. The redder the color, the higher the degree of enrichment, and the smaller the P value. On the left of dotplot is Kyoto encyclopedia of genes and genomes name, and the number below corresponds to the ratio of targets. The circle size represents the number of targets enriched, and the color represents P value. The redder the color, the higher the degree of enrichment, and the smaller the P value

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Combining the literature on cancer signaling pathways, we found that IL-17 signaling pathway,[9] kaposi sarcoma-associated herpesvirus infection,[10] TNF signaling pathway,[11] toxoplasmosis,[12] AGE-RAGE signaling pathway in diabetic complications,[13] hepatitis B,[14] measles,[15] Epstein − Barr virus infection,[16] platinum drug resistance,[17] apoptosis,[18] CRC,[19] small cell lung cancer[20] are involved in cancer development.

Molecular docking

To verify the accuracy of the network analysis results, this study selected the Protein–protein interaction network, in which the top five target proteins (AKT1, PTGS2, VEGFA, CXCL8, and JUN) were used for molecular docking with the active components of T. wilfordii. The vina score was evaluated using the vina program to perform molecular docking of the receptor and ligand with corresponding pocket parameters. The lower the score, the higher the affinity between the receptor and ligand. The docking results showed that the vina score of the affinity between triptolide and AKT1 was −10.4 kcal·mol−1 [Figure 6]a; Triptonoditerpenic acid with PTGS2 was −8.4 kcal·mol−1 [Figure 6]b; Celafurine with VEGFA was -8.7 kcal·mol−1 [Figure 6]c; Tripchlorolide with CXCL8 was -8.6 kcal·mol−1 [Figure 6]d; and Canin with JUN was -9.1 kcal·mol−1 [Figure 6]e. The results showed that the target proteins AKT1, PTGS2, VEGFA, CXCL8, and JUN had good binding activities with triptolide, triptonoditerpenic acid, celafurine, tripchlorolide, and canin, respectively.
Figure 6: Molecular docking models of EAKT1, PTGS2, VEGFA, CXCL8 and JUN. (a) The docking model of AKT1 and triptolide; (b) The docking model of PTGS2 and Triptonoditerpenic acid; (c) The docking model of VEGFA and celafurine; (d) The docking model of CXCL8 and tripchlorolide; (e) The docking model of JUN and canin

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Effect of triptonoditerpenic acid on the proliferation inhibition rate of SW480 cells

After treatment with different concentrations (20, 40, 80, and 160 nmol/L) of triptonoditerpenic acid at different times (24, 48, 72, and 96 h), the proliferation inhibition rate of human CRC SW480 cells increased, showing a concentration-and time-dependent [Figure 7].
Figure 7: Effects of triptonoditerpenic acid on the proliferation inhibition rate of SW480 cells(± s, n = 6). Compared with control group for 24 h, *P < 0.05, **P < 0.01, compared with control group for 48 h, #P < 0.05, ##P < 0.01, compared with control group for 72 h, &P < 0.05, &&P < 0.01, compared with control group for 96 h, @P < 0.05 and @@P < 0.01

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Effect of triptonoditerpenic acid on mRNA expression of Bcl-2 and Bax in SW480 cells

Compared with the control group, the expression level of Bcl-2 mRNA was significantly decreased in the triptonoditerpenic acid group (P < 0.05), while the expression level of Bax mRNA was significantly increased (P < 0.05) in a concentration-dependent manner [Table 3].
Table 3: Hemogram parameters in patients with fibromyalgia before and after the therapy

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Effect of triptonoditerpenic acid on PTGS2 expression in SW480 cells

The expression level of PTGS2 in the Triptonoditerpenic acid group was significantly decreased than control group (P < 0.05) with a concentration-dependent way [Figure 8].
Figure 8: Effects of triptonoditerpenic acid on the expression of PTGS2 of SW480 cells (x¯ ± s). Compared with control group, *P < 0.05, **P < 0.01

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  Discussion Top


T. wilfordii was first recorded in the Shen Nong's Herbal Classic. It is bitter tasting, cold, extremely poisonous, and is more often used as a medicine for the external application rather than taken orally. In clinical applications, T. wilfordii has been found to treat refractory diseases such as autoimmune diseases within a certain dose range. It is, by far, the most effective form of Chinese medicine, and there are a few similar Chinese medicines that it can replace. Studies have shown that[6],[7] T. wilfordii has a good therapeutic effect on various cancers. The examples include stomach cancer, skin cancer, nasopharyngeal cancer, and breast cancer. However, the mechanism of anticancer activity has not been fully elucidated. Our study aimed to screen target proteins related to the shared signaling pathways of cancer and arthritis. Unfortunately, the target proteins associated with the shared signaling pathways of cancer and arthritis could not be identified as expected after screening. Therefore, we only screened the target proteins related to the signaling pathways of cancer and verified them through cell experiments in this study.

This study shows that the active components of T. wilfordii can affect the occurrence and development of cancer through multiple targets and signaling pathways. The main targets of T. wilfordii against cancer include AKT1, PTGS2, VEGFA, CXCL8, JUN, MAPK8, MMP9, STAT3, IL-4, MAPK14, ICAM1, CD40, FOS, IFNG, IL-2, CASP8, VCAM1, CXCR4, PPARG, AR, MCL1, MMP1, TIMP1, AHR, CDKN1A, NOS2, CASP9, SELE, and BIRC3. These targets can affect physiological functions to regulate the occurrence and development of cancer. For example, positive regulation of reactive oxygen species metabolic process, positive regulation of lymphocyte proliferation, positive regulation of phosphorylation of STAT protein, nuclear receptor activity, regulation of blood vessel endothelial cell migration, response to lipopolysaccharide, and long-chain fatty acid biosynthetic process. Molecular docking confirmed that the target proteins AKT1, PTGS2, VEGFA, CXCL8, and JUN had good binding activities with triptolide, triptonoditerpenic acid, celafurine, tripchlorolide, and canin, respectively.

There are many KEGG pathways for T. wilfordii against cancer. They are mainly involved in the following: IL-17 signaling pathway, kaposi sarcoma-associated herpesvirus infection, fluid shear stress and atherosclerosis, TNF signaling pathway, toxoplasmosis, AGE-RAGE signaling pathway in diabetic complications, hepatitis B, measles, Epstein − Barr virus infection, platinum drug resistance, chagas disease (American trypanosomiasis), apoptosis, Th17 cell differentiation, Human cytomegalovirus infection, CRC, and small cell lung cancer, among others. Zhang et al.[21] found that T. wilfordii enhances the antitumor activity of sorafenib in HCC tumor cells by suppressing the AKT pathway and VEGF autocrine system. Xiang et al.[22] found that T. wilfordii markedly inhibited human metastatic gastric cancer cell migration, invasion, proliferation, and tumorigenicity. Molecular mechanistic studies have shown that triptonide significantly reduces Notch1 protein levels in metastatic gastric cancer cells by degrading the oncogenic protein Notch1 via the ubiquitin-proteasome pathway.

CRC is one of the most frequent gastrointestinal malignancies and is the second most common gastrointestinal cancer. Chemotherapy is one of the main treatments for CRC. At present, the commonly used therapeutic drugs include 5-fluorouracil, carboplatin, and cisplatin, all of which have disadvantages such as poor therapeutic effect, large toxicity and side effects, and drug resistance caused by long-term use.[23] Therefore, there is an urgent need to explore the pathogenesis of CRC and identify effective therapeutic drugs. Based on network pharmacology and molecular docking data mining, this experiment preliminarily found that triptonoditerpenic acid has good binding activity with PTGS2. Studies have shown that[24] the PTGS2 gene is highly expressed in stage III colon cancer patients, suggesting that inhibiting PTGS2 expression may be an effective approach for the prevention and treatment of colorectal cancer. Therefore, the effect of Triptonoditerpenic acid on human colorectal cancer SW480 cells was further verified by this study, and it was found that it can inhibit the proliferation and induce the apoptosis of SW480 cells. The mechanism may be related to the inhibition of PTGS2 protein expression, downregulation of Bcl-2 expression, and upregulation of Bax mRNA expression.


  Conclusions Top


T. wilfordii regulates the occurrence and development of cancer through multiple components, targets and pathway interactions. In addition, its active ingredient, triptonoditerpenic acid, can significantly inhibit the proliferation and induce the apoptosis of SW480 cells, which will provide a basis for further research on the application of T. wilfordii in the prevention and treatment of cancer and also provide a new idea for the prevention and treatment of cancer; however, it is essential to note that because of the diversity of its targets, side effects may occur when treated with T. wilfordii. In addition, new network pharmacology databases, such as SymMap and ETCM, have been developed with more clinically relevant information. However, it would be a limitation that our study has just used TCMSP to curate the pharmacological relationships.

Data availability

The data used to support the findings of this study are available. The links to the databases are available at the corresponding locations in the original text.

Acknowledgments

This work was supported by the Guangzhou Concord Medical Humanities Research and Education Fund (23000-3050070), Project of Education Department of Guangdong Province (fund project of “Strengthening and Strengthening” of Guangdong Medical University in 2021)(4SG21202G), and Science popularization project of Science and Technology Development Center of Chinese Pharmaceutical Society (CMEI2021KPYJ00310).

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Correspondence Address:
Yong-Li Situ,
Jinan University, Guangzhou 510632, Guangdong
China
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2311-8571.344544



    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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    -  Li SJ
    -  Fang WX
    -  Chen J
    -  Li HJ
    -  Situ YL


Abstract
Introduction
Materials and Me...
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