scholarly journals Network Pharmacology Approach to Uncover the Mechanism Governing the Effect of Simiao Powder on Knee Osteoarthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhengquan Huang ◽  
Xiaoqing Shi ◽  
Xiaochen Li ◽  
Li Zhang ◽  
Peng Wu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Knee Osteoarthritis ◽  
Signaling Pathway ◽  
Protein Interaction ◽  
Cell Metabolism ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Components ◽  
Discovery Studio

Objective. To explore the molecular mechanism of Simiao powder in the treatment of knee osteoarthritis. Methods. Based on oral bioavailability and drug-likeness, the main active components of Simiao powder were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). GeneCard, OMIM, DisGeNET, DrugBank, PharmGkb, and the Therapeutic Target Database were used to establish target databases for knee osteoarthritis. Cytoscape software was used to construct a visual interactive network diagram of “active ingredient - action target – disease.” The STRING database was used to construct a protein interaction network and analyze related protein interaction relationships. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) biological process enrichment analysis were performed on the core targets. Additionally, Discovery Studio software was used for molecular docking verification of active pharmaceutical ingredients and disease targets. Results. Thirty-seven active components of Simiao powder were screened, including 106 common targets. The results of network analysis showed that the targets were mainly involved in regulating biological processes such as cell metabolism and apoptosis. Simiao powder components were predicted to exert their therapeutic effect on the AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and HIF-1 signaling pathway. The molecular docking results showed that the active components of Simiao powder had a good match with the targets of IL1B, MMP9, CXCL8, MAPK8, JUN, IL6, MAPK1, EGF, VEGFA, AKT1, and PTGS2. Conclusion. Simiao powder has multisystem, multicomponent, and multitarget characteristics in treating knee osteoarthritis. Its possible mechanism of action includes inhibiting the inflammatory response, regulating immune function, and resisting oxidative stress to control the occurrence and development of the disease. Quercetin, wogonin, kaempferol, beta-sitosterol, and other active ingredients may be the material basis for the treatment of knee osteoarthritis.

scholarly journals A Network Pharmacology and Molecular Docking Approach to Investigate the Anticoronavirus-Induced Diseases Effect of Yinqiao Powder Combined With Modified Sangju Decoction

2021 ◽  
Vol 16 (9) ◽  
pp. 1934578X2110352
Author(s):  
Tian-Shun Wang ◽  
Xing-Pan Wu ◽  
Qiu-Yuan Jian ◽  
Yan-Fang Yang ◽  
Wu He-Zhen
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Treatment Strategies ◽  
Interaction Network ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Common Mechanism ◽  
Active Components ◽  
Discovery Studio ◽  
The Core

Severe acute respiratory syndrome (SARS) once caused great harm in China, but now it is the coronavirus disease 2019 (COVID-19) pandemic that has become a huge threat to global health, which raises urgent demand for developing effective treatment strategies to avoid the recurrence of tragedies. Yinqiao powder, combined with modified Sangju decoction (YPCMSD), has been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanism of YPCMSD in the treatment of SARS and COVID-19 through network pharmacology and molecular docking and further explore the potential application value of YPCMSD in the treatment of coronavirus infections. Firstly, the active components were collected from the literature and Traditional Chinese Medicine Systems Pharmacology database platform. The COVID-19 and SARS associated targets of the active components were forecasted by the SwissTargetPrediction database and GeneCards. A protein–protein-interaction network was drawn and the core targets were obtained by selecting the targets larger than the average degree. By importing the core targets into database for annotation, visualization, and integrated discovery, enrichment analysis of gene ontology, and construction of a Kyoto Encyclopedia of genes and genomes pathway was conducted. Cytoscape 3.6.1 software was used to construct a “components–targets–pathways” network. Active components were selected to dock with acute respiratory syndrome coronavirus type 2 (SARS-COV-2) 3CL and angiotensin-converting enzyme 2 (ACE2) through Discovery Studio 2016 software. A network of “components–targets–pathways” was successfully constructed, with key targets involving mitogen-activated protein kinase 1, caspase-3 (CASP3), tumor necrosis factor (TNF), and interleukin 6. Major metabolic pathways affected were those in cancer, the hypoxia-inducible factor 1 signaling pathway, the TNF signaling pathway, the Toll-like receptor signaling pathway, and the PI3K-Akt signaling pathway. The core components, such as arctiin, scopolin, linarin, and isovitexin, showed a strong binding ability with SARS-COV-2 3CL and ACE2. We predicted that the mechanism of action of this prescription in the treatment of COVID-19 and SARS might be associated with multicomponents that bind to SARS-COV-2 3CL and ACE2, thereby regulating targets that coexpressed with them and pathways related to inflammation and the immune system.

scholarly journals Mechanism of Compound Houttuynia Mixture as an Anti-COVID-19 Drug Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110167
Author(s):  
Xing-Pan Wu ◽  
Tian-Shun Wang ◽  
Zi-Xin Yuan ◽  
Yan-Fang Yang ◽  
He-Zhen Wu
Keyword(s):  
Molecular Docking ◽  
Target Prediction ◽  
Interaction Network ◽  
Scientific Basis ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Discovery Studio ◽  
The Core ◽  
Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

scholarly journals Studies on the Mechanism of Gegen Qinlian Decoction in Treating Diabetes Mellitus Based on Network Pharmacology

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098213
Author(s):  
Xiaodong Deng ◽  
Yuhua Liang ◽  
Jianmei Hu ◽  
Yuhui Yang
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Network Pharmacology ◽  
Hub Genes ◽  
Topological Parameters

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.

scholarly journals The Underlying Mechanism of Chinese Herb of Regulating Marrow in the Treatment of  Osteonecrosis of the Femoral Head Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xiaojian Wang ◽  
Rui Wang ◽  
Ting Xu ◽  
Hongting Jin ◽  
Peijian Tong ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Active Components ◽  
Pathway Enrichment

Abstract Background The lesion of marrow is a crucial factor in orthopedic diseases, which is recognized by orthopedics-traumatology expert from "Zhe-School of Chinese Medicine". The Chinese herbs of regulating marrow has been widely used to treat osteonecrosis of the femoral head (ONFH) in China, while the interaction mechanisms were still elucidated. Thus, we conducted this study to explore the underlying mechanism of the five highest-frequency Chinese herbs of regulating marrow(HF-CHRM) in the treatment of ONFH with the aid of network pharmacology(NP) and molecular docking(MD). Methods The active components and potential targets of HF-CHRM were obtained through several online databases, such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), UniProt database. The gene targets related to ONFH were collected with the help of the OMIM and GeneCards disease-related databases. The "drug- component-target-disease" network and protein-protein interaction(PPI) network of the drug and disease intersecting targets were constructed by using Cytoscape software and the STRING database. R software was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The MD of critical components and targets was carried out using Autodock Vina and Pymol to validate the binding affinity. Results A total of 54 active components, 1074 drug targets and 195 gene targets were obtained. There were 1219 ONFH related targets. 39 drug and disease intersection targets(representative genes: IL6, TP53, VEGFA, ESR1, IL1B) were obtained and considered potential therapeutic targets. 1619 items were obtained by the GO enrichment analysis, including 1517 biological processes, 10 cellular components and 92 molecular functions, which is mainly related to angiogenesis, bone and lipid metabolism and inflammatory reaction. The KEGG pathway enrichment analysis revealed 119 pathways, including AGE-RAGE signaling pathway, PI3K-Akt signaling pathway and IL-17 signaling pathway. MD results showed that quercetin, wogonin, and kaempferol active components had good affinity with IL6, TP53, and VEGFA core proteins. Conclusion The HF-CHRM can treat ONFH by multi-component, multi-target, and multi-pathway comprehensive action.

scholarly journals Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Minglong Guan ◽  
Lan Guo ◽  
Hengli Ma ◽  
Huimei Wu ◽  
Xiaoyun Fan
Keyword(s):  
Biological Activity ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Rosmarinic Acid ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

scholarly journals Study on the Mechanism of Acori Graminei Rhizoma in the Treatment of Alzheimer’s Disease Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yi Kuan Du ◽  
Yue Xiao ◽  
Shao Min Zhong ◽  
Yi Xing Huang ◽  
Qian Wen Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
The Elderly ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Active Components

Alzheimer’s disease is a common neurodegenerative disease in the elderly. This study explored the curative effect and possible mechanism of Acori graminei rhizoma on Alzheimer’s disease. In this paper, 8 active components of Acori graminei rhizoma were collected by consulting literature and using the TCMSP database, and 272 targets were screened using the PubChem and Swiss Target Prediction databases. Introduce it into the software of Cytoscape 3.7.2 and establish the graph of “drug-active ingredient-ingredient target.” A total of 276 AD targets were obtained from OMIM, Gene Cards, and DisGeNET databases. Import the intersection targets of drugs and diseases into STRING database for enrichment analysis, and build PPI network in the Cytoscape 3.7.2 software, whose core targets involve APP, AMPK, NOS3, etc. GO analysis and KEGG analysis showed that there were 195 GO items and 30 AD-related pathways, including Alzheimer’s disease pathway, serotonin synapse, estrogen signaling pathway, dopaminergic synapse, and PI3K-Akt signaling pathway. Finally, molecular docking was carried out to verify the binding ability between Acori graminei rhizoma and core genes. Our results predict that Acori graminei rhizoma can treat AD mainly by mediating Alzheimer’s signal pathway, thus reducing the production of Aβ, inhibiting the hyperphosphorylation of tau protein, regulating neurotrophic factors, and regulating the activity of kinase to change the function of the receptor.

scholarly journals Research on the Treatment of Colorectal Cancer Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Shu Xinyao ◽  
Zhang Yunwu ◽  
Wang Yujia ◽  
Wu Jing ◽  
Chen Xingyu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Drug Targets ◽  
Cell Metabolism ◽  
Enrichment Analysis ◽  
Endocrine Tumor ◽  
Network Pharmacology ◽  
Active Components ◽  
Sophora Japonica ◽  
Core Components

Abstract Background: To predict the mechanism of Huaijiao Diyu Decoction in the treatment of colorectal cancer. Methods: The active components and related targets of 7 kinds of Chinese medicinal materials were collected from the database of Chinese medicinal materials. CRC related targets are obtained from the Genes card database. cross targets of disease and drug targets were input into the STRING database to construct protein-protein interaction networks.GO enrichment analysis and KEGG enrichment analysis using clusterProfiler packets in the language, Finally, the interaction between core components and core targets is discussed by molecular docking.Result: TCMSP database prompts, There are 34 active compounds mapping 114 targets in Sophora japonica decoction; G enecards database prompts, A total of 858 targets are closely related to CRC, The two data sets map each other to obtain 114 intersection targets. Core components of Sophora flavescens decoction in treating CRC may be quercetin, kaempferol, luteolin, The core therapeutic targets may be PTGS2、PTGS1、HSP90AA1 and AR, CRC related pathways involve multiple molecular functions such as cell proliferation, apoptosis, cell signal transduction, metabolism, endocrine, tumor immunity, transcription and cell metabolism. Molecular docking results show that the binding ability of PTGS1、PTGS2、AR to core components is strong, The Vina value (binding energy) of the interaction between PTGS1 protein and core components is the best, -7.9kcal/mol . Conclusion: This study demonstrates the mechanism of multi-component, multi-target and multi-pathway action in the treatment of CRC, Can provide the idea for clarifying the specific mechanism of Huaijiao Diyu decoction in the treatment of CRC in the future.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Yinma Jiedu Granules

2021 ◽  
Vol 16 (2) ◽  
pp. 1934578X2199171
Author(s):  
ZiXin Yuan ◽  
Can Zeng ◽  
Bing Yu ◽  
Ying Zhang ◽  
TianShun Wang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Hypoxia Inducible Factor ◽  
Growth Factor Receptor ◽  
Interaction Network ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Discovery Studio

To investigate the mechanism of action of components of Yinma Jiedu granules in the treatment of coronavirus disease 2019 (COVID-19) using network pharmacology and molecular docking. The main chemical components of Yinma Jiedu granules were collected in the literature and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Using the SwissTargetPrediction database, the targets of the active component were identified and further correlated to the targets of COVID-19 through the GeneCards database. The overlapping targets of Yinma Jiedu granules components and COVID-19 were identified as the research target. Using the Database for Annotation, Visualization and Integrated Discovery database to carry out the target gene function Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation and Cytoscape 3.6.1 software was used to construct a “component-target-pathway” network. The protein-protein interaction network was built using Search Tool for the Retrieval of Interacting Genes/Proteins database. Using Discovery Studio 2016 Client software to study the virtual docking of key protein and active components. One hundred active components were screened from the Yinma Jiedu Granules that involved 67 targets, including mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor, tumor necrosis factor, tumor protein 53, and MAPK1. These targets affected 109 signaling pathways including hypoxia-inducible factor-1, apoptosis, and Toll-like receptor signaling pathways. Molecular docking results showed that the screened active components have a strong binding ability to the key targets. In this study, through network pharmacology and molecular docking, we justified the multicomponent, multitarget, and multipathways of Yinma Jiedu Granules in the treatment of COVID-19.

scholarly journals Investigating the pharmacological mechanisms of SheXiang XinTongNing against coronary heart disease based on network pharmacology

2020 ◽  
Author(s):  
Li-ying Jia ◽  
Jia Li ◽  
Gui-yun Cao ◽  
Zhao-qing Meng ◽  
Lu Gan ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology

Abstract Background SheXiang XinTongNing, a commercially available Chinese patent medicine, has been widely used in the treatment of coronary heart disease. However, the mechanisms of SheXiang XinTongNing are still unclear. The aim of this study was to investigate the pharmacological mechanisms of SheXiang XinTongNing against coronary heart disease via network analysis. Method The traditional Chinese medicine system pharmacology analysis platform was used to screen the potential active constituents of the six traditional Chinese medicines in SheXiang XinTongNing, and the potential targets were obtained from PharmMapper. The genome annotation database platform was used to screen the candidate targets related to coronary heart disease. Then the drug-components-targets network and protein interaction network were built by Cytoscape 3.6.0 software. Further, GO bio-functional enrichment analysis and KEGG pathway enrichment analysis were performed through annotation, visualization and integrated discovery database. Results Results showed that the drugs-components-targets network contains 104 targets and 62 key components. The protein interaction network consisted of 107 nodes; key targets included Bcl2l1, IGF1, SRC, CASP3, et al. Functionally, the candidate targets were significantly associated with multiple pathways such as PI3K-Akt signaling pathway, MAPK signaling pathway, Ras signaling pathway, FoxO signaling pathway, Endocrine resistance. Given the above, the pharmacological activities of SheXiang XinTongNing may be predominantly related to several factors such as cell apoptosis, inflammation and angiogenesis. Conclusion XTN can effectively attenuate the symptoms of coronary heart disease through diverse pathways. The research proves that network pharmacology can successfully reveal the mechanisms of traditional Chinese medicine in a holistic view. Our systematic analysis lays a foundation for further studying.

scholarly journals Network Pharmacology-Based Prediction of the Active Ingredients and Potential Targets of Chinese Herbal Danyu Gukang Pills for Application to Osteonecrosis of the Femoral Head Disease

2021 ◽  
Author(s):  
Yongchang Guo ◽  
Dapeng Zhang ◽  
Yuju Cao ◽  
Xiaoyan Feng ◽  
Caihong Shen ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Femoral Head ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
In Vitro Experiments ◽  
Active Components

Abstract Ethnopharmacological relevanceOsteonecrosis of the femoral head (ONFH) is still a challenge for orthopedists worldwide, which may lead to disability in patients without effective treatment. A newly developed formula of Chinese medicine, Danyu Gukang Pills (DGP), was recognized to be effective for ONFH. Nevertheless, its molecular mechanisms remain to be clarified. MethodsNetwork pharmacology was adopted to detect the mechanism of DGP on ONFH. The compounds of DGP were collected from the online databases, and active components were selected based on their OB and DL index. The potential proteins of DGP were acquired from TCMSP database, while the potential genes of ONFH were obtained from Gene Cards and Pubmed Gene databases. The function of Gene and potential pathways were researched by GO and KEGG pathway enrichment analysis. The compounds-targets and targets-pathways network were constructed in an R and Cytosacpe software. The mechanism was further investigated via molecular docking. Finally, in-vitro experiments were validated in the BMSCs. ResultsA total of 2305 compounds in DGP were gained, among which, 370 were selected as active components for which conforming to criteria. Combined the network analysis, molecular docking and in-vitro experiments, the results firstly demonstrated that the treatment effect of DGP on ONFH may be closely related to HIF-1α, VEGFA and HIF-1 signaling pathway. ConclusionThe current study firstly researched the molecular mechanism of DGP on ONFH based on network pharmacology. The results indicated that DGP may exert the effect on ONFH targeting on HIF-1α and VEGFA via HIF-1 signaling pathway.

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