A Study on the Mechanism of Lavender in the Treatment of Insomnia Based on Network Pharmacology

2020 ◽  
Vol 23 (5) ◽  
pp. 419-432
Author(s):  
Yao Wang ◽  
Junbo Zou ◽  
Yanzhuo Jia ◽  
Yulin Liang ◽  
Xiaofei Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Protein ◽  
Ammonium Ion ◽  
Network Pharmacology ◽  
Common Disease ◽  
Active Components ◽  
Target Proteins ◽  
Analysis Platform

Aim and Objective: The common disease of insomnia has complex and diverse clinical manifestations. Lavender represents an effective treatment of insomnia, but the molecular mechanism underlying the effectiveness of this treatment is not clear. The purpose of this study is to investigate the active components, target proteins and molecular pathways of lavender in the treatment of insomnia, thus explaining its possible mechanism. Materials and Methods: Firstly, 54 active components of lavender were identified by gas chromatography-mass spectrometry (GC-MS). The target protein of lavender was predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and the target protein of insomnia was predicted by the DisGeNET and DrugBank databases. Then, the "component-target-disease" network diagram was constructed using the Cytoscape 3.7.1 software. KEGG and GO enrichments were analyzed using the R statistical language. Finally, the key target proteins were verified by collecting and verifying the target protein GEO data using the Discovery Studio 3.5 molecular docking verification software. Results: 906 target proteins of lavender were predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and 182 insomnia target proteins were predicted by the DisGeNET and DrugBank databases. The results of GO enrichment analysis showed that it included the reaction process of ammonium ion, the regulation of the membrane potential and the secretion of catecholamine, while the results of KEGG enrichment included the calcium signaling pathway, serotonin synapse, morphine addiction and many more. Finally, using the Discovery Studio3.5 molecular docking verification software, it was verified that the key target proteins are ADRB1 and HLA-DRB1. Conclusion: The components in the lavender essential oil include the Ethyl 2-(5-methyl-5-vinyltetrahydrofuran- 2-yl)propan-2-ylcarbonate (0.774); 5-Oxatricyclo[8.2.0.04,6]dodecane, 4,12,12-trimethyl- 9-methylene-, (1R,4R,6R,10S)-(0.147); P-Cymen-7-ol (0.063); .alpha-Humulenem (0.317); Acetic acid, hexyl ester (1.374); etc. The role lavender plays in the treatment of insomnia might be accomplished through the regulation of the key targets ADRB1 and HLA-DRB1.

scholarly journals Exploring anti-nonalcoholic fatty liver disease mechanism of Gardeniae Fructus by combining an animal model with network pharmacology and molecular docking

2020 ◽  
Author(s):  
Lin Li ◽  
Lihua Lu ◽  
Zhong-yan Tang ◽  
Zhengxiang Xia
Keyword(s):  
Animal Model ◽  
Molecular Docking ◽  
Surface Plasmon Resonance ◽  
Liver Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Fatty Liver Disease ◽  
Target Protein ◽  
Network Pharmacology ◽  
Nonalcoholic Fatty Liver

Abstract Background Gardeniae Fructus (GF), a traditional Chinese medicine in clinic for the treatment of nonalcoholic fatty liver disease (NAFLD). However, the mechanisms of action of GF was still margin. To explore the efficacy and mechanism of action of GF for the treatment of NAFLD, we proposed a strategy combined in vivo efficacy verification, network pharmacology analysis, molecular docking, and validity assay of target protein. Methods Firstly, an animal model induced by the high fat diet feed was established, then orally administrated with GF, the mRNA expression levels of lipogenesis was performed by RT-PCR, the liver tissue specimens were stained by hematoxylin and eosin (H&E), then observed by light microscopy. Secondly, network pharmacology studies clarified the relationship among the active constituents, target protein, and pathways, and then explored by the molecular docking. Finally, validity assay of target protein was performed in surface plasmon resonance (SPR) test. Results GF protected against NAFLD in rats. Network pharmacology showed that quercetin, oleanolic acid, and geniposide, targeted on PPARα, PPARγ, and CA2 genes, through regulating PPAR, AMPK, and cGMP-PKG signal pathways, to protect against NAFLD. And the Conclusion GF could alleviate NAFLD through the molecular mechanisms explored by network pharmacology, molecular docking, and surface plasmon resonance, those method can be effective tools to clarify the mechanisms of actions of traditional Chinese medicine from a holistic perspective.

scholarly journals Network Pharmacology and Molecular Docking Combined to Analyze the Molecular and Pharmacological Mechanism of Pinellia ternata in the Treatment of Hypertension

2021 ◽  
Vol 43 (1) ◽  
pp. 65-78
Author(s):  
Zhaowei Zhai ◽  
Xinru Tao ◽  
Mohammad Murtaza Alami ◽  
Shaohua Shu ◽  
Xuekui Wang
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Western Medicine ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
Pharmacological Mechanism ◽  
Effective Components ◽  
Treatment Of Hypertension

Hypertension is a cardiovascular disease that causes great harm to health and life, affecting the function of important organs and accompanied by a variety of secondary diseases, which need to be treated with drugs for a long time. P. ternata alone or combination with western medicine has played an important role in traditional Chinese medicine. Although P. ternata is used clinically to treat hypertension, its functional molecular mechanism and pharmacological mechanism have not been elucidated. Therefore, in this study, the potentially effective components, and targets of P. ternata in the treatment of hypertension were screened by the method of network pharmacology, and the mechanism of P. ternata in the treatment of hypertension was analyzed by constructing a component-target relationship network, PPI interaction network, targets’ function analysis, and molecular docking. In the study, 12 potentially effective components and 88 targets were screened, and 3 potential protein modules were found and analyzed after constructing a PPI network using targets. In addition, 10 targets were selected as core targets of the PPI network. After that, the targets were analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, the molecular docking method is used to study the interaction between the targets and the active components. The above evidence shows that the mechanism of P. ternata in the treatment of hypertension is complicated, as it acts in many ways, mainly by affecting nerve signal transmission, cell proliferation, and apoptosis, calcium channels, and so on. The binding between targets and active components mainly depends on Pi bonds and hydrogen bonds. Using the method of network pharmacology and molecular docking to analyze the mechanism of P. ternata in the treatment of hypertension will help to provide a better scientific basis for the combined use of traditional Chinese medicine and western medicine, and will better help to improve the quality of P. ternata and point out its direction.

scholarly journals Study on the Potential Mechanism of Fructus Tribuli in the Treatment of Hypertensive Vascular Remodeling Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Shuyue Wang ◽  
Fei Guo ◽  
Xiaochen Sun ◽  
Xiao Song ◽  
Yaohui Yuan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Vascular Remodeling ◽  
Network Pharmacology ◽  
Research Approach ◽  
Active Components ◽  
Active Compounds ◽  
Ppi Networks

Background. Hypertensive vascular remodeling (HVR) is the pathophysiological basis of hypertension, which is also an important cause of vascular disease and target organ damage. Treatment with Fructus Tribuli (FT), a traditional Chinese medicine, has a positive effect on HVR. However, the pharmacological mechanisms of FT are still unclear. Therefore, this study aimed to reveal the potential mechanisms involved in the effects of FT on HVR based on network pharmacology and molecular docking. Materials and Methods. We selected the active compounds and targets of FT according to the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Swiss Target Prediction database, and the targets of HVR were collected from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and DrugBank databases. The protein-protein interaction network (PPI) was established using the STRING database. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and network analysis were performed to further explore the potential mechanisms. Finally, molecular docking methods were used to evaluate the affinity between the active compounds and the main target. Results. Seventeen active compounds of FT  and 164 potential targets for the treatment of HVR were identified. Component-target and PPI networks were constructed, and 12 main active components and 33 main targets were identified by analyzing the topological parameters. Additionally, GO analysis indicated that the potential targets were enriched in 483 biological processes, 52 cellular components, and 110 molecular functions. KEGG analysis revealed that the potential targets were correlated with 122 pathways, such as the HIF-1 signaling pathway, ErbB signaling pathway, and VEGF signaling pathway. Finally, molecular docking showed that the 12 main active components had a good affinity for the top five main targets. Conclusion. This study demonstrated the multiple compounds, targets, and pathway characteristics of FT in the treatment of HVR. The network pharmacology method provided a novel research approach to analyze potential mechanisms.

scholarly journals Network Pharmacology-Based Approach to Investigate the Molecular Targets of Rhubarb for Treating Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Lan Jiang ◽  
Zhongquan Shi ◽  
Yi Yang
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Protein Interactions ◽  
Scientific Basis ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Active Components ◽  
Kegg Pathways

Background. As a traditional Chinese medicine, rhubarb (also named Dahuang) is used to treat various diseases. Objective. To explore the possible antitumor mechanism of rhubarb by using network pharmacology and molecular docking in this study. Methods. Bioactive ingredients and related targets of rhubarb were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. And the gene names corresponding to the proteins were found in the UniProt database. Then, the tumor-related targets were screened out from GeneCards and OMIM databases. Key antitumor targets of rhubarb were acquired by overlapping the above targets via the Venn diagram. The antitumor targets network of rhubarb active components was constructed by using Cytoscape 3.6.0 software. The protein interactions network was constructed using the STRING database. The GO and KEGG pathways involved in the targets were analyzed by using the DAVID database. Autodock Vina software was used to verify the molecular docking of rhubarb components and key targets. Results. Through screening and analysis, 10 active ingredients and 58 antitumor prediction targets were obtained and constructed a compound-target network. The targets such as CASP3, JUN, MYC, TNF, and PTGS2 may play a crucial role. These targets are involved in cancer pathway, calcium signaling pathway, cell apoptosis, small-cell lung cancer pathway, p53 signaling pathway, and TNF signaling pathway. The docking results indicated that the rhein binding with the CASP3 showed the highest binding energy. Conclusion. Based on the network pharmacology, the characteristics of multicomponent, multitarget, and multipathway of rhubarb were discussed, which provided a scientific basis for explaining the mechanism in treating cancer and new ideas for further research.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 and SARS Mechanism of Fufang Banlangen Keli

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098842
Author(s):  
Li Cheng ◽  
Fei Wang ◽  
Shun Bo Zhang ◽  
Qiu Yun You
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Docking Studies ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Active Components

Purpose Fufang Banlangen Keli (FBK) has been recommended for its clinical treatment of Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS), but the mechanism of action is unclear. So, using network pharmacology and molecular docking, we studied the active components and mechanism of FBK in the treatment of COVID-19 and SARS. Methods The Encyclopedia of Traditional Chinese Medicine and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform were used to screen the active components by oral bioactivity and drug likeness. Then, PharmMapper and SwissTargetPrediction databases were used to screen potential target genes of active components; the related target genes of COVID-19 and SARS were obtained from the GeneCards database. The intersection of the active components and disease-related targets was performed by the Venny2.1.0 database. The DAVID6.8 database and KOBAS3.0 database were used to get gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation of gene targets. The “components-targets-pathways (C-T-P)” network of FBK was conducted by Cytoscape3.6.1 software. The top active components, angiotensin-converting enzyme 2 (ACE2) and SARS-CoV-2 3 Cl, were imported into AutoDock and PyMOL for molecular docking. Results From the FBK, a total of 28 active components and 73 gene targets were screened through network pharmacology. Twenty pathways were analyzed, including pathways in cancer, nod-like receptor signaling pathway, and pancreatic cancer, etc. ( P < 0.05). A total of 337 items were obtained by GO functional enrichment analysis ( P < 0.05), including 257 items for biological process, 38 items for cell composition, and 42 items for molecular function. Furthermore, molecular docking studies were performed to study potential binding between the key gene targets and selected active components. Conclusion Based on network pharmacology and molecular docking technology, qingdainone, (2Z)-2-(2-oxoindolin-3-ylidene) indolin-3-one, sinensetin, and acacetin in FBK were verified to bind to ACE2 and SARS-COV-2 3 Cl, so as to treat COVID-19 and SARS.

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 A Network Pharmacology-Based Study on Active Ingredients of Corydalis Rhizoma on Coronary Heart Disease

2020 ◽  
Author(s):  
Ying Li ◽  
Guhang Wei ◽  
Zhenkun Zhuang ◽  
Mingtai Chen ◽  
Changjian Yuan ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Active Components

Abstract BackgroundCorydalis Rhizoma(CR) showed a high efficacy for coronary heart disease (CHD). However, the interaction between the active ingredients of CR and the targets of CHD has not been unequivocally explained in previous researches. To study the active components and potential targets of Corydalis Rhizoma and to determine the mechanism underlying the exact effect of Corydalis Rhizoma on coronary heart disease, a method of network pharmacology was used.Materials and MethodsThe active components of CR and targets corresponding to each component were scanned out from Traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), and target genes of CHD were searched on GeneCards database and Online Mendelian Inheritance in Man(OMIM) database. The active components and common targets of CR and CHD were used to build the “CR-CHD” network through Cytoscape (version 3.2.1) software as well as protein-protein interaction(PPI) network on String database. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis was executed by clusterProfiler(version 3.8) and DOSE(version 3.6) package on R platform.Results49 active ingredients and 394 relevant targets of CR and the 7173 CHD-related genes were retrieved. 40 common genes were selected for subsequent analysis. Crucial biological processes and pathways were obtained and analyzed, including DNA-binding transcription activator activity, RNA polymerase II-specific, RNA polymerase II transcription factor binding, kinase regulator activity, ubiquitin-like protein ligase binding, fluid shear stress and atherosclerosis, TNF signaling pathway, apoptosis, MAPK signaling pathway and PI3K-Akt signaling pathway.ConclusionsOverall, CR could alleviate CHD through the mechanisms predicted by network pharmacology, laying the foundation for future development of new drugs from traditional Chinese medicine on CHD.

scholarly journals Integrating Data Mining, Network Pharmacology, and Molecular Docking Verification to Investigate the Molecular Mechanism of Traditional Chinese Medicine Prescriptions for Treating Male Infertility

2021 ◽  
Author(s):  
Xue Bai ◽  
Yibo Tang ◽  
Qiang Li ◽  
Guimin Liu ◽  
Dan Liu ◽  
...  
Keyword(s):  
Data Mining ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Male Infertility ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Oxidant Stress ◽  
Estrogen Signaling ◽  
Network Pharmacology

Abstract Background: Male infertility (MI) affects almost 5% adult men worldwide, and 75% of these cases are unexplained idiopathic. There are limitations in the current treatment due to the unclear mechanism of MI, which highlight the urgent need for a more effective strategy or drug. Traditional Chinese Medicine (TCM) prescriptions have been used to treat MI for thousands of years, but their molecular mechanism is not well defined. Methods: Aiming at revealing the molecular mechanism of TCM prescriptions on MI, a comprehensive strategy integrating data mining, network pharmacology, and molecular docking verification was performed. Firstly, we collected 289 TCM prescriptions for treating MI from National Institute of TCM Constitution and Preventive Medicine for 6 years. Then, Core Chinese Materia Medica (CCMM), the crucial combination of TCM prescriptions, was obtained by the TCM Inheritance Support System from China Academy of Chinese Medical Sciences. Next, the components and targets of CCMM in TCM prescriptions and MI-related targets were collected and analyzed through network pharmacology approach.Results: The results showed that the molecular mechanism of TCM prescriptions for treating MI are regulating hormone, inhibiting apoptosis, oxidant stress and inflammatory. Estrogen signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, and TNF signaling pathway are the most important signaling pathways. Molecular docking experiments were used to further validate network pharmacology results. Conclusions: This study not only discovers CCMM and the molecular mechanism of TCM prescriptions for treating MI, but may be helpful for the popularization and application of TCM treatment.

scholarly journals Discussion on the Mechanism of Action of High-frequency Drugs for Treating Heart Failure Based on Network Pharmacology

2021 ◽  
Vol 5 (3) ◽  
Author(s):  
Feifei Lei ◽  
Mingjun Zhao ◽  
Haifang Wang ◽  
Chao Pan ◽  
Xiaoya Shi
Keyword(s):  
Heart Failure ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Salvia Miltiorrhiza ◽  
Network Pharmacology ◽  
Active Components ◽  
Radix Astragalus ◽  
Pharmacological Studies ◽  
Chinese Medicine Treatment

Objective: To explore the target and mechanism of Astragalus membranaceus, poria, salvia miltiorrhiza and semen leiocarpa in the treatment of heart failure by network pharmacology. Methods: The active components of traditional Chinese medicine and the target of heart failure were screened by multi-platform, and the standard gene was transformed by Uniprot. CytoCasp 3.6.1 was used to draw the network diagram of traditional Chinese medicine - component - target. Go and KEGG analysis were performed by Metascape. Results: A total of 36 predictive target sites of Radix Astragalus, Fuling poria, Salvia miltiorrhiza and Draba nemorosa were screened for treatment of heart failure, mainly involving nerve and factor pathways: ADRB2, ADRA1B and AChE. Cancer pathway: TP53, TNF; Pathways of inflammation: IL1B, PTSG2, PTSG1; Sex hormone pathway: ESR1, AR, PGR; Others: SCN5A, HIF1A, etc. The results of GO and KEGG enrichment suggested that the treatment of heart failure with the top four drugs involved cancer pathway, calcium signaling pathway, HIF-1 signaling pathway, and involved in blood circulation, cell proliferation and other processes. Conclusion: This study combines the pharmacological studies of Chinese medicine and western medicine to reveal the mechanism of multi-target and multi-channel regulation of body balance in Chinese medicine treatment.

scholarly journals Study on the Mechanism of Baimai Ointment in the Treatment of Osteoarthritis Based on Network Pharmacology and Molecular Docking with Experimental Verification

2021 ◽  
Vol 12 ◽  
Author(s):  
Yingyin Zhu ◽  
Wanling Zhong ◽  
Jing Peng ◽  
Huichao Wu ◽  
Shouying Du
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Animal Experiments ◽  
Tibetan Medicine ◽  
Blue Staining ◽  
Network Pharmacology ◽  
Enzyme Linked Immunosorbent Assay

Purpose: The external preparation of the Tibetan medicine formula, Baimai ointment (BMO), has great therapeutic effects on osteoarthritis (OA). However, its molecular mechanism remains almost elusive. Here, a comprehensive strategy combining network pharmacology and molecular docking with pharmacological experiments was adopted to reveal the molecular mechanism of BMO against OA.Methods: The traditional Chinese medicine for systems pharmacology (TCMSP) database and analysis platform, traditional Chinese medicine integrated database (TCMID), GeneCards database, and DisGeNET database were used to screen the active components and targets of BMO in treating OA. A component–target (C-T) network was built with the help of Cytoscape, and the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment through STRING. Autodock Tools which was used to dock the key components and key target proteins was analyzed. Animal experiments were performed to verify the key targets of BMO. Hematoxylin–eosin and toluidine blue staining were used to observe the pathology of joints. Protein expression was determined using enzyme-linked immunosorbent assay.Results: Bioactive compounds and targets of BMO and OA were screened. The network analysis revealed that 17-β-estradiol, curcumin, licochalone A, quercetin, and glycyrrhizic acid were the candidate key components, and IL6, tumor necrosis factor (TNF), MAPK1, VEGFA, CXCL8, and IL1B were the candidate key targets in treating OA. The KEGG indicated that the TNF signaling pathway, NF-κB signaling pathway, and HIF-1 signaling pathway were the potential pathways. Molecular docking implied a strong combination between key components and key targets. The pathology and animal experiments showed BMO had great effects on OA via regulating IL6, TNF, MAPK1, VEGFA, CXCL8, and IL1B targets. These findings were consistent with the results obtained from the network pharmacology approach.Conclusion: This study preliminarily illustrated the candidate key components, key targets, and potential pathways of BMO against OA. It also provided a promising method to study the Tibetan medicine formula or external preparations.

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