Material Basis and Mechanism of Chansu Injection for COVID-19 Treatment Based on Network Pharmacology and Molecular Docking Technology

10.21203/rs.3.rs-364843/v2 ◽

2021 ◽

Author(s):

Yong Xu ◽

Wenpan Peng ◽

Di Han ◽

Zhichao Wang ◽

Fanchao Feng ◽

...

Keyword(s):

Molecular Docking ◽

Mechanism Of Action ◽

Kegg Pathway ◽

Topological Analysis ◽

Binding Energies ◽

Network Pharmacology ◽

Active Constituent ◽

S Protein ◽

Pathway Enrichment ◽

Material Basis

Abstract Background: Coronavirus disease 2019 (COVID-19) is an emerging and rapidly evolving disease with no effective drug treatment. Traditional Chinese medicines have been widely used to treat COVID-19 in China. Chansu and its major active constituent, bufalin, exert broad-spectrum antiviral effects. Although the clinical efficacy of Chansu injection for COVID-19 treatment has been confirmed, its mechanism of action remains unclear. Objectives: In this study, we used network pharmacology and molecular docking technology to explore the potential material basis and mechanism of action of Chansu injection for COVID-19 treatment. Methods: The main components of Chansu injection were determined using high-performance liquid chromatography (HPLC). The PharmMapper, SwissTargetPrediction, SEA, and TCMID databases were used to screen for the active ingredients and therapeutic targets of Chansu injection while the OMIM and GeneCards Suite databases were used to search for COVID-19-related targets. The STRING database was used for protein–protein interaction (PPI) network construction and topological analysis while DAVID was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the core targets. Molecular docking of the three Chansu injection components (i.e., cinobufagin, resibufogenin, and bufalin) to angiotensin-converting enzyme II, spike (S) protein, 3CL protease, and RNA-dependent RNA polymerase was also carried out. Results: The three Chansu injection compounds were identified using HPLC. A total of 236 drug-related targets and 16,611 disease-related targets were identified, and 77 common targets were determined through mapping. The PPI mapping results revealed 16 core targets obtained through topological analysis and screening. Further, GO and KEGG pathway enrichment analyses revealed that the PI3K and JAK–STAT signaling pathways are the major pathways regulated by Chansu injection in COVID-19 treatment. The molecular docking results suggest that the three Chansu injection components have high binding energies to the S protein. Conclusions: This study revealed that the potential mechanism of Chansu injection for COVID-19 treatment involves multiple targets and pathways, thereby providing a scientific basis for its clinical application and further research.

Material Basis and Mechanism of Chansu Injection for COVID-19 Treatment Based on Network Pharmacology and Molecular Docking Technology

10.21203/rs.3.rs-364843/v1 ◽

2021 ◽

Author(s):

Yong Xu ◽

Wenpan Peng ◽

Di Han ◽

Zhichao Wang ◽

Cheng Gu ◽

...

Keyword(s):

Molecular Docking ◽

Mechanism Of Action ◽

Kegg Pathway ◽

Topological Analysis ◽

Binding Energies ◽

Network Pharmacology ◽

Active Constituent ◽

S Protein ◽

Pathway Enrichment ◽

Material Basis

Abstract Background: Coronavirus disease 2019 (COVID-19) is an emerging and rapidly evolving disease with no effective drug treatment. Traditional Chinese medicines have been widely used to treat COVID-19 in China. Chansu and its major active constituent, bufalin, exert broad-spectrum antiviral effects. Although the clinical efficacy of Chansu injection for COVID-19 treatment has been confirmed, its mechanism of action remains unclear. Objectives: In this study, we used network pharmacology and molecular docking technology to explore the potential material basis and mechanism of action of Chansu injection for COVID-19 treatment. Methods: The main components of Chansu injection were determined using high-performance liquid chromatography (HPLC). The PharmMapper, SwissTargetPrediction, SEA, and TCMID databases were used to screen for the active ingredients and therapeutic targets of Chansu injection while the OMIM and GeneCards Suite databases were used to search for COVID-19-related targets. The STRING database was used for protein–protein interaction (PPI) network construction and topological analysis while DAVID was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the core targets. Molecular docking of the three Chansu injection components (i.e., cinobufagin, resibufogenin, and bufalin) to angiotensin-converting enzyme II, spike (S) protein, 3CL protease, and RNA-dependent RNA polymerase was also carried out. Results: The three Chansu injection compounds were identified using HPLC. A total of 236 drug-related targets and 16,611 disease-related targets were identified, and 77 common targets were determined through mapping. The PPI mapping results revealed 16 core targets obtained through topological analysis and screening. Further, GO and KEGG pathway enrichment analyses revealed that the PI3K and JAK–STAT signaling pathways are the major pathways regulated by Chansu injection in COVID-19 treatment. The molecular docking results suggest that the three Chansu injection components have high binding energies to the S protein. Conclusions: This study revealed that the potential mechanism of Chansu injection for COVID-19 treatment involves multiple targets and pathways, thereby providing a scientific basis for its clinical application and further research.

Pharmacological Mechanisms of Tinglizi against Chronic Heart Failure Determined by Network Pharmacology and Molecular Docking

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2022/2152399 ◽

2022 ◽

Vol 2022 ◽

pp. 1-11

Author(s):

Liangtao Luo ◽

Haowen Wang ◽

Guowei Huang ◽

Lu Zhang ◽

Xiuwei Li ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathway ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Advanced Glycation ◽

Pathway Enrichment ◽

Material Basis ◽

Glycation End Products ◽

End Products

Objective. Tinglizi has been extensively used to treat chronic heart failure (CHF) in modern times, but the material basis and pharmacological mechanisms are still unclear. To explore the material basis and corresponding potential targets and to elucidate the mechanism of Tinglizi, network pharmacology and molecular docking methods were utilized. Methods. The main chemical compounds and potential targets of Tinglizi were collected from the pharmacological database analysis platform (TCMSP). The corresponding genes of related action targets were queried through gene cards and UniProt database. The corresponding genes of CHF-related targets were searched through Disgenet database, and the intersection targets were obtained by drawing Venn map with the target genes related to pharmacodynamic components. Then, drug targets and disease targets were intersected and put into STRING database to establish a protein interaction network. The “active ingredient-CHF target” network was constructed with Cytoscape 3.8.2. Finally, Gene Ontology (GO) Enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of intersection targets were analyzed using metascape. With the aid of SYBYL software, the key active ingredients and core targets were docked at molecular level, and the results were visualized by PyMOL software. Molecular docking was carried out to investigate interactions between active compounds and potential targets. Results. A total of 12 active components in Tinglizi were chosen from the TCMSP database, and 193 corresponding targets were predicted. Twenty-nine potential targets of Tinglizi on CHF were obtained, of which nine were the core targets of this study. Twenty GO items were obtained by GO function enrichment analysis ( P < 0.05 ), and 10 signal pathways were screened by KEGG pathway enrichment analysis ( P < 0.05 ), which is closely related to the treatment of CHF by Tinglizi. The constructed drug compound composition action target disease network shows that quercetin, kaempferol, and other active compounds play a key role in the whole network. The results of molecular docking showed that all the key active ingredients, such as quercetin and isorhamnetin, were able to successfully dock with ADRB2 and HMOX1 with a total score above 5.0, suggesting that these key components have a strong binding force with the targets. Conclusion. Through network pharmacology and molecular docking technology, we found that the main components of Tinglizi in the treatment of CHF are quercetin, kaempferol, β-sitosterol, isorhamnetin, and so on. The action targets are beta 2-adrenergic receptor (ADRB2), heme oxygenase 1 (HMOX1), and so on. The main pathways are advanced glycation end products/receptor for advanced glycation end products (AGE-RAGE) signaling pathway in diabetic complications, hypoxia-inducible factor (HIF-1) signaling pathway, estrogen signaling pathway, and so on. They play an integrated role in the treatment of CHF.

Molecular mechanism underlying the hypolipidemic effect of Shanmei Capsule based on network pharmacology and molecular docking

Technology and Health Care ◽

10.3233/thc-218023 ◽

2021 ◽

Vol 29 ◽

pp. 239-256

Author(s):

Qian Wang ◽

Lijing Du ◽

Jiana Hong ◽

Zhenlin Chen ◽

Huijian Liu ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathway ◽

Molecular Mechanism ◽

Kegg Pathway ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Signal Pathways ◽

Hypolipidemic Effect ◽

Active Ingredients ◽

Pathway Enrichment

BACKGROUND: Shanmei Capsule is a famous preparation in China. However, the related mechanism of Shanmei Capsule against hyperlipidemia has yet to be revealed. OBJECTIVE: To elucidate underlying mechanism of Shanmei Capsule against hyperlipidemia through network pharmacology approach and molecular docking. METHODS: Active ingredients, targets of Shanmei Capsule as well as targets for hyperlipidemia were screened based on database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed via Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 database. Ingredient-target-disease-pathway network was visualized utilizing Cytoscape software and molecular docking was performed by Autodock Vina. RESULTS: Seventeen active ingredients in Shanmei Capsule were screened out with a closely connection with 34 hyperlipidemia-related targets. GO analysis revealed 40 biological processes, 5 cellular components and 29 molecular functions. A total of 15 signal pathways were enriched by KEGG pathway enrichment analysis. The docking results indicated that the binding activities of key ingredients for PPAR-α are equivalent to that of the positive drug lifibrate. CONCLUSIONS: The possible molecular mechanism mainly involved PPAR signaling pathway, Bile secretion and TNF signaling pathway via acting on MAPK8, PPARγ, MMP9, PPARα, FABP4 and NOS2 targets.

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

10.21203/rs.3.rs-699020/v1 ◽

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.

Investigating the Mechanism of Action of Frankincense against Drug-Induced Liver Injury Using Network Pharmacology and Molecular Docking

Letters in Drug Design & Discovery ◽

10.2174/1570180818666210319160217 ◽

2021 ◽

Vol 18 ◽

Author(s):

Yu-cheng Liao ◽

Jing-wen Wang ◽

Qian Yang ◽

Wen-jun Wanga ◽

Chao Zhao ◽

...

Keyword(s):

Molecular Docking ◽

Liver Injury ◽

Mechanism Of Action ◽

Target Genes ◽

Network Pharmacology ◽

Active Components ◽

Drug Induced ◽

Drug Induced Liver Injury ◽

Pathway Enrichment ◽

Core Genes

Background: Frankincense has been used as a traditional medicine in many countries. It is an important herb with multiple targets and therapeutic effects including liver protection. However, its mechanism of action in drug-induced liver injury (DILI) remains unknown. Objective: The purpose of this work was to elucidate the active components, core genes, and molecular mechanism of frankincense in DILI through network pharmacology and molecular docking approaches. Method: The active components of frankincense and its target genes were obtained from the BATMAN-TCM database, and the DILI target genes were obtained from the GeneCards and DrugBank databases. Cytoscape was used to create the compound-shared gene target network. STRING and DAVID software were used to analyze key targets and pathway enrichment. Autodock Vina software was used for molecular docking. Results: Network analysis identified 16 compounds in frankincense and 103 target genes that are highly related to DILI. The core genes in the protein-protein interaction network are INS, IL6, TP53, TNF, SRC, PTGS2, IL1B, CAT, IL10, and IGF1. Furthermore, GO and KEGG pathway enrichment analyses indicated that the effect of frankincense on DILI is related to positive regulation of transcription from RNA polymerase II promoter and inflammatory response. Core pathways such as the HIF-1, TNF, FoxO, PI3K-Akt, and the sphingolipid signaling pathway are closely related to DILI. Conclusion: This study revealed the chemical constituents and pharmacological effects of frankincense and unveiled potential DILI healing targets. This study could provide insights for further development of drugs that specifically target DILI.

Network pharmacology and molecular docking analysis on mechanisms of Tibetan Hongjingtian (Rhodiola crenulata) in the treatment of COVID-19

Journal of Medical Microbiology ◽

10.1099/jmm.0.001374 ◽

2021 ◽

Vol 70 (7) ◽

Author(s):

Li Wang ◽

Yuhe Wang ◽

Wei Yang ◽

Xue He ◽

Shilin Xu ◽

...

Keyword(s):

Molecular Docking ◽

Kegg Pathway ◽

Signalling Pathway ◽

Network Pharmacology ◽

Cytokine Storm ◽

Ppi Network ◽

Pathway Network ◽

Pathway Enrichment ◽

Tnf Α ◽

Rhodiola Crenulata

Introduction. Coronavirus disease 2019 (COVID-19) is a highly contagious disease and ravages the world. Hypothesis/Gap Statement. We proposed that R. crenulata might have potential value in the treatment of COVID-19 patients by regulating the immune response and inhibiting cytokine storm. Aim. We aimed to explore the potential molecular mechanism for Rhodiola crenulata (R. crenulata), against the immune regulation of COVID-19, and to provide a referenced candidate Tibetan herb (R. crenulata) to overcome COVID-19. Methodology. Components and targets of R. crenulata were retrieved from the TCMSP database. GO analysis and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were built by R bioconductor package to explore the potential biological effects for targets of R. crenulata. The R. crenulata-compound-target network, target pathway network and protein–protein interaction (PPI) network were constructed using Cytoscape 3.3.0. Autodock 4.2 and Discovery Studio software were applied for molecular docking. Result. Four bioactive components (quercetin, kaempferol, kaempferol-3-O-α-l-rhamnoside and tamarixetin) and 159 potential targets of R. crenulata were identified from the TCMSP database. The result of GO annotation and KEGG-pathway-enrichment analyses showed that target genes of R. crenulata were associated with inflammatory response and immune-related signalling pathways, especially IL-17 signalling pathway, and TNF signalling pathway. Targets-pathway network and PPI network showed that IL-6, IL-1B and TNF-α were considered to be hub genes. Molecular docking showed that core compound (quercetin) had a certain affinity with IL-1β, IL-6 and TNF-α. Conclusion. R. crenulata might play an anti-inflammatory and immunoregulatory role in the cytokine storm of COVID-19.

Integrating Network Pharmacology and Experimental Validation Deciphers the Mechanism of Guizhi Fuling Wan against Adenomyosis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6034147 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Haoxian Wang ◽

Jihong Zhang ◽

Qinqin Zhu ◽

Xianyun Fu ◽

Chenjie Li

Keyword(s):

Molecular Docking ◽

Signaling Pathway ◽

Kegg Pathway ◽

Animal Experiments ◽

Enrichment Analysis ◽

Estrogen Signaling ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Verification Methods

Aim. This study aimed to predict the key targets and endocrine mechanisms of Guizhi Fuling Wan (GZFLW) in treating adenomyosis (AM) through network pharmacology, molecular docking, and animal experiment verification. Methods. The related ingredients and targets of GZFLW in treating AM were screened out using TCMSP, BATMAN-TCM, SwissTargetPrediction, and PubChem Database. Then, the protein-protein interaction (PPI) analysis and the network of compound-hub targets were constructed. At the same time, the key targets were uploaded to the Metascape Database for KEGG pathway enrichment analysis. After that, the molecular docking technology of the main active components and hub targets was performed. Furthermore, animal experiments were used to verify the results of network pharmacology analysis. Results. A total of 55 active ingredients of GZFLW and 44 overlapping targets of GZFLW in treating AM were obtained. After screening, 25 hub targets were collected, including ESR1, EGF, and EGFR. Then, the KEGG pathway enrichment analysis results indicated that the endocrine therapeutic mechanism of GZFLW against AM is mainly associated with the estrogen signaling pathway, endocrine resistance, and an EGFR tyrosine kinase signaling pathway. Then, molecular docking showed that the significant compounds of GZFLW had a strong binding ability with ERα and EGFR. More importantly, the animal experiments confirmed that the GZFLW could downregulate the abnormal infiltration of the endometrial epithelium into the myometrium and had no interference with the normal sexual cycle. This effect may be directly related to intervening the local estrogen signaling pathway of the endometrial myometrial interface (EMI). It may also be associated with the myometrium cells’ estrogen resistance via GPER/EGFR signaling pathway. Conclusion. The endocrine mechanism of GZFLW in treating AM was explored based on network pharmacology, molecular docking, and animal experiments, which provided a theoretical basis for the clinical application of GZFLW.

Analysis of the Active Components and Mechanism of Three Prescriptions in the Treatment of COVID-19 Via Network Pharmacology and Molecular Docking

Natural Product Communications ◽

10.1177/1934578x211047702 ◽

2021 ◽

Vol 16 (9) ◽

pp. 1934578X2110477

Author(s):

Fei Wang ◽

Jia-Hui Chen ◽

Bo Liu ◽

Ting Zhang

Keyword(s):

Molecular Docking ◽

Binding Energies ◽

Network Pharmacology ◽

Active Components ◽

Chinese Medicines ◽

Protein Protein Interaction ◽

Kegg Pathways ◽

Ppi Networks ◽

Infection And Inflammation ◽

Analysis Platform

Purpose: Prescriptions of Han-Shi-Yu-Fei (HSYF), Han-Shi-Zu-Fei (HSZF), and Yi-Du-Bi-Fei (YDBF) were effective in treating COVID-19. Based on network pharmacology and molecular docking, overlapping Traditional Chinese medicines (TCMs), their active components, and core targets were explored in this study. Methods: First, the overlapping TCMs and their active components were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) by evaluating Oral Bioactivity (OB) and Drug Likeness (DL). The overlapping targets of potential components and COVID-19 were collected by SwissTargetPrediction, Gene Cards, and Venn 2.1.0 databases. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were analyzed via DAVID6.8.1 database. Through comprehensive analysis of the “prescriptions-TCMs-components” (P-T-C), “components-targets-pathways” (C-T-P) and “protein–protein interaction” (PPI) networks constructed by Cytoscape 3.7.1 software, the active components and core targets were obtained. Finally, the binding energies of these components with ACE2 and SARS-CoV-2 3CL were analyzed by AutDockTools-1.5.6 and PyMOL software. Results: In all, five overlapping TCMs, 40 potential active components, and 47 candidate targets were obtained and analyzed in these prescriptions. There were 288 GO entries ( P < 0.05), including 211 biological process (BP), 40 cell composition (CC), and 37 molecular function (MF) entries. Most of the 105 KEGG pathways ( P < 0.05) were involved with viral infection and inflammation. Through “PPI” and “C-T-P” networks, the core targets (EGFR, PTGS2, CDK2, GSK3B, PIK3R1, and MAPK3) and active components (Q27134551, acanthoside B, neohesperidin, and irisolidone) with high degrees were obtained. Molecular docking results showed that the above-mentioned four components could inhibit the binding of ACE2 and SARS-COV-2 3CL to protect against COVID-19. Conclusion: In this study, the active components and core targets of three prescriptions in the treatment of COVID-19 were elaborated by network pharmacology and molecular docking, providing a reference for their applications.

Mechanism of Peony and Licorice and Aconite Decoction in the Treatment of Osteoarthritis Based on Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-1057016/v1 ◽

2021 ◽

Author(s):

Zhiqiang li ◽

Luo Jun

Keyword(s):

Molecular Docking ◽

Chinese Medicine ◽

Protein Interaction ◽

Active Component ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Biological Processes ◽

Pathway Enrichment

Abstract Objective: To predict the key molecular mechanism of Shaoyao Liquorice Aconite Decoction in the treatment of osteoarthritis by using network pharmacology and molecular docking technology, and to provide a new target for the treatment of osteoarthritis. Methods: by means of traditional Chinese medicine database TCMSP screening peony licorice monkshood soup main active component of radix paeoniae alba, radix glycyrrhizae, and the corresponding targets, lateral root of aconite and retrieve OMIM, GeneCards, TDD, PharmGKB and Drugbank database related target for treatment of osteoarthritis, and then forecast drug targets and disease targets for intersection get peony licorice monkshood soup targets for the treatment of osteoarthritis.Then, STRING database and Cytoscape software were used to construct the "drug active component - action target" network and protein interaction network of Shaoyaogaofuzi Decoction in the treatment of osteoarthritis, and David database was used for GO function enrichment analysis and KEGG pathway enrichment analysis of shaoyaogaofuzi Decoction in the treatment of osteoarthritis.Finally, PyMOL, Chem3D, AutoDock, OpenBabel and other software were used to verify the molecular docking of the key active ingredients and key targets of Shaoyao Liquorice Aconite Decoction. Results: 162 active components were screened out.A total of 954 disease targets were collected, and a total of 72 disease targets were obtained after weight removal.Protein interaction analysis suggested that TNF, AKT1, IL6, IL1B and TP53 were the core targets of protein interaction network.Through GO enrichment analysis, 393 biological processes were obtained, and it was found that biological processes were mainly enriched in cell differentiation, migration, apoptosis, and cell stress response to organisms.A total of 116 Pathways were obtained through KEGG pathway enrichment analysis, mainly involving Pathways in cancer, TNF Signaling Pathway, Tuberculosis, Chagas disease, Hepatitis B, etc. Finally, the molecular docking of key active molecules and key targets was realized for verification.Conclusions: this study of compound Chinese medicine pharmacology, through the network of peony licorice monkshood soup ingredients with osteoarthritis, targets, pathway analysis, you can see that drugs in the treatment of osteoarthritis is not a simple single targeted therapy, but by many components, multi-channel, mutual communications between the multiple targets, on the treatment of osteoarthritis in the future to provide more advice.