scholarly journals Predicting the levels of orcinol glucoside during the treatment of osteoporosis by network pharmacology and molecular docking

2020 ◽  
Author(s):  
xia liu ◽  
Mingchun Huang ◽  
Chen Yang ◽  
Qin Wang ◽  
Mei Zhang
Keyword(s):  
Molecular Docking ◽  
Topological Analysis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Active Constituent ◽  
Treatment Of Osteoporosis ◽  
Similarity Ensemble Approach ◽  
The Common

Abstract Introduction: As a traditional Chinese medicine (TCM), Curculigo orchioides Gaertn. (Xianmao) has been widely used to treat bone-related diseases. However, the active components of this TCM, and the specific mechanisms by which it exerts effect, have yet to be elucidated. To identify potential targets for orcinol glucoside (OG), an active constituent of C. orchioides, during the treatment of osteoporosis (OP) by adopting a network pharmacology approach. Methods: First, we mined the Similarity ensemble approach (SEA), SwissTargetPrediction, DisGeNET, and Genecards databases were mined for data related to the prediction of OG- and OP-related targets. Next, we identified the common targets for OG and OP, and then used STRING software to create a protein-protein interaction (PPI) network. Then, we used topological analysis to identify which of the common targets were most significant. Then, we used the common significant targets and g:profiler to perform gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes ( KEGG) pathway enrichment analysis. Finally, we used molecular docking to predict the targets of OG that were most relevant to the treatment of OP and investigated the potential pharmacological mechanisms that might be involved. Results: In total, 130 potential targets of OG, and 4582 targets relevant to OP, were subjected to network analysis. There were 73 common targets; these identified the principal pathways linked to OP. In addition, topological analysis identified 14 key targets. Most of the predicted targets played crucial roles in the PI3K-AKT signaling pathway. Molecular docking identified ten core targets (VEGFA, IL6, EGFR, MAPK1, HRAS, CCND1, FGF2, IL2, MCL1 and CDK4), thus indicating that OG may promote osteoblast proliferation and differentiation by accelerating progression of the cell cycle.Conclusions: This research provides a theoretical base for identifying the specific potential mechanisms of OG in treatment of OP.

scholarly journals Exploring the Pharmacological Mechanism of Duhuo Jisheng Decoction in Treating Osteoporosis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhencheng Xiong ◽  
Can Zheng ◽  
Yanan Chang ◽  
Kuankuan Liu ◽  
Li Shu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds ◽  
Treatment Of Osteoporosis ◽  
Target Proteins

Objective. The purpose of this work is to study the mechanism of action of Duhuo Jisheng Decoction (DHJSD) in the treatment of osteoporosis based on the methods of bioinformatics and network pharmacology. Methods. In this study, the active compounds of each medicinal ingredient of DHJSD and their corresponding targets were obtained from TCMSP database. Osteoporosis was treated as search query in GeneCards, MalaCards, DisGeNET, Therapeutic Target Database (TTD), Comparative Toxicogenomics Database (CTD), and OMIM databases to obtain disease-related genes. The overlapping targets of DHJSD and osteoporosis were identified, and then GO and KEGG enrichment analysis were performed. Cytoscape was employed to construct DHJSD-compounds-target genes-osteoporosis network and protein-protein interaction (PPI) network. CytoHubba was utilized to select the hub genes. The activities of binding of hub genes and key components were confirmed by molecular docking. Results. 174 active compounds and their 205 related potential targets were identified in DHJSD for the treatment of osteoporosis, including 10 hub genes (AKT1, ALB, IL6, MAPK3, VEGFA, JUN, CASP3, EGFR, MYC, and EGF). Pathway enrichment analysis of target proteins indicated that osteoclast differentiation, AGE-RAGE signaling pathway in diabetic complications, Wnt signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, calcium signaling pathway, and TNF signaling pathway were the specifically major pathways regulated by DHJSD against osteoporosis. Further verification based on molecular docking results showed that the small molecule compounds (Quercetin, Kaempferol, Beta-sitosterol, Beta-carotene, and Formononetin) contained in DHJSD generally have excellent binding affinity to the macromolecular target proteins encoded by the top 10 genes. Conclusion. This study reveals the characteristics of multi-component, multi-target, and multi-pathway of DHJSD against osteoporosis and provides novel insights for verifying the mechanism of DHJSD in the treatment of osteoporosis.

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.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals The Mechanism of Huanglian Wendan Decotion Against Metabolic Syndrome

2020 ◽  
Author(s):  
Junli Bao ◽  
Xinyuan Gao ◽  
Yubo Han ◽  
Ke Zhang ◽  
Li Liu
Keyword(s):  
Metabolic Syndrome ◽  
Molecular Docking ◽  
Cellular Response ◽  
Enrichment Analysis ◽  
Docking Studies ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Core Network ◽  
Active Components ◽  
R Program

Abstract Background: Metabolic syndrome (MetS) is a group of abnormalities which includes abdominal obesity, hypertension, insulin resistance, and dyslipidemia. Many clinical studies showed that Huanglian Wendan Decoction(HWD) is effective in the treatment of MetS.Methods: In this study, the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, STITCH database and Swisstargetpredicition database were used to excavate the active components of HWD and to predict the potential targets. The key targets of MetS are screened through GeneCards database and DisGeNET database. Moreover, we obtained the overlapping target of HWD and MetS based on venndiagram of "R program". Next, we performed enrichment analysis for common-target network and protein-protein interaction (PPI) network. Afterwards, Cytoscape was used to construct the components-targets core network for HWD in treating MetS, and R program was used to perform GO-BP and KEGG pathway enrichment analysis on these core targets. Last, we further investigated our predictions of crucial targets by performing molecular docking studies with components of HWD.Results: The component-target core network of HWD against MetS was screened to contain 22 active components, which corresponded to 77 core targets. Additionally, enrichment analysis suggested that targets of HWD against MetS were mainly clustered into multiple biological processes (response to nutrient levels, gland development, response to steroid hormone, cellular response to oxidative stress, reproductive structure development etc and related pathways (AGE-RAGE, AMPK, JAK-STAT, MAPK), indicating the underlying mechanisms of HWD on MetS. The results of molecular docking showed that beta-sitost, naringenin, berberine and baicalein bound well to IL6 and AKT1.Conclusion: The network pharmacological strategy integrated molecular docking to explore the mechanism of HWD against MetS. Our present outcomes might shed light on the further clinical application of HWD on MetS treatment.

scholarly journals Predicting the Molecular Mechanism of Shenling Baizhu San in Treating Convalescent Patients With COVID-19 Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (10) ◽  
pp. 1934578X2110460
Author(s):  
Ying Zhang ◽  
Li Lu ◽  
YiWen Liu ◽  
AiXia Yang ◽  
Yanfang Yang
Keyword(s):  
Molecular Docking ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Binding Energies ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interactions ◽  
Active Ingredients ◽  
Active Components ◽  
Pathway Network

Objective: Shenling Baizhu San (SBS) was selected as the regimen for the treatment of COVID-19 in Guangdong Province. It is mainly used for the convalescent treatment of COVID-19 patients with deficiency of both lung and spleen. In this study, we aimed to explore the mechanism of SBS in the treatment of COVID-19 through network pharmacology combined with molecular docking. Methods: The targets of active components of SBS were collected through Traditional Chinese Medicine Systems Pharmacology (TCMSP) and ETCM databases. Using the Genecards, TTD, OMIM and other databases, the targets of COVID-19 were determined. The next step was to use a string database to build a protein–protein interactions (PPI) network between proteins, and use David database to perform gene ontology (GO) function enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct the active ingredients-core target-signaling pathway network, and finally the active ingredients of SBS were molecularly docked with the core targets to predict the mechanism of SBS in the treatment of COVID-19. Results: A total of 177 active compounds, 43 core targets and 58 signaling pathways were selected. Molecular docking results showed that the binding energies of the top six active components and the targets were all less than −5 kcal/MOL. Conclusion: The potential mechanism of action of SBS in the treatment of COVID-19 may be associated with the regulation of genes co-expressed with IL6, DPP4, PTGS2, PTGS1 and TNF.

scholarly journals A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Tiancheng Ma ◽  
Yu Sun ◽  
Chang Jiang ◽  
Weilin Xiong ◽  
Tingxu Yan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Protein Interactions ◽  
Kegg Pathway ◽  
Endocrine System ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Antidepressant Effect ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Pathway Network

Objective. The purpose of our research is to systematically explore the multiple mechanisms of Hemerocallis fulva Flowers (HF) on depressive disorder (DD). Methods. The components of HF were searched from the literature. The targets of components were obtained from PharmMapper. After that, Cytoscape software was used to build a component-target network. The targets of DD were collected from DisGeNET, PharmGKB, TTD, and OMIM. Protein-protein interactions (PPIs) among the DD targets were executed to screen the key targets. Afterward, the GO and KEGG pathway enrichment analysis were performed by the KOBAS database. A compound-target-KEGG pathway network was built to analyze the key compounds and targets. Finally, the potential active substances and targets were validated by molecular docking. Results. A total of 55 active compounds in HF, 646 compound-related targets, and 527 DD-related targets were identified from public databases. After treated with PPI, 219 key targets of DD were acquired. The gene enrichment analysis suggested that HF probably benefits DD patients by modulating pathways related to the nervous system, endocrine system, amino acid metabolism, and signal transduction. The network analysis showed the critical components and targets of HF on DD. Results of molecular docking increased the reliability of this study. Conclusions. It predicted and verified the pharmacological and molecular mechanism of HF against DD from a holistic perspective, which will also lay a foundation for further experimental research and rational clinical application of DD.

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.

Discussing the Mechanism of Dahuang Huanglian Xiexin Decoction in the Treatment of Type 2 Diabetes Mellitus via Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xi Cen ◽  
Yan Wang ◽  
LeiLei Zhang ◽  
XiaoXiao Xue ◽  
Yan Wang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Potential Mechanism ◽  
Active Components ◽  
The Core ◽  
Core Genes

Abstract BackgroundType 2 diabetes mellitus (T2DM) is regarded as Pi Dan disease in traditional Chinese medicine (TCM). Dahuang Huanglian Xiexin Decoction (DHXD), a classical TCM formula, has been used for treating Pi Dan disease in clinic, its pharmacological mechanism has not been elucidated. MethodsThis study used network pharmacological analysis and molecular docking approach to explore the mechanism of DHXD on T2DM. Firstly, the compounds in DHXD were obtained from TCMSP and TCMID databases, the potential targets were determined based on TCMSP and UniProt databases. Next, Genecards, Digenet and UniProt databases were used to identify the targets of T2DM. Then, the protein-protein interaction (PPI) network was established with overlapping genes of T2DM and compounds, and the core targets in the network were identified and analyzed. Then, the David database was used for GO and KEGG enrichment analysis. Finally, the target genes were selected and the molecular docking was completed by Autodock software to observe the binding level of active components with target genes.ResultsA total of 397 related components and 128 overlapping genes were identified. After enrichment analysis, it was found that HIF-1, TNF, IL-17 and other signaling pathways, as well as DNA transcription, gene expression, apoptosis and other cellular biological processes had the strongest correlation with the treatment of T2DM by DHXD, and most of them occurred in the extracellular space, plasma membrane and other places, which were related to enzyme binding and protein binding. In addition, 42 core genes of DHXD, such as VEGFA, TP53 and MAPK1, were considered as potential therapeutic targets, indicating the potential mechanism of DHXD on T2DM. Finally, the results of molecular docking showed that HIF-1 pathway had strong correlation with the target genes INSR and GLUT4, quercetin and berberine had the strongest binding power with them respectively.ConclusionThis study summarized the main components of DHXD in the treatment of T2DM, identified the core genes and pathways, and systematically analyzed the interaction of related targets, trying to lay the foundation for clarifying the potential mechanism of DHXD on T2DM, so as to carry out further research in the future.

scholarly journals Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Mengshi Tang ◽  
Xi Xie ◽  
Pengji Yi ◽  
Jin Kang ◽  
Jiafen Liao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Binding Activity ◽  
New Combination ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

scholarly journals Ganghuo Kanggan Decoction in Influenza: Integrating Network Pharmacology and In Vivo Pharmacological Evaluation

2020 ◽  
Vol 11 ◽  
Author(s):  
Yanni Lai ◽  
Qiong Zhang ◽  
Haishan Long ◽  
Tiantian Han ◽  
Geng Li ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Influenza A ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
New Drugs ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Compound Screening

Background: Ganghuo Kanggan decoction (GHKGD) is a clinical experience prescription used for the treatment of viral pneumonia in the Lingnan area of China, and its clinical effect is remarkable. However, the mechanism of GHKGD in influenza is still unclear.Objective: To predict the active components and signaling pathway of GHKGD and to explore its therapeutic mechanism in influenza and to verified it in vivo using network pharmacology.Methods: The potential active components and therapeutic targets of GHKGD in the treatment of influenza were hypothesized through a series of network pharmacological strategies, including compound screening, target prediction and pathway enrichment analysis. Based on the target network and enrichment results, a mouse model of influenza A virus (IAV) infection was established to evaluate the therapeutic effect of GHKGD on influenza and to verify the possible molecular mechanism predicted by network pharmacology.Results: A total of 116 candidate active compounds and 17 potential targets were identified. The results of the potential target enrichment analysis suggested GHKGD may involve the RLR signaling pathway to reduce inflammation in the lungs. In vivo experiments showed that GHKGD had a protective effect on pneumonia caused by IAV-infected mice. Compared with the untreated group, the weight loss in the GHKGD group in the BALB/c mice decreased, and the inflammatory pathological changes in lung tissue were reduced (p < 0.05). The expression of NP protein and the virus titers in lung were significantly decreased (p < 0.05). The protein expression of RIG-I, NF-kB, and STAT1 and the level of MAVS and IRF3/7 mRNA were remarkably inhibited in GHKGD group (p < 0.05). After the treatment with GHKGD, the level of Th1 cytokines (IFN-γ, TNF-α, IL-2) was increased, while the expression of Th2 (IL-5, IL4) cytokines was reduced (p < 0.05).Conclusion: Through a network pharmacology strategy and in vivo experiments, the multi-target and multi-component pharmacological characteristics of GHKGD in the treatment of influenza were revealed, and regulation of the RLR signaling pathway during the anti-influenza process was confirmed. This study provides a theoretical basis for the research and development of new drugs from GHKGD.

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