scholarly journals A Network Pharmacology Approach to Explore the Potential Mechanisms of Yifei Sanjie Formula in Treating Pulmonary Fibrosis

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Bo Qiao ◽  
Yueying Wu ◽  
Xiaoya Li ◽  
Zhenyuan Xu ◽  
Weigang Duan ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Cell Receptor ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Kegg Pathways ◽  
Th17 Cell Differentiation ◽  
Associated Proteins ◽  
Cellular Components

Objective. Yifei Sanjie Formula (YFSJF) is an effective formula on pulmonary fibrosis (PF), which has been used in clinic for more than 30 years. In order to investigate the molecular mechanism of YFSJF in treating PF, network pharmacology was used to predict the cooperative ingredients and associated pathways. Methods. Firstly, we collected potential active ingredients of YFSJF by TCMSP databases. Secondly, we obtained PF-associated targets through OMIM and Genecards database. Finally, metascape was applied for the analysis of GO terms and KEGG pathways. Results. We screened out 76 potential active ingredients and 98 associated proteins. A total of 5715 items were obtained by GO enrichment analysis ( P < 0.05 ), including 4632 biological processes, 444 cellular components, and 639 molecular functions. A total of 143 related KEGG pathways were enriched ( P < 0.05 ), including IL-17 signaling pathway, T cell receptor signaling pathway, TNF signaling pathway, calcium signaling pathway, TH17 cell differentiation, HIF-1 signaling pathway, and PI3K-Akt signaling pathway. Conclusion. YFSJF can interfere with immune and inflammatory response through multiple targets and pathways, which has a certain role in the treatment of PF. This study lays a foundation for future experimental research.

scholarly journals Exploration of the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology and molecular docking

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Postmenopausal Osteoporosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Core Proteins ◽  
Key Genes

Abstract Background: Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease, which poses huge challenges to individuals and society. Ziyin Tongluo Formula (ZYTLF) has been proved effective in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP have not been thoroughly elucidated.Methods: Online databases were used to identify the active ingredients of ZYTLF and corresponding putative targets. Genes associated with PMOP were mined, and then mapped with the putative targets to obtain overlapping genes. Multiple networks were constructed and analyzed, from which the key genes were selected. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analysis. Finally, AutoDock Tools and other software were used for molecular docking of core compounds and key proteins. Results: Ninety-two active compounds of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. Network analysis showed the top 5 active ingredients including quercetin, kaempferol, luteolin, scutellarein, and formononetin., and the top 50 key genes such as VEGFA, MAPK8, AKT1, TNF, ESR1. Enrichment analysis uncovered two significant types of KEGG pathways in PMOP, hormone-related signaling pathways (estrogen , prolactin, and thyroid hormone signaling pathway) and inflammation-related pathways (TNF, PI3K-Akt, and MAPK signaling pathway). Moreover, molecular docking analysis verified that the main active compounds were tightly bound to the core proteins, further confirming the anti-PMOP effects. Conclusions: Based on network pharmacology and molecular docking technology, this study initially revealed the mechanisms of ZYTLF on PMOP, which involves multiple targets and multiple pathways.

scholarly journals Network Pharmacology-Based Strategy for Predicting Therapy Targets of Tripterygium wilfordii on Acute Myeloid Leukemia

2020 ◽  
Author(s):  
Tingting Fang ◽  
Lanqin Liu ◽  
wenjun liu
Keyword(s):  
Acute Myeloid Leukemia ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Myeloid Leukemia ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Tripterygium Wilfordii ◽  
Active Ingredients ◽  
Acute Myeloid

Abstract Background. Acute myeloid leukemia (AML) is a common malignant tumor of the hematopoietic system. How to extend the survival time of AML patients and improve their prognosis is still a major medical problem. Chinese medicine has a long history in treating AML. Tripterygium wilfordii (TW) is a traditional Chinese medicine. With the deepening of pharmacological research of traditional Chinese medicine, triptolide, one of its active ingredients, has been proven to have a positive effect on the treatment of AML. Therefore，this study aimed on studying the potential therapeutic targets and pharmacological mechanism of TW in Acute myeloid leukemia (AML) based on network pharmacology.Methods. The active components of TW were obtained by network pharmacology through oral bioavailability, drug-likeness filtration. Comparative analysis was used to study the overlapping genes between active ingredient’s targets and AML treatment-related targets. Using STRING database to analyze interactions between overlapping genes. KEGG pathway analysis and Gene Ontology enrichment analysis were conducted in DAVID. These genes were analyzed for survival in OncoLnc database.Key findings. We screened 53 active ingredients, the results of comparative analysis showed that 8 active ingredients had an effect on AML treatment. Based on the active ingredients and overlapping genes, we constructed the Drug-Compounds-Genes-Disease Network. Survival analysis of overlapping genes indicated that some targets possess a significant influence on patients’ survival and prognosis. The enrichment analysis showed that the main pathways of targets are Toll-like receptor signaling pathway, NF-kappa B signaling pathway and HIF-1 signaling pathway.Conclusion. This study, using a network pharmacologic approach, provides another strategy that can help us to understand the mechanisms by which TW treats AML comprehensively.

scholarly journals Mechanism of Fei-Xian Formula in the Treatment of Pulmonary Fibrosis on the Basis of Network Pharmacology Analysis Combined with Molecular Docking Validation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiao-Li Chen ◽  
Cheng Tang ◽  
Qing-Ling Xiao ◽  
Zhong-Hua Pang ◽  
Dan-Dan Zhou ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virus Infection ◽  
Pulmonary Fibrosis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Molecular Docking Study ◽  
The Core ◽  
Target Network

Objective. This study aimed to clarify the mechanism of Fei-Xian formula (FXF) in the treatment of pulmonary fibrosis based on network pharmacology analysis combined with molecular docking validation. Methods. Firstly, ingredients in FXF with pharmacological activities, together with specific targets, were identified based on the BATMA-TCM and TCMSP databases. Then, targets associated with pulmonary fibrosis, which included pathogenic targets as well as those known therapeutic targets, were screened against the CTD, TTD, GeneCards, and DisGeNet databases. Later, Cytoscape was employed to construct a candidate component-target network of FXF for treating pulmonary fibrosis. In addition, for nodes within the as-constructed network, topological parameters were calculated using CytoHubba plug-in, and the degree value (twice as high as the median degree value for all the nodes) was adopted to select core components as well as core targets of FXF for treating pulmonary fibrosis, which were subsequently utilized for constructing the core network. Furthermore, molecular docking study was carried out on those core active ingredients together with the core targets using AutoDock Vina for verifying results of network pharmacology analysis. At last, OmicShare was employed for enrichment analysis of the core targets. Results. Altogether 12 active ingredients along with 13 core targets were identified from our constructed core component-target network of FXF for the treatment of pulmonary fibrosis. As revealed by enrichment analysis, the 13 core targets mostly concentrated in regulating biological functions, like response to external stimulus (from oxidative stress, radiation, UV, chemical substances, and virus infection), apoptosis, cell cycle, aging, immune process, and protein metabolism. In addition, several pathways, like IL-17, AGE-RAGE, TNF, HIF-1, PI3K-AKT, NOD-like receptor, T/B cell receptor, and virus infection-related pathways, exerted vital parts in FXF in the treatment of pulmonary fibrosis. Conclusions. FXF can treat pulmonary fibrosis through a “multicomponent, multitarget, and multipathway” mean. Findings in this work lay foundation for further exploration of the FXF mechanism in the treatment of pulmonary fibrosis.

scholarly journals A Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Chunli Piao ◽  
Qi Zhang ◽  
De Jin ◽  
Li Wang ◽  
Cheng Tang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Systems Pharmacology ◽  
Active Components ◽  
Kegg Pathways

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.

scholarly journals Network Pharmacology Analysis on the Mechanism of Huangqi Sijunzi Decoction in Treating Cancer-Related Fatigue

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yixin Cui ◽  
Haiming Wang ◽  
Decai Wang ◽  
Jiwei Mi ◽  
Gege Chen ◽  
...  
Keyword(s):  
Topological Analysis ◽  
Enrichment Analysis ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Cancer Related Fatigue ◽  
Tumor Gene Expression

Objective. This study aimed to determine the active ingredients of Huangqi Sijunzi Decoction (HQSJZD) and the targets in treating cancer-related fatigue (CRF) so as to investigate the treatment mechanism of HQSJZD for CRF. Methods. This study adopted the method of network pharmacology. The active ingredients and targets of HQSJZD were retrieved, and the targets of HQSJZD in treating CRF were obtained using a Venn diagram. Next, a protein-protein interaction (PPI) network was constructed using the String database. The core targets of HQSJZD in treating CRF were identified through topological analysis, and functional annotation analysis and pathway enrichment analysis were carried out. Subsequently, a compound-disease-target regulatory network was constructed using Cystoscape 3.8.0 software. Results. A total of 250 targets of HQSJZD ingredients, 1447 CRF-related genes, and 144 common targets were obtained. Through topological analysis, 61 core targets were screened. Bioinformatics annotation of these genes identified 2366 gene ontology (GO) terms and 172 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Conclusion. The active ingredients in HQSJZD, that is, quercetin, luteolin, kaempferol, and naringenin, may act on AKT1, IL-6, VEGFA, MAPK3, CASP3, JUN, and EGFR to regulate the PI3K-Akt, TNF, and IL-17 signaling pathways, thereby suppressing inflammatory response, tumor gene expression, and tumor angiogenesis to treat CRF. This study investigated the pharmacological basis and mechanism of HQSJZD in the treatment of CRF using systematic pharmacology, which provides an important reference for further elucidation of the anti-CRF mechanism and clinical applications of HQSJZD, and also provides a method protocol for similar studies in the future.

scholarly journals Molecular Targets and Mechanisms of Scutellariae radix-Coptidis rhizoma Drug Pair for the Treatment of Ulcerative Colitis Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Niu ◽  
Qifang Li ◽  
Yuan Liu ◽  
Yi Qiao ◽  
Bingbing Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Akt Signaling ◽  
Network Pharmacology ◽  
Akt Signaling Pathway ◽  
Active Ingredients ◽  
Scutellariae Radix ◽  
Drug Ingredient

This study aims to analyze the targets of the effective active ingredients of Scutellariae radix-Coptidis rhizoma drug pair (SCDP) in ulcerative colitis (UC) by network pharmacology and molecular docking and to explore the associated therapeutic mechanism. The effective active ingredients and targets of SCDP were determined from the TCMSP database, and the drug ingredient-target network was constructed using the Cytoscape software. The disease targets related to UC were searched in GeneCards, DisGeNET, OMIM, and DrugBank databases. Then, the drug ingredient and disease targets were intersected to construct a protein-protein interaction network through the STRING database. The Metascape database was used for the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the predicted targets of SCDP for UC. The Autodock software was used for molecular docking between the main active ingredient and the core target to evaluate the binding ability. SCDP has 43 effective active ingredients and 134 intersection targets. Core targets included AKT1, TP53, IL-6, VEGFA, CASP3, JUN, TNF, MYC, EGFR, and PTGS2. GO functional enrichment analysis showed that biological process was mainly associated with a cytokine-mediated signaling pathway, response to an inorganic substance, response to a toxic substance, response to lipopolysaccharide, reactive oxygen species metabolic process, positive regulation of cell death, apoptotic signaling pathway, and response to wounding. KEGG enrichment analysis showed main pathway concentrations were related to pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, bladder cancer, IL-17 signaling pathway, apoptosis, p53 signaling pathway, and PI3K-Akt signaling pathway. The drug active ingredient-core target-key pathway network contains 41 nodes and 108 edges, of which quercetin, wogonin, baicalein, acacetin, oroxylin A, and beta-sitosterol are important active ingredients; PTGS2, CASP3, TP53, IL-6, TNF, and AKT1 are important targets; and the pathways involved in UC treatment include pathways in cancer, PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetic, apoptosis, IL-17 signaling pathway and herpes simplex infection. The active ingredient has a good binding capacity to the core target. SCDP key active ingredients are mainly quercetin, wogonin, baicalein, acacetin, oroxylin A, and beta-sitosterol, which function mainly by regulating targets, such as PTGS2, CASP3, TP53, IL-6, TNF, and AKT1, and are associated with multiple signaling pathways as pathways in cancer, PI3K-Akt signaling pathway, apoptosis, IL-17 signaling pathways.

scholarly journals Phillyrin for COVID-19 and Influenza Co-infection: A Potential Therapeutic Strategy Targeting Host Based on Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Yanni Lai ◽  
Tiantian Han ◽  
Zizhao Lao ◽  
Geng Li ◽  
Jianyong Xiao ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Therapeutic Potential ◽  
Cell Receptor ◽  
Network Pharmacology ◽  
Ras Signaling ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Immune Balance ◽  
The Future ◽  
Receptor Signaling Pathway

Background: The risk of co-epidemic between COVID-19 and influenza is very high, so it is urgent to find a treatment strategy for the co-infection. Previous studies have shown that phillyrin can not only inhibit the replication of the two viruses, but also has a good anti-inflammatory effect, which is expected to become a candidate compound against COVID-19 and influenza.Objective: To explore the possibility of phillyrin as a candidate compound for the treatment of COVID-19 and influenza co-infection and to speculate its potential regulatory mechanism.Methods: We used a series of bioinformatics network pharmacology methods to understand and characterize the pharmacological targets, biological functions, and therapeutic mechanisms of phillyrin in COVID-19 and influenza co-infection and discover its therapeutic potential.Results: We revealed potential targets, biological processes, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and upstream pathway activity of phillyrin against COVID-19 and influenza co-infection. We constructed protein–protein interaction (PPI) network and identified 50 hub genes, such as MMP9, IL-2, VEGFA, AKT, and HIF-1A. Furthermore, our findings indicated that the treatment of phillyrin for COVID-19 and influenza co-infection was associated with immune balance and regulation of hypoxia-cytokine storm, including HIF-1 signaling pathway, PI3K-Akt signaling pathway, Ras signaling pathway, and T cell receptor signaling pathway.Conclusion: For the first time, we uncovered the potential targets and biological pathways of phillyrin for COVID-19 and influenza co-infection. These findings should solve the urgent problem of co-infection of COVID-19 and influenza that the world will face in the future, but clinical drug trials are needed for verification in the future.

scholarly journals Network Pharmacology Analysis of the Identification of Phytochemicals and Therapeutic Mechanisms of Paeoniae Radix Alba for the Treatment of Asthma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jingwei Wang ◽  
Ling Peng ◽  
Lu Jin ◽  
Huiying Fu ◽  
Qiyang Shou
Keyword(s):  
Enrichment Analysis ◽  
Biological Information ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Clinical Effects ◽  
Active Ingredients ◽  
Annotation Database ◽  
Kegg Pathways ◽  
Therapeutic Mechanisms ◽  
Paeoniae Radix

Background. Paeoniae Radix Alba (PRA), the root of the plant Paeonia lactiflora Pall., has been suggested to play an important role for the treatment of asthma. A biochemical understanding of the clinical effects of Paeoniae Radix Alba is needed. Here, we explore the phytochemicals and therapeutic mechanisms via a systematic and comprehensive network pharmacology analysis. Methods. Through TCMSP, PubChem, GeneCards database, and SwissTargetPrediction online tools, potential targets of active ingredients from PRA for the treatment of asthma were obtained. Cytoscape 3.7.2 was used to determine the target of active ingredients of PRA. Target protein interaction (PPI) network was constructed through the STRING database. The Gene Ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genes (KEGG) pathway enrichment analysis were analyzed through the biological information annotation database (DAVID). Results. Our results indicate that PRA contains 21 candidate active ingredients with the potential to treat asthma. The enrichment analysis of GO and KEGG pathways found that the treatment of asthma by PRA may be related to the process of TNF (tumor necrosis factor) release, which can regulate and inhibit multiple signaling pathways such as ceramide signaling. Conclusions. Our work provides a phytochemical basis and therapeutic mechanisms of PRA for the treatment of asthma, which provides new insights on further research on PRA.

scholarly journals Network Pharmacology-Based Prediction of Mechanism of Shenzhuo Formula for Application to DKD

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xinmiao Wang ◽  
Haoyu Yang ◽  
Lili Zhang ◽  
Lin Han ◽  
Sha Di ◽  
...  
Keyword(s):  
Rna Polymerase Ii ◽  
Signaling Pathway ◽  
Topological Analysis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Go Analysis

Background. Shenzhuo formula (SZF) is a traditional Chinese medicine (TCM) prescription which has significant therapeutic effects on diabetic kidney disease (DKD). However, its mechanism remains unknown. Therefore, this study aimed to explore the underlying anti-DKD mechanism of SZF. Methods. The active ingredients and targets of SZF were obtained by searching TCMSP, TCMID, SwissTargetPrediction, HIT, and literature. The DKD target was identified from TTD, DrugBank, and DisGeNet. The potential targets were obtained and PPI network were built after mapping SZF targets and DKD targets. The key targets were screened out by network topology and the “SZF-key targets-DKD” network was constructed by Cytoscape. GO analysis and KEGG pathway enrichment analysis were performed by using DAVID, and the results were visualized by Omicshare Tools. Results. We obtained 182 potential targets and 30 key targets. Furthermore, a “SZF-key targets-DKD” network topological analysis showed that active ingredients like M51, M21, M5, M71, and M28 and targets like EGFR, MMP9, MAPK8, PIK3CA, and STAT3 might play important roles in the process of SZF treating in DKD. GO analysis results showed that targets were mainly involved in positive regulation of transcription from RNA polymerase II promoter, inflammatory response, lipopolysaccharide-mediated signaling pathway, and other biological processes. KEGG showed that DKD-related pathways like TNF signaling pathway and PI3K-Akt signaling pathway were at the top of the list. Conclusion. This research reveals the potential pharmacological targets of SZF in the treatment of DKD through network pharmacology and lays a foundation for further studies.

scholarly journals Based on Network Pharmacology to Explore the Molecular Mechanism of Buzhong Yiqi Decoction for the Treatment of Gastric Cancer

2021 ◽  
Author(s):  
Ruiping Yang ◽  
Xiaojing Lin ◽  
Chunhui Tao ◽  
Ruixue Jiang
Keyword(s):  
Gastric Cancer ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Active Ingredients

Abstract BackgroundBuzhong Yiqi Decoction (BZYQD) has been widely accepted as an alternative treatment for gastric cancer (GC) in China. The present study set out to determine the potential molecular mechanism of BZYQD in the treatment of GC by means of network pharmacology, molecular docking, and molecular dynamics simulation.MethodsThe potential active ingredients and targets of BZYQD were screened out through the Traditional Chinese Medicine Systems Pharmacology (TCMSP). GC-related targets were screened out through the GeneCards database, and the intersection targets of BZYQD and GC were obtained by using the Venn diagram online tool. Then, the TCM-Active Ingredient-Target network was constructed by using the Cytoscape, and the protein-protein interaction (PPI) network was constructed by using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the effective targets of BZYQD in GC were performed through the Metascape platform. Finally, the molecular docking between the compounds and the target proteins was performed by using the AutoDock Vina software. The simulation of molecular dynamics was conducted for the optimal protein-ligand complex obtained by molecular docking using the Amber18 software.ResultsA total of 150 active ingredients of BZYQD were retrieved, corresponding to 136 targets of GC. The key active ingredients were quercetin, kaempferol, nobiletin, naringenin, and formononetin. The core targets were AKT1, STAT3, TP53, MAPK1, and MAPK3. GO functional enrichment analysis showed that BZYQD treated GC by affecting various biological processes such as oxidative stress, chemical stress, lipopolysaccharide reaction, and apoptosis. KEGG pathway enrichment analysis indicated that the apoptosis signaling pathway, PI3K/Akt signaling pathway, proteoglycan in cancer, IL-17 signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway were involved. Molecular docking results revealed the highest binding energy for MAPK3 and naringenin. The stable binding of MAPK3 and naringenin was also demonstrated in the molecular dynamics simulation test, with the binding free energy of -25kcal/mol.ConclusionThis study preliminarily revealed the multi-component, multi-target, and multi-pathway characteristics of BZYQD against GC, laying a scientific basis for further research on the molecular mechanism of BZYQD.

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