scholarly journals Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang
Keyword(s):  
Molecular Docking ◽  
Liver Fibrosis ◽  
Molecular Mechanisms ◽  
Docking Simulation ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Metabolomics Data ◽  
Metabolic Products ◽  
Compound Target

Abstract Background The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6: 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics data, network pharmacology and molecular docking methods. Methods Firstly, we collected prototype components and metabolic products after administration of HQD from a publication. With known and predicted targets, compound-target interactions were obtained. Then, the global compound-liver fibrosis target bipartite network and the HQD-liver fibrosis protein–protein interaction network were constructed, separately. KEGG pathway analysis was applied to further understand the mechanisms related to the target proteins of HQD. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets. Finally, considering the concentrations of prototype compounds and metabolites of HQD, the critical compound-liver fibrosis target bipartite network was constructed. Results 68 compounds including 17 prototype components and 51 metabolic products were collected. 540 compound-target interactions were obtained between the 68 compounds and 95 targets. Combining network analysis, molecular docking and concentration of compounds, our final results demonstrated that eight compounds (three prototype compounds and five metabolites) and eight targets (CDK1, MMP9, PPARD, PPARG, PTGS2, SERPINE1, TP53, and HIF1A) might contribute to the effects of HQD on liver fibrosis. These interactions would maintain the balance of ECM, reduce liver damage, inhibit hepatocyte apoptosis, and alleviate liver inflammation through five signaling pathways including p53, PPAR, HIF-1, IL-17, and TNF signaling pathway. Conclusions This study provides a new way to understand the MoA of HQD on liver fibrosis by considering the concentrations of components and metabolites, which might be a model for investigation of MoA of other Chinese herbs.

scholarly journals Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches

2021 ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Liver Fibrosis ◽  
Signaling Pathway ◽  
Chinese Herbs ◽  
Bipartite Network ◽  
Therapeutic Effects ◽  
Metabolic Products ◽  
Compound Target

Abstract Background: The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6 : 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics data, network pharmacology and molecular docking methods. Methods: Firstly, we collected prototype components and metabolic products after administration of HQD from a publication. With known and predicted targets, compound-target interactions were obtained. Then, the global compound-liver fibrosis target bipartite network and the HQD-liver fibrosis protein-protein interaction network were constructed, separately. KEGG pathway analysis was applied to further understand the mechanisms related to the target proteins of HQD. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets. Finally, after taking concentration of prototype compounds and metabolites of HQD after administration into consideration, the critical compound-liver fibrosis target bipartite network was constructed.Results: We collected 68 components, including 17 prototype components and 51 metabolic products after administration of HQD, and 540 compound-target interactions were obtained between the 68 components and 95 targets. Combining network analysis and molecular docking, as well as concentration of prototype compounds and metabolites of HQD, our final results demonstrated that eight compounds (three prototype compounds and five metabolites) and eight targets (CDK1, MMP9, PPARD, PPARG, PTGS2, SERPINE1, TP53, and HIF1A) might contribute to the effects of HQD on liver fibrosis by reducing fibrogenesis and stimulate degradation, which through p53 signaling pathway, PPAR signaling pathway, HIF-1 signaling pathway, IL-17 signaling pathway, and TNF signaling pathway.Conclusions: Our results would shed light on the complicated MoA of traditional Chinese medicine and help to attract attention to the therapeutic effects of metabolites of original components in Chinese herbs through computational methods.

scholarly journals Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Jiye Wang ◽  
Weihua Li ◽  
Guixia Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Binding Free Energy ◽  
Leukemia Cell ◽  
Docking Simulation ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Molecular Docking Simulation ◽  
Arnebia Euchroma ◽  
Compound Target

Abstract Background Arnebia euchroma (A. euchroma) is a traditional Chinese medicine (TCM) used for the treatment of blood diseases including leukemia. In recent years, many studies have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. However, the underlying mechanism of action (MoA) for all the components of A. euchroma on leukemia has not been explored systematically. Methods In this study, we analyzed the MoA of A. euchroma on leukemia via network pharmacology approach. Firstly, the chemical components and their concentrations in A. euchroma as well as leukemia-related targets were collected. Next, we predicted compound-target interactions (CTIs) with our balanced substructure-drug-target network-based inference (bSDTNBI) method. The known and predicted targets of A. euchroma and leukemia-related targets were merged together to construct A. euchroma-leukemia protein-protein interactions (PPIs) network. Then, weighted compound-target bipartite network was constructed according to combination of eight central attributes with concentration information through Cytoscape. Additionally, molecular docking simulation was performed to calculate whether the components and predicted targets have interactions or not. Results A total of 65 components of A. euchroma were obtained and 27 of them with concentration information, which were involved in 157 targets and 779 compound-target interactions (CTIs). Following the calculation of eight central attributes of targets in A. euchroma-leukemia PPI network, 37 targets with all central attributes greater than the median values were selected to construct the weighted compound-target bipartite network and do the KEGG pathway analysis. We found that A. euchroma candidate targets were significantly associated with several apoptosis and inflammation-related biological pathways, such as MAPK signaling, PI3K-Akt signaling, IL-17 signaling, and T cell receptor signaling pathways. Moreover, molecular docking simulation demonstrated that there were eight pairs of predicted CTIs had the strong binding free energy. Conclusions This study deciphered that the efficacy of A. euchroma in the treatment of leukemia might be attributed to 10 targets and 14 components, which were associated with inhibiting leukemia cell survival and inducing apoptosis, relieving inflammatory environment and inhibiting angiogenesis.

scholarly journals Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach

2020 ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Jiye Wang ◽  
Weihua Li ◽  
Guixia Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Binding Free Energy ◽  
Docking Simulation ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Molecular Docking Simulation ◽  
Arnebia Euchroma ◽  
Compound Target

Abstract Background: Arnebia euchroma (A. euchroma), a traditional Chinese medicine (TCM) for the treatment of blood diseases. In recent years, more and more researches have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. However, the underlying mechanism of action (MoA) for all the ingredients of A. euchroma on leukemia has not been explored systematically.Methods: In this study, we tried to analyze the MoA of A. euchroma on leukemia via network pharmacology approach. Firstly, the chemical components and their concentrations in A. euchroma as well as leukemia-related targets were collected. Next, we predicted compound-target interactions (CTIs) via our balanced substructure-drug-target network-based inference (bSDTNBI) method. The known and predicted targets of A. euchroma and leukemia-related targets were merged together to construct A. euchroma-leukemia protein-protein interactions (PPIs) network. Then, weighted compound-target bipartite network was constructed according to combination of eight central attributes with concentrations information via Cytoscape. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets.Results: A total of 65 components of A. euchroma were obtained and 27 of them with concentration information, which involved in 157 targets, 779 compound- target interactions (CTIs), including 129 known CTIs (KCTIs) and 650 predicted CTIs (PCTIs). Following the analysis of A. euchroma-leukemia PPI network, 37 targets were used to construct the weighted compound-target bipartite network and further KEGG pathway analysis. We found that A. euchroma candidate targets were significantly associated with several apoptosis and inflammation-related biological pathways, such as MAPK signaling pathway, PI3K-Akt signaling pathway, IL-17 signaling pathway, T cell receptor signaling pathway. Moreover, molecular docking simulation demonstrated that there were 8 pairs of PCTIs had the strong binding free energy.Conclusions: This network pharmacology-based study considered the information of component concentration, in combination with molecular docking, deciphered that the efficacy of A. euchroma in the treatment of leukemia may be mainly attributed to 10 targets and 14 components, which were associated with inhibiting leukemia cell survival and inducing apoptosis, relieving inflammatory environment and inhibiting angiogenesis.

scholarly journals Elucidating the Mechanisms of Hugan Buzure Granule in the Treatment of Liver Fibrosis via Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yi Zhu ◽  
Ming Qiao ◽  
Jianhua Yang ◽  
Junping Hu
Keyword(s):  
Liver Fibrosis ◽  
Rna Polymerase Ii ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Docking Simulation ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Transcription Activator ◽  
Active Ingredients ◽  
Oxidoreductase Activity

Objective. To holistically explore the latent active ingredients, targets, and related mechanisms of Hugan buzure granule (HBG) in the treatment of liver fibrosis (LF) via network pharmacology. Methods. First, we collected the ingredients of HBG by referring the TCMSP server and literature and filtered the active ingredients though the criteria of oral bioavailability ≥30% and drug-likeness index ≥0.18. Second, herb-associated targets were predicted and screened based on the BATMAN-TCM and SwissTargetPrediction platforms. Candidate targets related to LF were collected from the GeneCards and OMIM databases. Furthermore, the overlapping target genes were used to construct the protein-protein interaction network and “drug-compound-target-disease” network. Third, GO and KEGG pathway analyses were carried out to illustrate the latent mechanisms of HBG in the treatment of LF. Finally, the combining activities of hub targets with active ingredients were further verified based on software AutoDock Vina. Results. A total of 25 active ingredients and 115 overlapping target genes of HBG and LF were collected. Besides, GO enrichment analysis exhibited that the overlapping target genes were involved in DNA-binding transcription activator activity, RNA polymerase II-specific, and oxidoreductase activity. Simultaneously, the key molecular mechanisms of HBG against LF were mainly involved in PI3K-AKT, MAPK, HIF-1, and NF-κB signaling pathways. Also, molecular docking simulation demonstrated that the key targets of HBG for antiliver fibrosis were IL6, CASP3, EGFR, VEGF, and MAPK. Conclusion. This work validated and predicted the underlying mechanisms of multicomponent and multitarget about HBG in treating LF and provided a scientific foundation for further research.

scholarly journals Exploration in the Mechanism of Kaempferol for the Treatment of Gastric Cancer Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Liangjun Yang ◽  
Haiwen Li ◽  
Maoyi Yang ◽  
Weijian Zhang ◽  
Mianli Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Mendelian Inheritance ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Novel Approach ◽  
Disease Associated Genes

Background. Kaempferol is a natural polyphenol in lots of Chinese herbs, which has shown promising treatment for gastric cancer (GC). However, the molecular mechanisms of its action have not been systematically revealed yet. In this work, a network pharmacology approach was used to elucidate the potential mechanisms of kaempferol in the treatment of GC. Methods. The kaempferol was input into the PharmMapper and SwissTargetPrediction database to get its targets, and the targets of GC were obtained by retrieving the Online Mendelian Inheritance in Man (OMIM) database, MalaCards database, Therapeutic Target Database (TTD), and Coolgen database. The molecular docking was performed to assess the interactions between kaempferol and these targets. Next, the overlap targets of kaempferol and GC were identified for GO and KEGG enrichment analyses. Afterward, a protein-protein interaction (PPI) network was constructed to get the hub targets, and the expression and overall survival analysis of the hub target were investigated. Finally, the overall survival (OS) analysis of hub targets was performed using the Kaplan-Meier Plotter online tool. Results. A total of 990 genes related to GC and 10 overlapping genes were determined through matching the 24 potential targets of kaempferol with disease-associated genes. The result of molecular docking indicated that kaempferol can bind with these hub targets with good binding scores. These targets were further mapped to 140 GO biological process terms and 11 remarkable pathways. In the PPI network analysis, 3 key targets were identified, including ESR1, EGFR, and SRC. The mRNA and protein expression levels of EGFR and SRC were obviously higher in GC tissues. High expression of these targets was related to poor OS in GC patients. Conclusions. This study provided a novel approach to reveal the therapeutic mechanisms of kaempferol on GC, which will ease the future clinical application of kaempferol in the treatment of GC.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Qing-Fei-Da-Yuan Granules

2020 ◽  
Vol 15 (6) ◽  
pp. 1934578X2093421 ◽  
Author(s):  
Zongchao Hong ◽  
Xueyun Duan ◽  
Songtao Wu ◽  
Yang Yanfang ◽  
Hezhen Wu
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Binding Capacity ◽  
Chemical Constituents ◽  
Network Pharmacology ◽  
Binding Ability ◽  
The Core ◽  
Strong Binding ◽  
Compound Target

Coronavirus disease (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a highly infectious viral disease. Clinical observations have shown that Qing-Fei-Da-Yuan (QFDY) granules have good anti-COVID-19 effects, but the underlying molecular mechanisms are unclear. In this study, we explored the potential mechanism of QFDY with regard to its anti-COVID-19 effect. We first screened the active chemical constituents of QFDY based on the pharmacodynamic activity parameters, followed by screening with the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The Uniprot database was used for querying the corresponding genes of the target, and Cyoscape 3.6.1 software was used to construct the network of herb-compound-target. Protein interaction analysis, target gene function enrichment analysis, and signal pathway analysis were performed via STRING database, Database for Annotation, Visualization, and Integrated Discovery, and KEGG Pathway database. Molecular docking was used to predict the binding capacity of the core compound with COVID-19 hydrolase 3CL and angiotensin converting enzyme 2 (ACE2). The results showed that a network of herb-compound-target was successfully constructed, with key targets involving PTGS2, HSP90AA1, CAMKK2, NCOA2, and ESR1. Major metabolic pathways affected were those in cancer, procancer, nonsmall cell lung cancer, and apoptosis. The core compounds, such as quercetin, luteolin, and naringenin, showed a strong binding ability with COVID-19 3CL hydrolase; compounds such as anemasaponin C and medicocarpin showed a strong binding ability with ACE2. Thus, it is predicted that QFDY has the characteristics for multicomponent, multitarget, and multichannel overall control. The mechanism of action of QFDY in the treatment of COVID-19 may be associated with the regulation of genes co-expressed with ACE2, the regulation of inflammation and immune-related signaling pathways, and the influence of COVID-19 3CL hydrolase and ACE2 binding ability.

scholarly journals Network pharmacology and molecular docking study on the active ingredients of qidengmingmu capsule for the treatment of diabetic retinopathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingxu Zhang ◽  
Jiawei Yang ◽  
Xiulan Zhao ◽  
Ying Zhao ◽  
Siquan Zhu
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Hypoxia Inducible Factor ◽  
Enrichment Analysis ◽  
Docking Study ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Ingredients ◽  
Molecular Docking Study

AbstractDiabetic retinopathy (DR) is a leading cause of irreversible blindness globally. Qidengmingmu Capsule (QC) is a Chinese patent medicine used to treat DR, but the molecular mechanism of the treatment remains unknown. In this study, we identified and validated potential molecular mechanisms involved in the treatment of DR with QC via network pharmacology and molecular docking methods. The results of Ingredient-DR Target Network showed that 134 common targets and 20 active ingredients of QC were involved. According to the results of enrichment analysis, 2307 biological processes and 40 pathways were related to the treatment effects. Most of these processes and pathways were important for cell survival and were associated with many key factors in DR, such as vascular endothelial growth factor-A (VEGFA), hypoxia-inducible factor-1A (HIF-1Α), and tumor necrosis factor-α (TNFα). Based on the results of the PPI network and KEGG enrichment analyses, we selected AKT1, HIF-1α, VEGFA, TNFα and their corresponding active ingredients for molecular docking. According to the molecular docking results, several key targets of DR (including AKT1, HIF-1α, VEGFA, and TNFα) can form stable bonds with the corresponding active ingredients of QC. In conclusion, through network pharmacology methods, we found that potential biological mechanisms involved in the alleviation of DR by QC are related to multiple biological processes and signaling pathways. The molecular docking results also provide us with sound directions for further experiments.

scholarly journals NMPA-approved traditional Chinese medicine-Pingwei Pill: new indication for colistin recovery against MCR-positive bacteria infection

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Qiushuang Sheng ◽  
Runbao Du ◽  
Cunhui Ma ◽  
Yonglin Zhou ◽  
Xue Shen ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Bacterial Infection ◽  
Molecular Mechanisms ◽  
Topological Analysis ◽  
Network Pharmacology ◽  
Synergistic Activity ◽  
Colistin Resistance ◽  
Western Blot Assay ◽  
Gram Negative

Abstract Background The wide spread of plasmid-mediated colistin resistance by mobile colistin resistance (MCR) in Enterobacteriaceae severely limits the clinical application of colistin as a last-line drug against bacterial infection. The identification of colistin potentiator from natural plants or their compound preparation as antibiotic adjuncts is a new promising strategy to meet this challenge. Methods Herein, the synergistic activity, as well as the potential mechanism, of Pingwei pill plus antibiotics against MCR-positive Gram-negative pathogens was examined using checkerboard assay, time-killing curves, combined disk test, western blot assay, and microscope analysis. Additionally, the Salmonella sp. HYM2 infection models of mouse and chick were employed to examine the in vivo efficacy of Pingwei pill in combination with colistin against bacteria infection. Finally, network pharmacology and molecular docking assay were used to predicate other actions of Pingwei pill for Salmonella infection. Results Our results revealed that Pingwei Pill synergistically potentiated the antibacterial activity of colistin against MCR-1-positive bacteria by accelerating the damage and permeability of the bacterial outer membrane with an FIC (Fractional Inhibitory Concentration) index less than 0.5. The treatment of Pingwei Pill neither inhibited bacterial growth nor affected MCR production. Notably, Pingwei Pill in combination with colistin significantly prolonged the median survival in mouse and chick models of infection using the Salmonella sp. strain HYM2, decreased bacteria burden and organ index of infected animal, alleviated pathological damage of cecum, which suggest that Pingwei Pill recovered the therapeutic performance of colistin for MCR-1- positive Salmonella infection in mice and the naturally infected host chick. Pharmacological network topological analysis, molecular docking, bacterial adhesion, and invasion pathway verification assays were performed to identify the other molecular mechanisms of Pingwei Pill as a colistin potentiator against Gram-negative bacteria infection. Conclusion Taken together, NMPA (National Medical Products Administration)-approved Pingwei Pill is a promising adjuvant with colistin for MCR-positive bacterial infection with a shortened R&D (research and development) cycle and affordable R&D cost and risk.

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 Mechanisms of Compound Kushen Injection for the Treatment of Lung Cancer Based on Network Pharmacology

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Ziqi Meng ◽  
Xinkui Liu ◽  
Jiarui Wu ◽  
Wei Zhou ◽  
Kaihuan Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Molecular Docking ◽  
Small Cell Lung Cancer ◽  
Docking Simulation ◽  
Small Cell ◽  
Network Pharmacology ◽  
Small Cell Lung ◽  
Molecular Docking Simulation ◽  
Target Network ◽  
Compound Kushen Injection

Background. Compound Kushen Injection (CKI) is a Chinese patent drug that shows good efficacy in treating lung cancer (LC). However, its underlying mechanisms need to be further clarified.Methods. In this study, we adopted a network pharmacology method to gather compounds, predict targets, construct networks, and analyze biological functions and pathways. Moreover, molecular docking simulation was employed to assess the binding potential of selected target-compound pairs.Results. Four networks were established, including the compound-putative target network, protein-protein interaction (PPI) network of LC targets, compound-LC target network, and herb-compound-target-pathway network. Network analysis showed that 8 targets (CHRNA3, DRD2, PRKCA, CDK1, CDK2, CHRNA5, MMP1, and MMP9) may be the therapeutic targets of CKI in LC. In addition, molecular docking simulation indicated that CHRNA3, DRD2, PRKCA, CDK1, CDK2, MMP1, and MMP9 had good binding activity with the corresponding compounds. Furthermore, enrichment analysis indicated that CKI might exert a therapeutic role in LC by regulating some important pathways, namely, pathways in cancer, proteoglycans in cancer, PI3K-Akt signaling pathway, non-small-cell lung cancer, and small cell lung cancer.Conclusions. This study validated and predicted the mechanism of CKI in treating LC. Additionally, this study provides a good foundation for further experimental studies and promotes the reasonable application of CKI in the clinical treatment of LC.

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