scholarly journals Network Pharmacology-Based Systematic Analysis of Molecular Mechanisms of Geranium wilfordii Maxim for HSV-2 Infection

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hao Zhang ◽  
Ming-Huang Gao ◽  
Yang Chen ◽  
Tao Liu
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Pharmacological Study ◽  
Network Pharmacology ◽  
System Response ◽  
Cytokine Signaling ◽  
Bioactive Substances ◽  
Systematic Analysis ◽  
Specific Distribution

Background. Being a traditional Chinese medicine, Geranium wilfordii Maxim (GWM) is used for the treatment of various infectious diseases, and its main active ingredients are the polyphenolic substances such as polyphenols quercetin, corilagin, and geraniin. Previous studies have demonstrated the anti-HSV-1 viral activity of these three main ingredients. Through employing a network pharmacological method, the authors of the present research intend to probe the mechanism of GWM for the therapeutic treatment of HSV-2 infection. Methods. The bioactive substances and related targets of GWM were obtained from the TCMSP database. Gene expression discrepancy for HSV-2 infection was obtained from dataset GSE18527. Crossover genes between disease target genes and GWM target genes were gained via Circos package. Distinctively displayed genes (DDGs) during HSV-2 infection were uploaded to the Metascape database with GWM target genes for further analysis. The tissue-specific distribution of the genes was obtained by uploading the genes to the PaGenBase database. Ingredient-gene-pathway (IGP) networks were constructed using Cytoscape software. Molecular docking investigations were carried out utilizing AutoDock Vina software. Results. Nine actively involved components were retrieved from the TCMSP database. After taking the intersection among 153 drug target genes and 83 DDGs, 7 crossover genes were screened. Gene enrichment analysis showed that GWM treatment of HSV-2 infection mainly involves cytokine signaling in the immune system, response to virus, epithelial cell differentiation, and type II interferon signaling (IFNG). One hub, three core objectives, and two critical paths were filtered out from the built network. Geraniin showed strong binding activity with HSV-2 gD protein and STING protein in molecular docking. Conclusions. This network pharmacological study provides a fundamental molecular mechanistic exploration of GWM for the treatment of HSV-2 infection.

scholarly journals Network Pharmacology-Based Systematic Analysis of Molecular Mechanisms of Dingji Fumai Decoction for Ventricular Arrhythmia

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yi Liang ◽  
Bo Liang ◽  
Xin-Rui Wu ◽  
Wen Chen ◽  
Li-Zhi Zhao
Keyword(s):  
Molecular Docking ◽  
Ventricular Arrhythmia ◽  
Molecular Mechanisms ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Systematic Analysis ◽  
Chemical Structures ◽  
Function Modules ◽  
Underlying Mechanisms

Background. Dingji Fumai Decoction (DFD), a traditional herbal mixture, has been widely used to ventricular arrhythmia (VA) in clinical practice in China. However, research on the bioactive components and underlying mechanisms of DFD in VA is still scarce. Methods. Components of DFD were collected from TCMSP, ETCM, and literature. The chemical structures of each component were obtained from PubChem. Next, SwissADME and SwissTargetPrediction were applied for compounds screening and targets prediction of DFD; meanwhile, targets of VA were collected from DrugBank and Online Mendelian Inheritance in Man (OMIM). Then, the H-C-T-D network and the protein-protein interaction (PPI) network were constructed based on the data obtained above. CytoNCA was utilized to filter hub genes and VarElect was used to analyze the relationship between genes and diseases. At last, Metascape was employed for systematic analysis on the potential targets of herbals against VA, and AutoDock was applied for molecular docking to verify the results. Results. A total of 434 components were collected, 168 of which were qualified, and there were 28 shared targets between DFD and VA. Three function modules of DFD were found from the PPI network. Further systematic analysis of shared genes and function modules explained the potential mechanism of DFD in the treatment of VA; molecular docking has verified the interactions. Conclusions. DFD could be employed for VA through mechanisms, including complex interactions between related components and targets, as predicted by network pharmacology and molecular docking. This work confirmed that DFD could apply to the treatment of VA and promoted the explanation of DFD for VA in the molecular mechanisms.

scholarly journals Network Pharmacology-based Systematic Analysis of Molecular Mechanisms of Dingji Fumai Decoction for Ventricular Arrhythmia

2020 ◽  
Author(s):  
Yi Liang ◽  
Bo Liang ◽  
Rui Xin Wu ◽  
Wen Chen ◽  
Li-zhi ZHAO
Keyword(s):  
Molecular Docking ◽  
Ventricular Arrhythmia ◽  
Molecular Mechanisms ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Systematic Analysis ◽  
Chemical Structures ◽  
Function Modules ◽  
Underlying Mechanisms ◽  
And Function

Abstract Background: Dingji Fumai decoction (DFD), a traditional herbal mixture, has been widely used to ventricular arrhythmia (VA) in clinical practice in China. However, research on the bioactive components and underlying mechanisms of DFD in VA is still scarce. Methods: Components of DFD were collected from TCMSP, ETCM, and literature. Then, the chemical structures of each component were obtained from PubChem. Next, SwissADME and SwissTargetPrediction were applied for compounds screening and targets prediction of DFD, meanwhile, targets of VA were collected from DrugBank and OMIM. Then, the H-C-T-D network as well as the PPI network were constructed based on the data obtained above. CytoNCA was utilized to filter hub genes and VarElect was used to analyze the relationship between genes and diseases. At last, Metascape was employed for systematic analysis on the potential targets of herbals against VA, and AutoDock was applied for molecular docking to verify the results.Results: A total of 434 components were collected, 168 of which were qualified, and there were 28 shared targets between DFD and VA. Three function modules of DFD were found from the PPI network. Further systematic analysis of shared genes and function modules explained the potential mechanism of DFD in the treatment of VA, molecular docking has verified the interactions. Conclusions: DFD could be employed for VA through mechanisms, including complex interactions between related components and targets, as predicted by network pharmacology and molecular docking. This work confirmed DFD could apply for the treatment of VA and promoted the explaining of DFD for VA in the molecular mechanisms.

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 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.

Molecular Mechanism of The Effect of Huanglian Jiedu Decoction On Ulcerative Colitis Based On Network Pharmacology And Molecular Docking

2021 ◽  
Author(s):  
Jing Yang ◽  
Chao-Tao Tang ◽  
Ruiri Jin ◽  
Bixia Liu ◽  
Peng Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Signal Pathway ◽  
Intestinal Barrier Function ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Ppi Network ◽  
Active Components

Abstract Huanglian jiedu decoction (HLJDD) is a heat-clearing and detoxifying agent composed of four kinds of Chinese herbal medicine. Previous studies have shown that HLJDD can improve the inflammatory response of ulcerative colitis (UC) and maintain intestinal barrier function. However, its molecular mechanism is not completely clear. In this study, we verified the bioactive components (BCI) and potential targets of HLJDD in the treatment of UC by means of network pharmacology and molecular docking, and constructed the pharmacological network and PPI network. Then the core genes were enriched by GO and KEGG. Finally, the bioactive components were docked with the key targets to verify the binding ability between them. A total of 54 active components related to UC were identified. Ten genes are considered to be very important to PPI network. Functional analysis showed that these target genes were mainly involved in the regulation of cell response to different stimuli, IL-17 signal pathway and TNF signal pathway. The results of molecular docking showed that the active components of HLJDD had good affinity with Hub gene. This study systematically elucidates the "multi-component, multi-target, multi-pathway" mechanism of anti-UC with HLJDD for the first time, suggesting that HLJDD or its active components may be candidate drugs for the treatment of ulcerative colitis.

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 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.

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.

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 Identifying Active Compounds and Targets of Fritillariae thunbergii against Influenza-Associated Inflammation by Network Pharmacology Analysis and Molecular Docking

Molecules ◽  
2020 ◽  
Vol 25 (17) ◽  
pp. 3853 ◽  
Author(s):  
Minjee Kim ◽  
Ki Hoon Park ◽  
Young Bong Kim
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Target Genes ◽  
Inflammatory Diseases ◽  
Network Pharmacology ◽  
Pharmacokinetic Parameters ◽  
Active Compounds ◽  
Biological Targets ◽  
Underlying Mechanisms ◽  
Cox 1

Complications due to influenza are often associated with inflammation with excessive release of cytokines. The bulbs of Fritillariae thunbergii (FT) have been traditionally used to control airway inflammatory diseases, such as bronchitis and pneumonia. To elucidate active compounds, the targets, and underlying mechanisms of FT for the treatment of influenza-induced inflammation, systems biology was employed. Active compounds of FT were identified through the TCMSP database according to oral bioavailability (OB) and drug-likeness (DL) criteria. Other pharmacokinetic parameters, Caco-2 permeability (Caco-2), and drug half-life (HL) were also identified. Biological targets of FT were retrieved from DrugBank and STITCH databases, and target genes associated with influenza, lung, and spleen inflammation were collected from DisGeNET and NCBI databases. Compound-disease-target (C-D-T) networks were constructed and merged using Cytoscape. Target genes retrieved from the C-D-T network were further analyzed with GO enrichment and KEGG pathway analysis. In our network, GO and KEGG results yielded two compounds (beta-sitosterol (BS) and pelargonidin (PG)), targets (PTGS1 (COX-1) and PTGS2 (COX-2)), and pathways (nitric oxide, TNF) were involved in the inhibitory effects of FT on influenza-associated inflammation. We retrieved the binding affinity of each ligand-target, and found that PG and COX-1 showed the strongest binding affinity among four binding results using a molecular docking method. We identified the potential compounds and targets of FT against influenza and suggest that FT is an immunomodulatory therapy for influenza-associated inflammation.

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