scholarly journals An Integrated Analysis of Network Pharmacology, Molecular Docking, and Experiment Validation to Explore the New Candidate Active Component and Mechanism of Cuscutae Semen-Mori Fructus Coupled-Herbs in Treating Oligoasthenozoospermia

2021 ◽  
Vol Volume 15 ◽  
pp. 2059-2089
Author(s):  
Xue Bai ◽  
Yibo Tang ◽  
Qiang Li ◽  
Dan Liu ◽  
Guimin Liu ◽  
...  
2020 ◽  
Author(s):  
Jin ping Hou ◽  
Yong heng Wang ◽  
Yu meng Chen ◽  
Yi hao Chen ◽  
Xiao Zhu ◽  
...  

Abstract BackgroundCoronavirus Disease 2019 (COVID-19) respiratory disease rapidly caused a global pandemic and social and economic disruption. The combination of Traditional Chinese medicine (TCM) and Conventional Western medicine (CWM) is more effective for COVID-19 treatment. Moreover, TCM and CWM are important data source for developing new drug targets and promote strategies treat SARS-CoV-2 infections. However, many studies have analyzed the therapeutic mechanism of CWM or TCM alone for COVID-19, it is still unclear the interaction mechanism between TCM and CWM on COVID-19.MethodsThis paper integrates network pharmacology and GEO database to mine and identify COVID-19 molecular therapeutic targets, providing potential targets and new ideas for COVID-19 gene therapy and new drug development. It includes: 1) using TCMSP, TTD, PubChem and CTD databases to analyze drug interactions and associated phenotypes for SARS-CoV-2, to correlate drug and disease interaction mechanisms to screen key drug targets; 2) using GEO database to correlate differential genes and drug targets to screen potential antiviral gene therapy targets, to construct regulatory network and key points of SARS-CoV-2 therapeutic drugs; 3) using computer simulation of molecular docking to screen virus-related proteins for new drugs. ResultsIntegrated analysis of network pharmacology discovered that baicalein, estrone and quercetin are the pivotal active ingredients in TCM and CWM. Combining drug target genes in pharmacology database and virus induced genes in GEO database, the result showed the core hub genes related to COVID-19: STAT1, IL1B, IL6, IL8, PTGS2 and NFKBIA, and these genes were significantly downregulated in A549 and NHBE cells by SARS-CoV-2 infection. Moreover, chemical interaction and molecular docking analysis of hub genes showed that folic acid might as be potential therapeutic drug for COVID-19 treatment, and SARS-CoV-2 nucleocapsid phosphoprotein was a potential drug target. The network of “drug-target-SARS-CoV-2 related genes” provide noval potential compounds and targets for further studies of SARS-CoV-2.ConclusionsIntegrated analysis of network pharmacology and big data mining provided noval potential compounds and targets for further studies of SARS-CoV-2. Our research implied folic acid and SARS-CoV-2 N as therapeutic target in TCM and CWM. Our research also suggests that targeting SARS-CoV-2 N protein is likely to be a common mechanism of TCM and CWM. On the one hand, the identification of pivotal genes provides a target for COVID-19 molecular therapy, on the other hand, it provides ideas for the analysis of interaction mechanism between virus and host.


2021 ◽  
Author(s):  
Zhiqiang li ◽  
Luo Jun

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


2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Guilin Ren ◽  
Yu Zhong ◽  
Gang Ke ◽  
Xiaoli Liu ◽  
Huiting Li ◽  
...  

The active component-target network and protein-protein interaction network of Compound Anshen essential oil were constructed. The target functions and related pathways were analyzed to explore the mechanism of Compound Anshen essential oil in the treatment of insomnia. GC-MS was used to detect the chemical composition of Compound Anshen essential oil, and the TCMSP, STITCH, TTD, and DrugBank databases were searched to predict and screen the targets of Compound Anshen essential oil in the treatment of insomnia. Cytoscape software was used to construct the network diagrams of the active component-action target and protein-protein interaction networks, ClueGO software was used to analyze the GO enrichment and KEGG pathway of the target, and the systemsDock website database was used for molecular docking. The analysis of the network results showed that the activity of Compound Anshen essential oil mainly involves biological processes such as the phospholipase C-activating G protein-coupled receptor signaling pathway, response to ammonium ions, calcium ion transport into the cytosol, and chloride transport. The results of molecular docking showed that linalool, caryophyllene, dibutyl phthalate, (-)-4-terpineol, and (-)-α-terpineol have good binding activity with ADRB2, DRD2, ESR1, KCNH2, NR1H4, NR1I2, NR1I3, and TRPV1 targets. This study demonstrates the multicomponent, multitarget, and multichannel characteristics of Compound Anshen essential oil and provides a new therapeutic idea and method for further research on the mechanism of Compound Anshen essential oil in the treatment of insomnia.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dan He ◽  
Qiang Li ◽  
Guangli Du ◽  
Jijia Sun ◽  
Guofeng Meng ◽  
...  

Objective. Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. Methods. The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. Results. According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. Conclusions. In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhicong Ding ◽  
Fangfang Xu ◽  
Qidi Sun ◽  
Bin Li ◽  
Nengxing Liang ◽  
...  

Background. Poststroke depression (PSD) is the most common and serious neuropsychiatric complication occurring after cerebrovascular accidents, seriously endangering human health while also imposing a heavy burden on society. Nevertheless, it is difficult to control disease progression. Gan-Mai-Da-Zao Decoction (GMDZD) is effective for PSD, but its mechanism of action in PSD is unknown. In this study, we explored the mechanism of action of GMDZD in PSD treatment using network pharmacology and molecular docking. Material and methods. We obtained the active components of all drugs and their targets from the public database TCMSP and published articles. Then, we collected PSD-related targets from the GeneCards and OMIM databases. Cytoscape 3.8.2 was applied to construct PPI and composite target disease networks. In parallel, the DAVID database was used to perform GO and KEGG enrichment analyses to determine the biological processes enriched in the treatment-related drugs in vivo. Finally, molecular docking was used to verify the association between the main active ingredients and their targets. Results. The network pharmacological analysis of GMDZD in PSD revealed 107 active ingredients with important biological effects, including quercetin, luteolin, kaempferol, naringenin, and isorhamnetin. In total, 203 potential targets for the treatment of this disease were screened, including STAT3, JUN, TNF, TPT53, AKT1, and EGFR. These drugs are widely enriched in a series of signaling pathways, such as TNF, HIF-1, and toll-like receptor. Moreover, molecular docking analysis showed that the core active components were tightly bound to their core targets, further confirming their anti-PSD effects. Conclusion. This prospective study was based on the integrated analysis of large data using network pharmacology technology to explore the feasibility of GMDZD for PSD treatment that was successfully validated by molecular docking. It reflects the multicomponent and multitarget characteristics of Chinese medicine and, more importantly, brings hope for the clinical treatment of PSD.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaoling Li ◽  
Baixin Lin ◽  
Zhiping Lin ◽  
Yucui Ma ◽  
Qu Wang ◽  
...  

AbstractFucosterol, a sterol isolated from brown algae, has been demonstrated to have anti-cancer properties. However, the effects and underlying molecular mechanism of fucosterol on non-small cell lung cancer remain to be elucidated. In this study, the corresponding targets of fucosterol were obtained from PharmMapper, and NSCLC related targets were gathered from the GeneCards database, and the candidate targets of fucosterol-treated NSCLC were predicted. The mechanism of fucosterol against NSCLC was identified in DAVID6.8 by enrichment analysis of GO and KEGG, and protein–protein interaction data were collected from STRING database. The hub gene GRB2 was further screened out and verified by molecular docking. Moreover, the relationship of GRB2 expression and immune infiltrates were analyzed by the TIMER database. The results of network pharmacology suggest that fucosterol acts against candidate targets, such as MAPK1, EGFR, GRB2, IGF2, MAPK8, and SRC, which regulate biological processes including negative regulation of the apoptotic process, peptidyl-tyrosine phosphorylation, positive regulation of cell proliferation. The Raf/MEK/ERK signaling pathway initiated by GRB2 showed to be significant in treating NSCLC. In conclusion, our study indicates that fucosterol may suppress NSCLC progression by targeting GRB2 activated the Raf/MEK/ERK signaling pathway, which laying a theoretical foundation for further research and providing scientific support for the development of new drugs.


RSC Advances ◽  
2021 ◽  
Vol 11 (19) ◽  
pp. 11610-11626
Author(s):  
Reham S. Ibrahim ◽  
Alaa A. El-Banna

Multi-level mechanism of action of propolis constituents in cancer treatment using an integrated approach of network pharmacology-based analysis, molecular docking and in vitro cytotoxicity testing.


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