scholarly journals Revealing the Mechanism of Astragali Radix against Cancer-Related Fatigue by Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yi Xie ◽  
Kainan Zhou ◽  
Yan Wang ◽  
Shuhan Yang ◽  
Suying Liu ◽  
...  

Background. Cancer-related fatigue (CRF) is an increasingly appreciated complication in cancer patients, which severely impairs their quality of life for a long time. Astragali Radix (AR) is a safe and effective treatment to improve CRF, but the related mechanistic studies are still limited. Objective. To systematically analyze the mechanism of AR against CRF by network pharmacology. Methods. TCMSP was searched to obtain the active compounds and targets of AR. The active compound-target (AC-T) network was established and exhibited by related visualization software. The GeneCards database was searched to acquire CRF targets, and the intersection targets with AR targets were used to make the Venny diagram. The protein-protein interaction (PPI) network of intersection targets was established, and further, the therapeutic core targets were selected by topological parameters. The selected core targets were uploaded to Metascape for GO and KEGG analysis. Finally, AutoDock Vina and PyMOL were employed for molecular docking validation. Results. 16 active compounds of AR were obtained, such as quercetin, kaempferol, 7-O-methylisomucronulatol, formononetin, and isorhamnetin. 57 core targets were screened, such as AKT1, TP53, VEGFA, IL-6, and CASP3. KEGG analysis manifested that the core targets acted on various pathways, including 137 pathways such as TNF, IL-17, and the AGE-RAGE signaling pathway. Molecular docking demonstrated that active compounds docked well with the core targets. Conclusion. The mechanism of AR in treating CRF involves multiple targets and multiple pathways. The present study laid a theoretical foundation for the subsequent research and clinical application of AR and its extracts against CRF.

2021 ◽  
Author(s):  
Lu Sun ◽  
Zining Wang ◽  
Jian Li ◽  
Li Xu ◽  
Xiaoou Xue

Abstract Background: Primary dysmenorrhea(PD)is the most common gynecologic disorder.Despite the prevalence is high, it is often underdiagnosed,undertreated and normalized even by patients themselves. Guizhi Fuling Formula (GFF) is experientially used for the treatment of PD in a long time. Therefore, the efficiency and potential mechanism are waiting to identify.Methods: We adopted network pharmacology integrated molecular docking strategy in this study.Based on published literatures, the relative compounds of GFF were selected preliminarily. Secondly, the putative targets of PD were obtained by wide-searching DisGeNET, OMIM, Drugbank and GeneCards databases.With protein-protein interaction(PPI) analysis, GO and KEGG pathway enrichment analysis and molecular docking ,we systematically evaluated the relationship of herb ingredients and disease targets.Results: The results showed that 30 ingredients of GFF and 43 hub targets made a difference.Under the further analysis,8 targets(EGFR,AKT1,PTGS2,TNF,ESR1,AHR,CTNNB1,CXCL8) were recognized as key therapeutic targets with excellent binding. The enrichment analyses indicated that the GFF had the potential to influence varieties of biological pathways, especially the pathways in cancer and steroid hormone biosynthesis, which play an important part in the pathogenesis of primary dysmenorrhea.Conclusion: GFF influenced primary dysmenorrhea through the synergistic effect of multiple components, multiple targets, and multiple pathways.This study predictedthe potential mechanism, hope that could made contribution for clinical application and scientific research.


2021 ◽  
Vol 8 ◽  
Author(s):  
Guishu Wang ◽  
Bo Zhou ◽  
Zheyi Wang ◽  
Yufeng Meng ◽  
Yaqian Liu ◽  
...  

BackgroundAsthma is a chronic inflammatory disease characterized by Th2-predominant inflammation and airway remodeling. Modified Guo Min decoction (MGMD) has been an extensive practical strategy for allergic disorders in China. Although its potential anti-asthmatic activity has been reported, the exact mechanism of action of MGMD in asthma remains unexplored.MethodsNetwork pharmacology approach was employed to predict the active components, potential targets, and molecular mechanism of MGMD for asthma treatment, including drug-likeness evaluation, oral bioavailability prediction, protein–protein interaction (PPI) network construction and analysis, Gene Ontology (GO) terms, and Reactome pathway annotation. Molecular docking was carried out to investigate interactions between active compounds and potential targets.ResultsA total of 92 active compounds and 72 anti-asthma targets of MGMD were selected for analysis. The GO enrichment analysis results indicated that the anti-asthmatic targets of MGMD mainly participate in inflammatory and in airway remolding processes. The Reactome pathway analysis showed that MGMD prevents asthma mainly through regulation of the IL-4 and IL-13 signaling and the specialized pro-resolving mediators (SPMs) biosynthesis. Molecular docking results suggest that each bioactive compounds (quercetin, wogonin, luteolin, naringenin, and kaempferol) is capable to bind with STAT3, PTGS2, JUN, VEGFA, EGFR, and ALOX5.ConclusionThis study revealed the active ingredients and potential molecular mechanism by which MGMD treatment is effective against airway inflammation and remodeling in asthma through regulating IL-4 and IL-13 signaling and SPMs biosynthesis.


2020 ◽  
Author(s):  
Xiao Song ◽  
Fei Guo ◽  
Xiao-Chen Sun ◽  
Shu-Yue Wang ◽  
Yao-Hui Yuan ◽  
...  

Abstract Background: Leukemia was listed by the World Health Organization as one of the five most intractable diseases in the world. The multi-drug resistance (MDR) of leukemia cells limits the efficacy of anti-tumor drugs and is the major reason for the chemotherapy failure and recurrence of leukemia chemotherapy. Some studies have shown that Euphorbiae semen (ES) possesses the characteristics of new therapeutic drugs for MDR. However, the molecular mechanisms and active compounds have not yet been fully clarified. Therefore, there is a need for explore its active compounds and demonstrate its mechanisms through network pharmacology and molecular docking technology.Method: First, the TCMSP database was searched and screened the active compounds of the ES, supplemented with compounds verified by literature, so as to further identify the core compounds in the active ingredient. Simultaneously, the TCMSP and Swiss database were searched to the targets of active compounds, and the targets of reverses leukemia multidrug resistance (RL-MDR) were screened in the relevant databases, such as GeneCards and DrugBank. Then, the targets of active compounds were intersected with RL-MDR targets to obtain potential targets of ES acting on MDR. The compound–target network was constructed by Cytoscape. The target protein–protein interaction network was built using STRING and Cytoscape database. Second, the R language and DAVID database were used to analyse Gene Ontology (GO) biological functions analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways enrichment. Finally, molecular docking method was utilized to investigate the binding activity between the core targets and the active compounds of ES.Results: Compound–target network mainly contained 22 compounds and 81 corresponding targets. Finally, seven components in ES were selected and 10 core targets were identified; Key targets contained JUN, CASP3, MAOA, AR, PPARG, DRD2, ADRA2A, CHRM2, PTGS2 and MAPK14. GO enrichment analysis indicated the main biological functions of potential genes of ES in the treatment of MDR. KEGG pathway enrichment analysis showed the main pathways, mainly including apoptosis, pathways in cancer, p53 signaling pathway, VEGF signaling pathway, TNF signaling pathway and PI3K–Akt signaling pathway. Finally, we chose the top 10 common targets for molecular docking with the 7 active compounds of ES. The results of molecular docking indicated that the compounds of ES, which had good affinity with targets. Conclusion: The molecular mechanism of ES in the treatment of MDR showed the synergistic reaction of multi-compound, multi-target, and multi-pathway of traditional Chinese medicine, which provided ideas for further clinical research.


2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110206
Author(s):  
Ying Zhang ◽  
Yunfeng Yao ◽  
Yanfang Yang ◽  
Hezhen Wu

Objective Jinhua Qinggan Granules (JQGs) have achieved certain results in the prevention and treatment of COVID-19 in China during this coronavirus storm. In this study, we aimed to analyze the common mechanisms of JQG in the treatment of coronavirus-induced diseases, such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19 via network pharmacology and molecular docking. Methods The active compounds of JQG were collected through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The common targets associated with these 3 diseases were screened from GeneCards database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of JQG’s core targets were analyzed using The Database for Annotation, Visualization, and Integrated Discovery and KOBAS 3.0 system. Further, the protein-protein interaction network was built using STRING database. The compound-target- signaling pathway network was constructed using Cytoscape 3.7.2. The core components of JQG were docked with core targets, COVID-19 coronavirus 3 Cl hydrolase, and angiotensin-converting enzyme 2 (ACE2) via Discovery Studio 2016 software. Results A total of 139 active compounds, 50 core targets, and 122 signaling pathways were screened out. The results of molecular docking showed that arctiin and linarin had a higher docking score with 3 Cl, ACE2, and core targets of JQH for antiviral effect. Conclusion The potential mechanism of action of JHQ in the treatment of MERS, SARS, and COVID-19 may be associated with the regulation of genes co-expressed with ACE2 and immune- related signaling pathways.


2022 ◽  
Vol 2022 ◽  
pp. 1-20
Author(s):  
Sijie Li ◽  
Yong Yang ◽  
Wei Zhang ◽  
Haiyan Li ◽  
Wantong Yu ◽  
...  

Purpose. Danggui Shaoyao San (DSS) was developed to treat the ischemic stroke (IS) in patients and animal models. The purpose of this study was to explore its active compounds and demonstrate its mechanism against IS through network pharmacology, molecular docking, and animal experiment. Methods. All the components of DSS were retrieved from the pharmacology database of TCM system. The genes corresponding to the targets were retrieved using OMIM, CTD database, and TTD database. The herb-compound-target network was constructed by Cytoscape software. The target protein-protein interaction network was built using the STRING database. The core targets of DSS were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then, we achieved molecular docking between the hub proteins and the key active compounds. Finally, animal experiments were performed to verify the core targets. Triphenyltetrazolium chloride (TTC) staining was used to calculate the infarct size in mice. The protein expression was determined using the Western blot. Results. Compound-target network mainly contained 51 compounds and 315 corresponding targets. Key targets contained MAPK1, SRC, PIK3R1, HRAS, AKT1, RHOA, RAC1, HSP90AA1, and RXRA FN1. There were 417 GO items in GO enrichment analysis ( p < 0.05 ) and 119 signaling pathways ( p < 0.05 ) in KEGG, mainly including negative regulation of apoptosis, steroid hormone-mediated signaling pathway, neutrophil activation, cellular response to oxidative stress, and VEGF signaling pathway. MAPK1, SRC, and PIK3R1 docked with small molecule compounds. According to the Western blot, the expression of p-MAPK 1, p-AKT, and p-SRC was regulated by DSS. Conclusions. This study showed that DSS can treat IS through multiple targets and routes and provided new insights to explore the mechanisms of DSS against IS.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Hui Tian ◽  
Linli Wei ◽  
Yunxiu Yao ◽  
Zhaoqing Zeng ◽  
Xue Liang ◽  
...  

Objective. The possible core active compounds and potential mechanism of action of Shiyifang Vinum were explored through network pharmacology and in vitro enzyme activity verification experiments. Methods. We screened the core active components and the action targets of Shiyifang Vinum through the TCMSP database and literature mining and drew a Venn map of the intersection with anti-inflammatory and analgesic-related gene targets. Go and KEGG analyses were enriched with the David database. The compound target pathway network was constructed using Cytoscape 3.6.1. The binding strength of core active compounds and target proteins was verified through molecular docking, and the direct effects of Shiyifang Vinum and four monomer compounds on COX-2 enzyme activity were detected through an in vitro enzyme activity test. Results. 14 active compounds and 11 targets were screened out from Shiyifang Vinum through TCMSP database and literature mining; 252 GO entries were obtained by GO analysis, and 114 signal pathways were screened by KEGG analysis. The results of the molecular docking showed that the core compounds and target proteins had strong binding activity. In vitro validation experiments showed that both the Shiyifang Vinum and the four monomer compounds could inhibit the activity of COX-2. Conclusion. This study preliminarily explored the potential active compounds and target proteins of the anti-inflammatory and analgesic effects of Shiyifang Vinum, which could provide a scientific basis for further study on the anti-inflammatory and analgesic mechanism and material basis of this recipe.


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.


Author(s):  
Xiao Zhou ◽  
Xiao-Fei Zhang ◽  
Dong-Yan Guo ◽  
Yan-Jun Yang ◽  
Lin Liu ◽  
...  

Objective: Lingzhu San (LZS) is a traditional Chinese medicine (TCM) prescription which can be effective in treating febrile seizures (FS) and has few researches on the mechanisms. In order to better guide the clinical use of LZS, we used the research ideas and methods of network pharmacology to find the potential core compounds, targets and pathways of LZS in the complex TCM system for the treatment of FS, and predict the mechanism. Materials and Methods: Databases such as BATMAN, TCMSP, TCMID, and SWISS TARGET are used to mine the active compounds and targets of LZS, and the target information of FS was obtained through GENECARDS and OMIM. Using Venny2.1.0 and Cytoscape software to locked the potential core compounds and targets of FS. The R language and ClusterProfiler software package were adopt to enrich and analyze the KEGG and GO pathways of the core targets and the biological processes and potential mechanisms of the core targets were revealed. Results: 187 active compounds and 2113 target proteins of LZS were collected. And 38 potential core compounds, 35 core targets and 775 metabolic and functional pathways were screened which involved in mediating FS. Finally, the role of the core compounds, targets and pivotal pathways of LZS regulated FS in the pathogenesis and therapeutic mechanism of FS was discussed and clarified. Conclusions: In this paper, the multi-compounds, multi-targets and multi-pathways mechanism of LZS in the treatment of FS was preliminarily revealed through the analysis of network pharmacology data, which is consistent with the principle of multi-compounds compatibility of TCM prescriptions and unified treatment of diseases from multiple angles, and it provides a new way for TCM to treat complex diseases caused by multiple factors.


2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110167
Author(s):  
Xing-Pan Wu ◽  
Tian-Shun Wang ◽  
Zi-Xin Yuan ◽  
Yan-Fang Yang ◽  
He-Zhen Wu

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.


2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098213
Author(s):  
Xiaodong Deng ◽  
Yuhua Liang ◽  
Jianmei Hu ◽  
Yuhui Yang

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.


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