Network pharmacology and molecular docking analysis on molecular targets: Mechanisms of baicalin and baicalein against hyperuricemic nephropathy

2021 ◽  
pp. 115594
Author(s):  
Huilong Xiang ◽  
Huan Lei ◽  
Ziyuan Liu ◽  
Yongjie Liu ◽  
Yang Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Molecular Targets ◽  
Network Pharmacology ◽  
Docking Analysis ◽  
Molecular Docking Analysis

scholarly journals Application of Network Pharmacology to Elucidate The Potential Mechanism of Finger Citron Against Obesity

2020 ◽  
Author(s):  
Zhen Wu ◽  
Yujiao Yang ◽  
Yao Wei ◽  
Xu-guang Hu
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Active Components ◽  
Docking Analysis ◽  
Treatment Of Obesity ◽  
Molecular Docking Analysis

Abstract Background: Finger citron (FS) is one of many traditional Chinese herbs that have been used to treat obesity. However, the active components and potential targets of FS in improving obesity remain unclear. Methods：The aim of this study was to elucidate the pharmacological effects and mechanisms of FS on obesity using network pharmacology analysis. We used network pharmacology to determine the active components, potential targets and mechanisms in the treatment of obesity.Results：We identified 25 active ingredients of FS such as diosmetin, hesperidin and sitosterol-alpha1 with important biological effect. A total of 258 key targets were screened, containing TNF，NOS2, MAPK8 which were found to be enriched in 27 signaling pathways, such as apoptosis, TNF, PPAR and AKT1, and Insulin resistance signaling pathways. Moreover, molecular docking analysis showed that the main ingredients were tightly bound to the core targets, further confirming the effects of weight loss. Conclusion: Based on network pharmacology and molecular docking analysis, our study provides insights into the potential mechanism of FS in ameliorating obesity after screening for associated key target genes and signaling pathways. These findings further provide a theoretical basis for further pharmacological research into the potential mechanism of FS in treating obesity.

scholarly journals Construction of Pharmacological Network and Molecular Docking Analysis of Key Molecular Components of Jianpi Yiqi Formula for Idiopathic Thrombocytopenic Purpura

2021 ◽  
Author(s):  
Qiming Li ◽  
Gang Deng ◽  
Yunlei He ◽  
Jiafeng Yang
Keyword(s):  
Molecular Docking ◽  
Idiopathic Thrombocytopenic Purpura ◽  
Target Genes ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Critical Pathway ◽  
Thrombocytopenic Purpura ◽  
Active Compounds ◽  
Docking Analysis ◽  
Molecular Docking Analysis

Abstract Purpose: To perform network pharmacological analysis so as to identify and screen the active ingredients of Jianpi Yiqi Formula; find its core target and explore its mechanism in the treatment of idiopathic thrombocytopenic purpura (ITP). Materials and Methods: A network pharmacology approach was used to inquire and screen the active ingredients from the Traditional Chinese Medicine System Pharmacology (TCMSP) database for potential active compounds that are commonly contained in the Jianpi Yiqi formula. The Swiss Target Prediction database was used for the prediction of the active ingredient's target of the action; the genecard database was used to search for target genes associated with ITP and to screen for target genes, in which the drug target was intersected with the disease target. Protein interaction network was constructed using string database software for GO and KEGG analysis to construct the "component/target/pathway" pharmacology network of Jianpi Yiqi granules therapy for ITP. Cytoscape 3.7.2 software was harnessed to visualize and integrate this network. The Virtua Drug web-based pharmacology website ( https://www.dockingserver.com ) was used to validate the regulatory relationship between key active compounds and critical pathway molecular signals by molecular docking. Results: Two key active ingredients, quercetin, and kaempferol, were selected from hundreds of herbal ingredients referenced in online pharmacological studies. Molecular docking analysis revealed that quercetin and kaempferol could stably bind PI3K/AKT and exert inhibitory effects, respectively. It was also speculated that PI3K/AKT/mTOR pathway might be the critical pathway for the pharmacokinetic mechanism of Jianpi Yiqi Granules. Conclusion: The present study suggests the multi-component effect characteristic of the treatment of ITP with Jianpi Yiqi granules, thus providing a theoretical basis for the clinical use of Jianpi Yiqi formula.

Network Pharmacology-based and Molecular Docking Analysis of Resveratrol’s Pharmacological Effects on Type I Endometrial Cancer

2021 ◽  
Vol 21 ◽  
Author(s):  
Zixing Zhong ◽  
Xin Guo ◽  
Yanmei Zheng
Keyword(s):  
Endometrial Cancer ◽  
Molecular Docking ◽  
In Silico ◽  
Target Genes ◽  
Network Pharmacology ◽  
Type I ◽  
Pharmacological Effects ◽  
Molecular Docking Study ◽  
Docking Analysis ◽  
Molecular Docking Analysis

Background: Resveratrol is a natural polyphenol commonly seen in foods. It has demonstrated an inhibitive effect on endometrial cancer, but the molecular action is still not known. Objective: We aimed to use network pharmacology to systematically study the possible mechanisms of resveratrol’s pharmacological effects on type I endometrial cancer. Methods: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) were used to predict resveratrol’s possible target genes. They were then converted to UniProt gene symbols. Simultaneously, type I endometrial cancer-related target genes were collected from GeneCards. All data were pooled to identify common target genes. The protein-protein interaction (PPI) network was constructed and further analyzed via STRING Online Database. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were also performed afterward. To visualise resveratrol's overall pharmacological effects on type I endometrial cancer, a network of drug components-target gene-disease (CTD) was constructed. Then, we performed in silico molecular docking study to validate the possible binding conformation between resveratrol and candidate targets. Results: There are 150 target genes of resveratrol retrieved after UniProt conversion; 122 of them shared interaction with type I endometrial cancer. Some important oncogenes and signaling pathways are involved in the process of resveratrol’s pharmacological effects on endometrioid cancer. Molecular docking analysis confirmed that hydrogen bonding and hydrophobic interaction are the main interaction between resveratrol and its targets. Conclusion: We have explored the possible underlying mechanism of resveratrol in antagonising type I endometrial cancer through a network pharmacology-based approach and in-silico verification. However, further experiments are necessary to add to the evidence identifying resveratrol as a promising anti-type I endometrial cancer agent.

scholarly journals Mechanism of Cordyceps Cicadae in Treating Diabetic Nephropathy Based on Network Pharmacology and Molecular Docking Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yi Qian ◽  
Xin Sun ◽  
Xin Wang ◽  
Xin Yang ◽  
Mengyao Fan ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Molecular Docking ◽  
Docking Studies ◽  
New Drugs ◽  
Network Pharmacology ◽  
Active Components ◽  
Docking Analysis ◽  
Discovery Studio ◽  
Cordyceps Cicadae ◽  
Molecular Docking Analysis

Objective. To systematically study the mechanism of cordyceps cicadae in the treatment of diabetic nephropathy (DN) with the method of network pharmacology and molecular docking analysis, so as to provide theoretical basis for the development of new drugs for the treatment of DN. Methods. TCMSP, Symmap, PubChem, PubMed, and CTD database were used to predict and screen the active components and therapeutic targets for DN. The network of active components and targets was drawn by Cytoscape 3.6.0, the protein-protein interaction (PPI) was analyzed by the STRING database, and the DAVID database was used for the enrichment analysis of intersection targets. Molecular docking studies were finished by Discovery Studio 3.5. Results. A total of 36 active compounds, including myriocin, guanosine, and inosine, and 378 potential targets of cordyceps cicadae were obtained. PPI network analysis showed that AKT1, MAPK8, and TP53 and other targets were related to both cordyceps cicadae and DN. GO and KEGG pathway analysis showed that these targets were mostly involved in R-HSA-450341, 157.14-3-3 cell cycle, and PDGF pathways. Docking studies suggested that myriocin can fit in the binding pocket of two target proteins (AKT1 and MAPK8). Conclusion. Active ingredients of cordyceps cicadae such as myriocin may act on DN through different targets such as AKT1, MAPK8, and TP53 and other targets, which can help to develop innovative drugs for effective treatment of DN.

scholarly journals Identifying and Verifying AR, ERBB2, and VEGFA Are the Targets of Qigesan in the Treatment of Esophageal Adenocarcinoma In Silico and In Vitro

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Dong Zhang ◽  
Lang Guo ◽  
Xiaoting Wu ◽  
Meng Luo ◽  
Xinyi Liang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Esophageal Adenocarcinoma ◽  
Chinese Mainland ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Docking Analysis ◽  
Kegg Analysis ◽  
The Chinese Mainland ◽  
Molecular Docking Analysis

The Chinese medicine Qigesan can be used to treat esophageal adenocarcinoma in the Chinese mainland widely, but its mechanism is unclear. In order to investigate the mechanism of Qigesan in the treatment of esophageal adenocarcinoma, the concept of network pharmacology was used in this study. The database named TCMSP was used to identify the active therapeutic components as well as targets of Qigesan. The TTD, OMIM, CTD, DrugBank, and GeneCards database were used to identify genes related to esophageal adenocarcinoma. In STRING database, the potential targets were imported to obtain a PPI network, and then Cytoscape software has been used to analyse the results. Subsequently, important components and targets were simulated by molecular docking. Finally, experiments on the cell have been done to verify well docking targets. A total of 124 effective compounds and 646 corresponding targets were filtered. 1478 genes were found to be related to esophageal adenocarcinoma. 68 genes were identified as potential targets for esophageal adenocarcinoma. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the 68 potential targets indicated that the genes were mainly involved in cell transcription, translation, and apoptosis and mostly expressed in cancer-related pathways. The molecular docking analysis of the hub targets with their corresponding compounds indicated that the well docking targets were AR, ERBB2, and VEGFA. The cell experiments showed that Qigesan can reduce the expression of AR, ERBB2, and VEGFA at transcription and translation level. This network pharmacology study described that the possible targets of Qigesan in treatment of esophageal adenocarcinoma were AR, ERBB2, and VEGFA.

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