scholarly journals A new prospect for the treatment of nephrotic syndrome based on network pharmacology analysis

2022 ◽  
Author(s):  
Rini Varghese ◽  
Anuradha Majumdar
Keyword(s):  
Nephrotic Syndrome ◽  
Network Pharmacology

Uncovering the mechanism of Astragali Radix against nephrotic syndrome by intergrating lipidomics and network pharmacology

Phytomedicine ◽  
2020 ◽  
Vol 77 ◽  
pp. 153274
Author(s):  
Ai-Ping Li ◽  
Liu Yang ◽  
Ting Cui ◽  
Li-Chao Zhang ◽  
Yue-Tao Liu ◽  
...  
Keyword(s):  
Nephrotic Syndrome ◽  
Network Pharmacology ◽  
Astragali Radix

scholarly journals Integrated Metabolomics and Network Pharmacology to Establish the Action Mechanism of Qingrekasen Granule for Treating Nephrotic Syndrome

2021 ◽  
Vol 12 ◽  
Author(s):  
Yanfen Duan ◽  
Dongning Zhang ◽  
Yan Ye ◽  
Sili Zheng ◽  
Ping Huang ◽  
...  
Keyword(s):  
Nephrotic Syndrome ◽  
Molecular Docking ◽  
Metabolic Pathways ◽  
Underlying Mechanism ◽  
Network Pharmacology ◽  
Glutamate Metabolism ◽  
Active Components ◽  
Glomerular Permeability ◽  
Expression Levels ◽  
Integrated Metabolomics

Nephrotic syndrome (NS) is a clinical syndrome resulting from abnormal glomerular permeability, mainly manifesting as edema and proteinuria. Qingrekasen granule (QRKSG), a Chinese Uyghur folk medicine, is a single-flavor preparation made from chicory (Cichorium intybus L.), widely used in treating dysuria and edema. Chicory, the main component in QRKSG, effectively treats edema and protects kidneys. However, the active components in QRKSG and its underlying mechanism for treating NS remain unclear. This study explored the specific mechanism and composition of QRKSG on an NS rat model using integrated metabolomics and network pharmacology. First, metabolomics explored the relevant metabolic pathways impacted by QRKSG in the treatment of NS. Secondly, network pharmacology further explored the possible metabolite targets. Afterward, a comprehensive network was constructed using the results from the network pharmacology and metabolomics analysis. Finally, the interactions between the active components and targets were predicted by molecular docking, and the differential expression levels of the target protein were verified by Western blotting. The metabolomics results showed “D-Glutamine and D-glutamate metabolism” and “Alanine, aspartate, and glutamate metabolism” as the main targeted metabolic pathways for treating NS in rats. AKT1, BCL2L1, CASP3, and MTOR were the core QRKSG targets in the treatment of NS. Molecular docking revealed that these core targets have a strong affinity for flavonoids, terpenoids, and phenolic acids. Moreover, the expression levels of p-PI3K, p-AKT1, p-mTOR, and CASP3 in the QRKSG group significantly decreased, while BCL2L1 increased compared to the model group. These findings established the underlying mechanism of QRKSG, such as promoting autophagy and anti-apoptosis through the expression of AKT1, CASP3, BCL2L1, and mTOR to protect podocytes and maintain renal tubular function.

scholarly journals Research on the Mechanism of Guizhi to Treat Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dan He ◽  
Qiang Li ◽  
Guangli Du ◽  
Jijia Sun ◽  
Guofeng Meng ◽  
...  
Keyword(s):  
Nephrotic Syndrome ◽  
Molecular Docking ◽  
Active Component ◽  
Network Pharmacology ◽  
Protective Mechanism ◽  
Ppi Network ◽  
Active Components ◽  
Active Compounds ◽  
The Core ◽  
Target Network

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.

Cytokine polymorphisms and nephrotic syndrome

2002 ◽  
Vol 102 (5) ◽  
pp. 513 ◽  
Author(s):  
PETER W. MATHIESON
Keyword(s):  
Nephrotic Syndrome

Hereditary nephritis with the nephrotic syndrome

1970 ◽  
Vol 125 (3) ◽  
pp. 459-461 ◽  
Author(s):  
J. H. Felts
Keyword(s):  
Nephrotic Syndrome ◽  
Hereditary Nephritis
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