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Exploring the targets and molecular mechanism of glycyrrhetinic acid against diabetic nephropathy based on network pharmacology and molecular docking.
Meng, Fan-Di; Yuan, Ling; Xu, Duo-Jie; Che, Meng-Ying; Hou, Shao-Zhang; Lu, Dou-Dou; Liu, Wen-Jing; Nan, Yi.
Afiliación
  • Meng FD; Traditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Yuan L; Key Laboratory of Ningxia Ethnomedicine Modernization, Ministry of Education, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Xu DJ; College of Pharmacy, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Che MY; Traditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Hou SZ; Traditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Lu DD; Ningxia Key Laboratory of Craniocerebral Diseases, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Liu WJ; Traditional Chinese Medicine College, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
  • Nan Y; Key Laboratory of Ningxia Ethnomedicine Modernization, Ministry of Education, Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China.
World J Diabetes ; 14(11): 1672-1692, 2023 Nov 15.
Article en En | MEDLINE | ID: mdl-38077799
ABSTRACT

BACKGROUND:

Diabetic nephropathy (DN) stands as the most prevalent chronic microvascular complication of diabetes mellitus. Approximately 50% of DN patients progress to end-stage renal disease, posing a substantial health burden.

AIM:

To employ network pharmacology and molecular docking methods to predict the mechanism by which glycyrrhetinic acid (GA) treats DN, subsequently validating these predictions through experimental means.

METHODS:

The study initially identified GA targets using Pharm Mapper and the TCMSP database. Targets relevant to DN were obtained from the Genecards, OMIM, and TTD databases. The Venny database facilitated the acquisition of intersecting targets between GA and DN. The String database was used to construct a protein interaction network, while DAVID database was used to conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) analysis. Molecular docking experiments were performed using Autodock software with selected proteins. Experimental validation was conducted using renal proximal tubular cells (HK-2) as the study subjects. A hyperglycemic environment was simulated using glucose solution, and the effect of GA on cell viability was assessed through the cell counting kit-8 method. Flow cytometry was employed to detect cell cycle and apoptosis, and protein immunoblot (western blot) was used to measure the expression of proteins of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway and insulin resistance pathway, including insulin receptor (INSR), PI3K, p-PI3K, AKT, p-AKT, and glycogen synthase kinase-3 (GSK3).

RESULTS:

A total of 186 intersecting targets between GA and DN were identified, which were associated with 144 KEGG-related enrichment pathways, 375 GO biological process entries, 45 GO cellular component entries, and 112 GO cellular function entries. Molecular docking demonstrated strong binding of GA to mitogen-activated protein kinase (MAPK)-1, SRC, PIK3R1, HSP90AA1, CASPASE9, HARS, KRAS, and MAPK14. In vitro experiments revealed that GA inhibited HK-2 cell viability, induced cell cycle arrest at the G2/M phase, and reduced apoptosis with increasing drug concentration. Western blot analysis showed that GA differentially up-regulated GSK3 protein expression, up-regulated AKT/p-AKT expression, down-regulated INSR, AKT, p-AKT, PI3K, and p-PI3K protein expression, and reduced p-PI3K/PI3K levels under high glucose conditions.

CONCLUSION:

GA may protect renal intrinsic cells by modulating the PI3K/AKT signaling pathway, thereby inhibiting HK-2 cell viability, reducing HK-2 cell apoptosis, and inducing cell cycle arrest at the G0/G1 phase.
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: World J Diabetes Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: World J Diabetes Año: 2023 Tipo del documento: Article