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Mechanisms of Cinnamomi Cortex against Diabetes Mellitus Explored by Network Pharmacology combined with Molecular Docking and Experimental Validation.
Yu, Jianqin; Song, Zijun; Wang, Lusheng; Yang, Hongyu; Fan, Hui.
Afiliação
  • Yu J; College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
  • Song Z; Department of Pharmacy, Eye Hospital, Wenzhou Medical University, Hangzhou, 310020, China.
  • Wang L; College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
  • Yang H; Department of Pharmacy, Hangzhou Third People's Hospital, Hangzhou, 310009, China.
  • Fan H; Department of Pharmacy, Eye Hospital, Wenzhou Medical University, Hangzhou, 310020, China.
Article em En | MEDLINE | ID: mdl-39318013
ABSTRACT

OBJECTIVE:

Cinnamomi cortex (CC), a traditional Chinese herbal medicine, exhibits antidiabetic properties, yet the underlying mechanisms are not fully understood. Our study combined network pharmacology, molecular docking, and experimental validation to elucidate the antidiabetic mechanisms of CC.

METHODS:

Active components of CC and their potential antidiabetic targets were identified through TCMSP, DisGeNET, and GeneCards. The PPI networks were constructed with STRING and analyzed with Cytoscape, while GO and KEGG analyses utilized the DAVID database. Molecular docking with core targets was performed using Autodock Vina. The efficacy of CC in diabetes mellitus was evaluated through H&E staining, qPCR, and Western blot in the T2DM mouse.

RESULTS:

Eleven active components and sixty-six potential antidiabetic targets of CC were identified. The enrichment analysis revealed 288 GO terms and 37 pathways. The molecular docking showed high affinity for PPAR-γ and IL-6 receptors. In vivo studies further confirmed CC's ability to modulate PPAR-γ and IL-6, contributing to its antidiabetic effects.

CONCLUSION:

CC manages diabetes by regulating the PPAR-γ pathway and suppressing associated inflammation, providing a multi-pathway therapeutic approach.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article