已发表论文

综合代谢组学和网络药理学揭示甘豆灵片抗铜超载致威尔逊氏病大鼠神经元损伤的机制

 

Authors Chen L, Xu WY, Chen H, Han YQ, Zhang YT

Received 15 March 2023

Accepted for publication 6 June 2023

Published 13 June 2023 Volume 2023:17 Pages 1763—1782

DOI https://doi.org/10.2147/DDDT.S409691

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Jianbo Sun

Purpose: Gandouling Tablets (GDL), a proprietary Chinese medicine, have shown a preventive effect against Wilson’s disease (WD)-induced neuronal damage in previous studies. However, the potential mechanisms need additional investigation. Combining metabonomics and network pharmacology revealed the GDL pathway against WD-induced neuronal damage.
Methods: The WD rat model with a high copper load was developed, and nerve damage was assessed. Total metabonomics was used to identify distinct hippocampus metabolites and enriched metabolic pathways in MetaboAnalyst. The GDL’s possible targets against WD neuron damage were then determined by network pharmacology. Cytoscape constructed compound metabonomics and pharmacology networks. Moreover, molecular docking and Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) validated key targets.
Results: GDL reduced WD-induced neuronal injury. Twenty-nine GDL-induced metabolites may protect against WD neuron injury. According to network pharmacology, we identified three essential gene clusters, of which genes in cluster 2 had the most significant impact on the metabolic pathway. A comprehensive investigation identified six crucial targets, including UGT1A1, CYP3A4, CYP2E1, CYP1A2, PIK3CB, and LPL, and their associated core metabolites and processes. Four targets reacted strongly with GDL active components. GDL therapy improved five targets’ expression.
Conclusion: This collaborative effort revealed the mechanisms of GDL against WD neuron damage and a way to investigate the potential pharmacological mechanisms of other Traditional Chinese Medicine (TCM).
Keywords: GDL, metabonomics, network pharmacology, mechanisms