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黄连素改善衰老相关认知功能障碍的疗效及机制:基于网络药理学的研究

The efficacy and mechanism of berberine in improving aging-related cognitive dysfunction: A study based on network pharmacology.

作者信息

Yao Jiuxiu, Wei Wei, Wen Jiayu, Cao Yu, Li Hao

机构信息

College of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.

Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

出版信息

Front Neurosci. 2023 Jan 20;17:1093180. doi: 10.3389/fnins.2023.1093180. eCollection 2023.

DOI:10.3389/fnins.2023.1093180
PMID:36743801
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9895386/
Abstract

OBJECTIVE

To analyze the effects and mechanisms of berberine in the treatment of aging-related cognitive dysfunction based on network pharmacology methods, molecular docking techniques, and animal experiments.

METHODS

A mouse model of cognitive dysfunction was constructed by subcutaneous injection of D-galactose (D-gal) for 10 weeks, and the neuroprotective effects of berberine on aging-related cognitive dysfunction mice were evaluated by the Morris water maze (MWM) and immunofluorescence staining. The targets of berberine were obtained by SwissTargetPrediction, GeneCards, and PharmMapper. Putative targets of cognitive dysfunction were obtained by GeneCards, TTD, and DrugBank database. The STRING database and Cytoscape software were applied for protein-protein interaction (PPI) analysis and further screening of core targets. The DAVID database was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analysis to clarify the biological processes and pathways involved in the intersection targets, and AutoDockTools was adopted for molecular docking verification of core targets. Finally, the core genes were validated using real-time quantitative PCR.

RESULTS

The MWM results showed that treatment with berberine significantly improved spatial learning and memory in mice with cognitive decline induced by D-gal. Immunofluorescence staining indicated that berberine modified the levels of aging-related markers in the brain. A total of 386 berberine putative targets associated with cognitive dysfunction were identified based on the public database. The core targets of berberine for improving cognitive function, include , , , , , , , and . GO enrichment and KEGG pathway enrichment analyses indicated that the mechanism of berberine in the treatment of aging-related cognitive dysfunction is attributed to pathways such as PI3K-AKT and MAPK pathways. experiments further confirmed that , , , and were involved in the neuroprotective actions of berberine.

CONCLUSION

This study reveals the multi-target and multi-pathway effects of berberine on regulating aging-related cognitive dysfunction, which provides preclinical evidence and may promote new drug development in mitigating cognitive dysfunction.

摘要

目的

基于网络药理学方法、分子对接技术及动物实验,分析黄连素治疗衰老相关认知功能障碍的作用及机制。

方法

通过皮下注射D-半乳糖(D-gal)10周构建认知功能障碍小鼠模型,采用莫里斯水迷宫(MWM)和免疫荧光染色评估黄连素对衰老相关认知功能障碍小鼠的神经保护作用。通过SwissTargetPrediction、GeneCards和PharmMapper获取黄连素的作用靶点。通过GeneCards、TTD和DrugBank数据库获取认知功能障碍的潜在靶点。应用STRING数据库和Cytoscape软件进行蛋白质-蛋白质相互作用(PPI)分析并进一步筛选核心靶点。使用DAVID数据库进行京都基因与基因组百科全书(KEGG)和基因本体(GO)富集分析,以阐明交集靶点所涉及的生物学过程和途径,并采用AutoDockTools对核心靶点进行分子对接验证。最后,使用实时定量PCR验证核心基因。

结果

MWM结果显示,黄连素治疗显著改善了D-gal诱导的认知功能下降小鼠的空间学习和记忆能力。免疫荧光染色表明,黄连素改变了大脑中衰老相关标志物的水平。基于公共数据库共鉴定出386个与认知功能障碍相关的黄连素潜在靶点。黄连素改善认知功能的核心靶点包括……。GO富集和KEGG通路富集分析表明,黄连素治疗衰老相关认知功能障碍的机制归因于PI3K-AKT和MAPK通路等途径。……实验进一步证实……参与了黄连素的神经保护作用。

结论

本研究揭示了黄连素在调节衰老相关认知功能障碍方面的多靶点和多途径作用,为减轻认知功能障碍提供了临床前证据,并可能促进新药开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/09f9e08c2f94/fnins-17-1093180-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/3ca2d78b07e2/fnins-17-1093180-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/62b3435ae90a/fnins-17-1093180-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/e09218766094/fnins-17-1093180-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/dbf55720738a/fnins-17-1093180-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/b4f3ced8b262/fnins-17-1093180-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/09f9e08c2f94/fnins-17-1093180-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/3ca2d78b07e2/fnins-17-1093180-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/62b3435ae90a/fnins-17-1093180-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/e09218766094/fnins-17-1093180-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/dbf55720738a/fnins-17-1093180-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/b4f3ced8b262/fnins-17-1093180-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/41ff/9895386/09f9e08c2f94/fnins-17-1093180-g006.jpg

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