Shi Xin, Li Lingling, Liu Zhiyao, Wang Fangqi, Huang Hailiang
Shandong University of Traditional Chinese Medicine, Jinan City, Shandong Province, China.
Shandong University of Traditional Chinese Medicine, 4655 Guyunhu Street, Changqing District, Jinan City, Shandong Province, China.
Ther Adv Endocrinol Metab. 2023 Sep 27;14:20420188231187493. doi: 10.1177/20420188231187493. eCollection 2023.
Metformin, which has been shown to be highly effective in treating type 2 diabetes (T2D), is also believed to be valuable for Alzheimer's disease (AD). Computer simulation techniques have emerged as an innovative approach to explore mechanisms.
To study the potential mechanism of metformin action in AD and T2D.
The chemical structure of metformin was obtained from PubChem. The targets of metformin were obtained from PubChem, Pharm Mapper, Batman, SwissTargetPrediction, DrugBank, and PubMed. The pathogenic genes of AD and T2D were retrieved from the GeneCards, OMIM, TTD, Drugbank, PharmGKB, and DisGeNET. The intersection of metformin with the targets of AD and T2D is represented by a Venn diagram. The protein-protein interaction (PPI) and core targets networks of intersected targets were constructed by Cytoscape 3.7.1. The enrichment information of GO and Kyoto Encyclopedia of Gene and Genomics (KEGG) pathways obtained by the Metascape was made into a bar chart and a bubble diagram. AutoDockTools, Pymol, and Chem3D were used for the molecular docking. Gromacs software was used to perform molecular dynamics (MD) simulation of the best binding target protein.
A total of 115 key targets of metformin for AD and T2D were obtained. GO analysis showed that biological process mainly involved response to hormones and the regulation of ion transport. Cellular component was enriched in the cell body and axon. Molecular function mainly involved kinase binding and signal receptor regulator activity. The KEGG pathway was mainly enriched in pathways of cancer, neurodegeneration, and endocrine resistance. Core targets mainly included TP53, TNF, VEGFA, HIF1A, IL1B, IGF1, ESR1, SIRT1, CAT, and CXCL8. The molecular docking results showed best binding of metformin to CAT. MD simulation further indicated that the CAT-metformin complex could bind well and converge relatively stable at 30 ns.
Metformin exerts its effects on regulating oxidative stress, gluconeogenesis and inflammation, which may be the mechanism of action of metformin to improve the common pathological features of T2D and AD.
二甲双胍已被证明在治疗2型糖尿病（T2D）方面非常有效，人们也认为它对阿尔茨海默病（AD）有价值。计算机模拟技术已成为探索机制的一种创新方法。
研究二甲双胍在AD和T2D中的潜在作用机制。
从PubChem获取二甲双胍的化学结构。从PubChem、Pharm Mapper、Batman、SwissTargetPrediction、DrugBank和PubMed获取二甲双胍的靶点。从GeneCards、OMIM、TTD、Drugbank、PharmGKB和DisGeNET检索AD和T2D的致病基因。用维恩图表示二甲双胍与AD和T2D靶点的交集。用Cytoscape 3.7.1构建相交靶点的蛋白质-蛋白质相互作用（PPI）和核心靶点网络。将通过Metascape获得的GO和京都基因与基因组百科全书（KEGG）通路的富集信息制成柱状图和气泡图。使用AutoDockTools、Pymol和Chem3D进行分子对接。使用Gromacs软件对最佳结合靶蛋白进行分子动力学（MD）模拟。
共获得115个二甲双胍对AD和T2D的关键靶点。GO分析表明，生物学过程主要涉及对激素的反应和离子转运的调节。细胞成分在细胞体和轴突中富集。分子功能主要涉及激酶结合和信号受体调节活性。KEGG通路主要富集在癌症、神经退行性变和内分泌抵抗通路中。核心靶点主要包括TP53、TNF、VEGFA、HIF1A、IL1B、IGF1、ESR1、SIRT1、CAT和CXCL8。分子对接结果显示二甲双胍与CAT的结合最佳。MD模拟进一步表明，CAT-二甲双胍复合物在30 ns时能很好地结合并相对稳定地聚集。
二甲双胍通过调节氧化应激、糖异生和炎症发挥作用，这可能是二甲双胍改善T2D和AD共同病理特征的作用机制。
