Exploring Gastrodin Against Aging-Related Genes in Alzheimer’s Disease by Integrated Bioinformatics Analysis and Machine Learning

基因 小桶 计算生物学 天麻素 生物 基因调控网络 交互网络 遗传学 基因组 机器学习 生物信息学 基因预测 人工智能 对接(动物) 基因表达谱 转录因子 计算机科学 随机森林 生物网络 基因本体论
作者
Lipeng Zhou,Xinying Chen,Shuang Liang,Jiulong Yan,Lianhu Sun,Yaping Li,Xingliang Chen,Zhirong Sun
出处
期刊:International Journal of Molecular Sciences [Multidisciplinary Digital Publishing Institute]
卷期号:26 (18): 9097-9097 被引量:6
标识
DOI:10.3390/ijms26189097
摘要

Gastrodin is the main active ingredient of Gastrodia elata Blume, known for its prominent neuroprotective effects, especially in Alzheimer’s disease. Meanwhile, aging is a critical risk factor in age-related diseases, including AD. Now, the underlying mechanisms of gastrodin against aging-related genes in Alzheimer’s disease remain unclear. Our study aimed to identify and validate the molecular mechanisms of gastrodin on aging-related genes in Alzheimer’s disease. Firstly, we analyzed gene expression datasets from GEO in NCBI, and weighted gene co-expression network analysis (WGCNA) was used to identify the intersected genes with differentially expressed genes (DEGs) and aging genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses and protein–protein interaction (PPI) network were performed to analyze and evaluate the intersected genes to screen key genes. Subsequently, we used machine learning techniques to screen hub genes and subcellular localization to confirm the reliability of the hub genes. Finally, molecular docking and molecular dynamics simulation were combined to explore the binding interactions between core targets and gastrodin. We identified 29 intersecting genes among DEGs of AD, key module genes of AD, and aging genes. Next, nine common hub genes were identified by four algorithms of the cytoHubba plug-in. Four hub genes, GFAP, NPY, SNAP25, and SST, were found as possibly hub aging-related genes in Alzheimer’s disease from machine algorithms by adopting the random forest, LASSO, SVM, and Boruta models. Among them, GFAP showed marked upregulation, while NPY, SNAP25, and SST exhibited significant downregulation (p < 0.05). Finally, molecular docking and molecular dynamics simulation exhibited that gastrodin has an excellent affinity in docking with SNAP25. This study demonstrates that SNAP25 can be considered a key aging-related gene in AD, and gastrodin could treat AD by targeting specific genes and signaling pathways. These findings provide critical insights for the clinical application of gastrodin.
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