Department of Physiology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
Department of Pharmacology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
Int J Mol Sci. 2024 Sep 24;25(19):10259. doi: 10.3390/ijms251910259.
Depression is a common neuropsychiatric disease which brings an increasing burden to all countries globally. Baicalin, a flavonoid extracted from the dried roots of Scutellaria, has been reported to exert anti-inflammatory, antioxidant, and neuroprotective effects in the treatment of depression. However, the potential biological mechanisms underlying its antidepressant effect are still unclear. In the present study, we conducted extensive research on the potential mechanisms of baicalin's antidepressant effect using the methods of network pharmacology, including overlapped terms-based analysis, protein-protein interaction (PPI) network topology analysis, and enrichment analysis. Moreover, these results were further verified through molecular docking, weighted gene co-expression network analysis (WGCNA), differential gene expression analysis, and subsequent animal experiments. We identified forty-one genes as the targets of baicalin in the treatment of depression, among which , , , , and have higher centrality in the more core position. Meanwhile, the roles of peripheral genes derived from direct potential targets were also observed. Our study suggested that biological processes, such as inflammatory reaction, apoptosis, and oxidative stress, may be involved in the therapeutic process of baicalin on depression. These mechanisms were validated at the level of structure, gene, protein, and signaling pathway in the present study. Taken together, these findings propose a new perspective on the potential mechanisms underlying baicalin's antidepressant effect, and also provide a new basis and clarified perspective for its clinical application.
抑郁症是一种常见的神经精神疾病,给全球各国带来了日益沉重的负担。黄芩素是从黄芩的干燥根中提取的一种黄酮类化合物,已被报道具有抗炎、抗氧化和神经保护作用,可用于治疗抑郁症。然而,其抗抑郁作用的潜在生物学机制仍不清楚。在本研究中,我们使用网络药理学的方法,包括重叠术语分析、蛋白质-蛋白质相互作用(PPI)网络拓扑分析和富集分析,对黄芩素抗抑郁作用的潜在机制进行了广泛的研究。此外,这些结果还通过分子对接、加权基因共表达网络分析(WGCNA)、差异基因表达分析和随后的动物实验进行了验证。我们确定了 41 个基因作为黄芩素治疗抑郁症的靶点,其中 、 、 、 和 在更核心的位置具有更高的中心性。同时,也观察到了来自直接潜在靶点的外围基因的作用。我们的研究表明,生物过程,如炎症反应、细胞凋亡和氧化应激,可能参与了黄芩素治疗抑郁症的过程。这些机制在本研究的结构、基因、蛋白质和信号通路水平上得到了验证。总之,这些发现为黄芩素抗抑郁作用的潜在机制提供了新的视角,也为其临床应用提供了新的依据和明确的思路。