Si-Ni-San对焦虑失眠的多目标机制:网络药理学和分子对接分析的一个例子
Chih Ting Lin1,2, Hsin Yi Lin3, Wen Huang Peng3
1The School of Chinese Medicine for Post-Baccalaureate, I-Shou University, No. 8, Yida Rd., Jiaosu Village Yanchao District, Kaohsiung City, 82445, Taiwan.
Current medicinal chemistry
|October 16, 2024
概括
Si-Ni-San (SNS) 可以通过向多种化合物,蛋白质和途径来治疗焦虑性失眠. 这项网络药理学和分子对接研究为SNS提供了理论基础.
科学领域:
- 传统中国医药 传统中国医药
- 计算药理学计算药理学
- 网络药理学 网络药理学
背景情况:
- 焦虑失眠是一种复杂的疾病,治疗选择有限.
- Si-Ni-San (SNS) 是一种传统的草药配方,具有潜在的治疗益处.
研究的目的:
- 通过网络药理学和分子对接,阐明SNS在治疗焦虑失眠中的多目标,多途径机制.
- 在SNS公式中识别关键活性化合物及其相应的目标.
主要方法:
- 使用Cytoscape.net进行网络构建 (组件-组合物-目标) 和可视化.
- 蛋白与蛋白相互作用 (PPI) 网络分析.
- 基因本体学 (GO) 和基因和基因组的京都百科全书 (KEGG) 路径丰富分析.
- 分子对接模拟以验证连接体-受体相互作用.
主要成果:
- 确定了31种活性化合物和59种与焦虑性失眠相关的基因.
- 核心目标包括AKT1,IL6,TNF,SLC6A4,MAOA和GABRA2.2等.
- 通过神经活性联体受体相互作用和突触通路,SNS可以通过减少炎症,神经退行和神经元亡来缓解焦虑性失眠.
- 分子对接证实了关键化合物 (例如,异胺,β-醇) 具有核心点的稳定结合构造.
结论:
- 脑神经系统表现出一种多组合,多目标,多途径的机制来缓解与焦虑相关的睡眠障碍.
- 网络药理学和分子对接为SNS的抗焦虑和抗失眠作用提供了理论验证.
- 这项计算研究为未来对SNS疗效的实验研究奠定了基础.
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