解读炎症和神经退行性疾病中与亡相关的途径:基于网络药理学的药物发现方法
Abdullah Alkhammash1, Ghallab Alotaibi1, Aliyah Algethami2
1Department of Pharmacology, College of Pharmacy, Shaqra University, Shaqra, 11961, Saudi Arabia.
European journal of pharmacology
|October 13, 2025
概括
这项研究使用了网络药理学和分子对接来识别药用植物中可能治疗阿尔茨海默病 (AD) 的天然化合物. 关键的植物化学物质,如Quercetin,通过与关键疾病点相互作用,显示出潜在的神经保护作用.
科学领域:
- 计算生物学 计算生物学
- 药理学 药理学是指药理学的学科.
- 神经科学是一个神经科学.
背景情况:
- 神经退行性疾病,特别是阿尔茨海默氏症 (AD),在全球面临重大健康挑战,治疗选择有限.
- 来自药用植物的植物化学物质因其对抗复杂的神经退行性病理的潜力而受到越来越多的关注.
研究的目的:
- 通过网络药理学和分子对接,探索来自12种民族医药植物的生物活性化合物的治疗潜力,用于阿尔茨海默病.
- 确定关键的植物衍生化合物及其涉及阿尔茨海默病病理学的分子标.
主要方法:
- 利用网络药理学在1218个潜在目标和AD相关基因之间识别了479个重叠的目标.
- 进行了蛋白质与蛋白质相互作用 (PPI) 网络分析,以确定枢纽基因 (例如,AKT1,CASP3,TNF,BCL2).
- 进行了分子对接和模拟,以评估植物化学物质 (例如,Quercetin,Luteolin,Rosmarinic acid) 与已确定目标的结合 afinities.
主要成果:
- 确定了AKT1,CASP3,TNF和BCL2作为调节阿尔茨海默病的中心枢纽基因.
- 基因本体学和KEGG通路分析揭示了亡,炎症和突触信号的参与.
- 选择的植物化学物质,特别是奎尔丁和罗斯马林酸,与TNF和AKT1等点表现出强烈的结合 afinities,表明神经保护潜力.
结论:
- 这种综合计算方法为自然化合物对抗阿尔茨海默病的神经治疗作用提供了机械洞察力.
- 这些发现支持植物化学品的多目标监管潜力,并为实验验证和药物开发策略铺平了道路.
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