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基于机器学习和分子动力学模拟的特征基因和草药化合物的鉴定,用于治疗牛皮

Wenchao Dan¹, Shuying Lv¹, Wenya Gao²

¹Department of Dermatological, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China.

Journal of biomolecular structure & dynamics

|February 12, 2024

概括

这项研究确定了治疗牛皮的关键基因和天然化合物. 八种稳定的草药化合物-基因组合显示出有效管理牛皮的前途.

科学领域:

皮肤病学和计算生物学
药物基因组学和草药学研究研究

背景情况:

牛皮带来了重大的经济和心理挑战,其病因和发病原因仍未完全理解.
草药化合物为牛皮治疗提供了潜在的治疗途径.

研究的目的:

为了识别与牛皮相关的特征基因.
探索可能针对这些已识别的基因的潜在草药化合物.
以计算方式选和验证用于牛皮治疗的有希望的草药化合物基因相互作用.

主要方法:

在基因表达数据集上利用机器学习算法 (随机森林,神经网络,支持矢量机) 来识别与牛皮相关的基因.
使用外部数据集验证已识别的基因,并从多个数据库中收集化合物目标.
进行虚拟选,分子对接和分子动力学模拟,以评估化合物-基因相互作用.

主要成果:

从1270个差异基因中确定了12个特征基因,在数据集中进行了验证.
发现了牛皮基因之间的143个交叉点和59个已识别的草药化合物的点.
发现了8种高度关键和稳定的蛋白质配体组合,包括AKR1B10-阿斯蒂尔宾和IL36G-阿斯蒂尔宾,用于潜在的牛皮治疗.

结论:

这项研究为牛皮治疗开发提供了一个新的计算视角.
鉴定的特征基因和特定的草药化合物需要进一步研究以获得临床应用.
突出了自然化合物的治疗潜力,这些化合物针对牛皮的关键遗传途径.

关键词:

牛皮病是什么意思牛皮病生物信息学是一种生物信息学.机器学习是机器学习.分子动力学模拟模拟网络药理学网络药理学

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