基于NMR的生物化学2D异构变量分析:一种有针对性的方法,用于识别复杂混合物中的生物活性化合物
Sigrid Adelsberger1,2, Alexander F Perhal1, Lorenza Bertaina1,2
1Division of Pharmacognosy, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria.
Analytical chemistry
|October 12, 2025
概括
本研究引入了一种新的2DNMR异构变量分析 (HetCA) 工作流程,以有效地识别复杂天然提取物中的生物活性化合物. 这种方法加速了调节RORγ和TGR5受体的化合物的发现.
科学领域:
- 自然产品化学 自然产品化学
- 生物化学 生化学
- 频谱学是一种光谱学.
背景情况:
- 综合生物活性和光谱数据的生物化学测量方法可以简化生物活性化合物发现.
- 复杂的天然提取物和类似的类似物带来了挑战,使得隔离耗时且资源密集.
研究的目的:
- 开发和验证基于二维核磁共振 (NMR) 的异构共变性分析 (HetCA) 工作流程.
- 在复杂的混合物中识别与生物活性相关的化学特征.
- 为了能够有针对性地分离调节RORγ和TGR5.5的生物活性化合物.
主要方法:
- 建立了一个基于2D NMR的HetCA工作流.
- 使用人工混合的五环三烯用于概念验证的验证.
- 对与视网膜酸受体相关的孤儿受体玛 (RORγ) 和G蛋白结合胆酸受体 (TGR5) 的调节活性进行选的样本.
- 将工作流应用于富含三烯的 * Eriobotrya japonica * 叶子提取物.
主要成果:
- 使用人工混合物成功验证了2D NMR HetCA工作流.
- 从E. japonica提取物中确定了调节RORγ和/或TGR5.5的生物活性成分.
- 在复杂的自然基质中证明了活性化合物的有针对性和准确的识别.
结论:
- 开发的生物化学 2D NMR HetCA 方法是有效的,用于识别复杂的天然产品中的生物活性成分.
- 这种工作流显著提高了针对药物发现的有针对性的隔离策略的效率.
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