Abstract：
With significant advancements in high-resolution mass spectrometry, there has been a substantial increase in the amount of chemical component data acquired from natural products. Therefore, the rapid and efficient extraction of valuable mass spectral information from large volumes of high-resolution mass spectrometry data holds crucial significance. This study illustrates a targeted annotation of the metabolic products of alkaloid and sesquiterpene components from Dendrobium nobile (D. nobile) aqueous extract in mice serum through the integration of an in-houses database, R programming, a virtual metabolic product library, polygonal mass defect filtering, and Kendrick mass defect strategies. The research process involved initially establishing a library of alkaloids and sesquiterpenes components and simulating 71 potential metabolic reactions within the organism using R programming, thus creating a virtual metabolic product database. Subsequently, employing the virtual metabolic product library allowed for polygonal mass defect filtering, rapidly screening 1705 potential metabolites of alkaloids and 3044 potential metabolites of sesquiterpenes in the serum. Furthermore, based on the chemical composition database of D. nobile and online mass spectrometry databases, 95 compounds, including alkaloids, sesquiterpenes, and endogenous components, were characterized. Finally, utilizing Kendrick mass defect analysis in conjunction with known alkaloids and sesquiterpenes targeted screening of 209 demethylation, methylation, and oxidation products in phase I metabolism, and 146 glucuronidation and glutathione conjugation products in phase II metabolism. This study provides valuable insights for the rapid and accurate annotation of chemical components and their metabolites in vivo within natural products.
摘要：
随着高分辨率质谱的重大进步，从天然产物中获得的化学成分数据数量大幅增加。因此,从大量高分辨率质谱数据中快速有效地提取有价值的质谱信息具有至关重要的意义。本研究说明了金皮石斛生物碱和倍半萜组分代谢产物的靶向注释（D。nobile)通过整合内部数据库在小鼠血清中的水提取物，R编程,一个虚拟的代谢产品库，多边形质量缺陷过滤，和肯德里克质量缺陷策略。研究过程涉及最初建立生物碱和倍半萜组分的文库，并使用R编程模拟生物体内71个潜在的代谢反应，从而创建一个虚拟代谢产品数据库。随后，采用允许多边形质量缺陷过滤的虚拟代谢产品库，快速筛选血清中1705种生物碱的潜在代谢产物和3044种倍半萜的潜在代谢产物。此外，基于D.nobile的化学成分数据库和在线质谱数据库，95个化合物，包括生物碱,倍半萜,和内源性成分，被表征。最后,利用Kendrick质量缺陷分析结合已知生物碱和倍半萜靶向筛选209去甲基化，甲基化,和第一阶段代谢中的氧化产物，和146个葡萄糖醛酸化和谷胱甘肽缀合产物在II期代谢中。这项研究为快速准确地注释天然产物中的化学成分及其代谢产物提供了有价值的见解。
