4.6 Article

A molecular networking-assisted automatic database screening strategy for comprehensive annotation of small molecules in complex matrices

期刊

JOURNAL OF CHROMATOGRAPHY A
卷 1710, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.chroma.2023.464417

关键词

Database screening; Huangqi-Danshen herb pair; Liquid chromatography-mass spectrometry; Molecular networking; Python programming software

向作者/读者索取更多资源

In this study, a molecular networking assisted automatic database screening (MN/auto-DBS) strategy was developed to annotate multiple small molecules within complex matrices. The strategy combines MS1 exact mass screening and MS2 similarity analysis to identify compounds. Results from both strategies were merged and manually curated for correct structural assignment.
Liquid chromatography-tandem with high-resolution mass spectrometry (LC-HRMS) has proven challenging for annotating multiple small molecules within complex matrices due to the complexities of chemical structure and raw LC-HRMS data, as well as limitations in previous literatures and reference spectra related to those molecules. In this study, we developed a molecular networking assisted automatic database screening (MN/auto-DBS) strategy to examine the combined effect of MS1 exact mass screening and MS2 similarity analysis. We compiled all previously reported compounds from the relevant literatures. With the development of a Python software, the in-house database (DB) was created by automatically calculating the m/z and data from experimental MS1 hits were rapid screened with DB. We then performed a feature-based molecular network analysis on the auto-MS2 data for supplementary identification of unreported compounds, including clustered FBMN and annotated GNPS compounds. Finally, the results from both strategies were merged and manually curated for correct structural assignment. To demonstrate the applicability of MN/auto-DBS, we selected the Huangqi-Danshen herb pair (HD), commonly used in prescriptions or patent medicines to treat diabetic nephropathy and cerebrovascular disease. A total of 223 compounds were annotated, including 65 molecules not previously reported in HD, such as aromatic polyketides, coumarins, and diarylheptanoids. Using MN/auto-DBS, we can profile and mine a wide range of complex matrices for potentially new compounds.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据