Feature‐based molecular networking with MS2LDA to profile compounds in Lanbuzheng based on ultra‐high‐performance liquid chromatography‐quadrupole Exactive Orbitrap high‐resolution mass spectrometry

轨道轨道 质谱法 化学 色谱法 化学成分 注释 高分辨率 计算机科学 人工智能 遥感 地质学
作者
Xixian Kong,Guanghuan Tian,Tong Wu,Shaowei Hu,Jie Zhao,Fuzhu Pan,JingTong Liu,Yi Ouyang,Liying Tang,Hongwei Wu
出处
期刊:Journal of Separation Science [Wiley]
卷期号:47 (16) 被引量:3
标识
DOI:10.1002/jssc.202400248
摘要

Lanbuzheng (Geum japonicum Thunb. var. chinense Bolle), a plant found in Southwest China, is a traditional Chinese medicine that promotes hematopoiesis and antioxidant functions. Many of its chemical constituents remain unknown, posing challenges both to understanding its pharmacological mechanisms and to conducting quality control research. In this work, ultra-high performance liquid chromatography coupled with quadrupole Exactive Orbitrap high-resolution mass spectroscopy was used for profiling the composition of Lanbuzheng. Using positive ion mass spectrometry data enriched from Lanbuzheng extract, feature-based molecular networking (FBMN) was constructed and associated with Mass2Motifs substructures using MS2LDA. Prediction and validation of unknown constituents of Lanbuzheng using a custom-built compound library, SIRIUS, and network annotation propagation, achieved a semi-automated annotation of the molecular network. Based on the custom-built library comprising 206 compounds and the FBMN clustering results, the constituents in Lanbuzheng primarily include tannins, triterpenes, flavonoids, and phenolics. Using only 65 pre-identified compounds as references, 210 unknown compounds were annotated in various polarity regions of Lanbuzheng. Results of the current work indicate that molecular networks enable the efficient annotation of compounds in complex systems, laying the groundwork for the preliminary identification of pharmacologically active constituents of Lanbuzheng.
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