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

IF 2.8 3区 工程技术 Q2 CHEMISTRY, ANALYTICAL
Xixian Kong, Guanghuan Tian, Tong Wu, Shaowei Hu, Jie Zhao, Fuzhu Pan, JingTong Liu, Yi OuYang, Liying Tang, Hongwei Wu
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引用次数: 0

Abstract

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.

基于超高效液相色谱-四极杆Exactive Orbitrap高分辨质谱的MS2LDA特征分子网络分析兰菌净中的化合物。
兰菌净(Geum japonicum Thunb. Var. chinense Bolle)是一种产于中国西南部的植物,是一种促进造血和抗氧化功能的传统中药。它的许多化学成分仍不为人知,这给了解其药理机制和开展质量控制研究带来了挑战。本研究采用超高效液相色谱法和四极杆 Exactive Orbitrap 高分辨率质谱法分析了兰菌净的成分。利用正离子质谱富集的兰布正提取物数据,构建了基于特征的分子网络(FBMN),并利用 MS2LDA 将其与 Mass2Motifs 子结构相关联。利用定制化合物库 SIRIUS 和网络注释传播对兰布正的未知成分进行预测和验证,实现了分子网络的半自动注释。根据由 206 种化合物组成的定制化合物库和 FBMN 聚类结果,兰菌净中的成分主要包括单宁酸、三萜类、黄酮类和酚类。仅以 65 种预先确定的化合物为参考,在兰布正的不同极性区域标注了 210 种未知化合物。目前的研究结果表明,分子网络能够对复杂体系中的化合物进行有效标注,为初步鉴定具有药理活性的灯盏花成分奠定了基础。
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来源期刊
Journal of separation science
Journal of separation science 化学-分析化学
CiteScore
6.30
自引率
16.10%
发文量
408
审稿时长
1.8 months
期刊介绍: The Journal of Separation Science (JSS) is the most comprehensive source in separation science, since it covers all areas of chromatographic and electrophoretic separation methods in theory and practice, both in the analytical and in the preparative mode, solid phase extraction, sample preparation, and related techniques. Manuscripts on methodological or instrumental developments, including detection aspects, in particular mass spectrometry, as well as on innovative applications will also be published. Manuscripts on hyphenation, automation, and miniaturization are particularly welcome. Pre- and post-separation facets of a total analysis may be covered as well as the underlying logic of the development or application of a method.
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