| Literature DB >> 31733897 |
Huiqin Pan1, Heng Zhou1, Shui Miao1, Jiayin Cao2, Jiaming Liu1, Lan Lan1, Qing Hu1, Xiuhong Mao1, Shen Ji3.
Abstract
To fully capture the chemo-diversity of medicinal plants is very essential for understanding of their pharmacological activities and guiding scientific quality control. Aiming to facilitate chemical characterization and novel natural products discovery, the present study proposed an integrated approach based on two-dimensional liquid chromatography coupled with quadrupole-Orbitrap mass spectrometer (2D LC/Q-Orbitrap MS). An offline comprehensive two-dimensional (2D) LC system was constructed to cover and separate multi-type constituents by combining hydrophilic interaction chromatography (HILIC) and conventional reversed phase C18. A two-step mass defect filtering-induced exclusion list-data dependent acquisition was developed to increase MS/MS coverage and selectivity. Additionally, an efficient interpretation strategy, combining an automatic matching algorithm and molecular networking (MN), was introduced for rapid recognition of known compounds and efficient elucidation of unreported ones. As a case study, the integrated approach was tentatively applied for comprehensive characterization of complex multi-type components in Lonicerae Japonicae Flos (LJF), a traditional Chinese medicine. Consequently, a total of 537 compounds were characterized from LJF, including a large number of potential novel structures. It was demonstrated that the integrated approach is powerful in deep investigation on chemical diversity of medicinal plants and discovery of novel structures. Its application could also be extended for global profiling of other complicated chemical systems, such as Chinese medicinal formulas.Keywords: Automatic matching algorithm; Exclusion list-based data dependent acquisition; Lonicerae Japonicae Flos; Molecular networking; Offline comprehensive 2D LC
Year: 2019 PMID: 31733897 DOI: 10.1016/j.chroma.2019.460674
Source DB: PubMed Journal: J Chromatogr A ISSN: 0021-9673 Impact factor: 4.759