Jiang Yue, Gao Wen, Yang Hua, Li Ping
School of Traditional Chinese Pharmacy, China Pharmaceutical University Nanjing 211198, China.
Zhongguo Zhong Yao Za Zhi. 2022 Sep;47(18):4835-4845. doi: 10.19540/j.cnki.cjcmm.20220518.601.
The components of traditional Chinese medicine(TCM) are characterized by diversity and complexity, and the comprehensive characterization of chemical compositions is the premise to study the effective substances of TCM. High-resolution mass spectrometry(HRMS) is an important tool for qualitative analysis of the complex composition of TCM. A series of HRMS post-processing strategies have been greatly developed and applied for the analysis of complex HRMS data and the structural annotation of chemical components. Considering that the structural analogues tend to have a specific range of mass defect, mass defect filtering(MDF) can be subjected to HRMS data for rapid identification of TCM structural analogues. As a representative data-mining strategy, MDF can effectively improve the characterization efficiency of target compounds in the complex system of TCM. In recent years, classic MDF has been developed into various modified MDF technologies, facilitating the efficient interpretation of HRMS data. This review introduced the principles and characteristics of different MDF technologies and summarized the application of MDF in the qualitative analysis of TCM to provide a comprehensive reference for the research on component characterization and structural identification in TCM.
中药成分具有多样性和复杂性,化学成分的全面表征是研究中药有效物质的前提。高分辨质谱(HRMS)是定性分析中药复杂成分的重要工具。一系列HRMS后处理策略得到了极大发展,并应用于复杂HRMS数据的分析和化学成分的结构注释。考虑到结构类似物往往具有特定的质量亏损范围,质量亏损过滤(MDF)可用于HRMS数据,以快速鉴定中药结构类似物。作为一种代表性的数据挖掘策略,MDF可以有效提高中药复杂体系中目标化合物的表征效率。近年来,经典的MDF已发展为各种改进的MDF技术,便于高效解读HRMS数据。本文综述了不同MDF技术的原理和特点,总结了MDF在中药定性分析中的应用,为中药成分表征和结构鉴定研究提供全面参考。