基于高分辨质谱数据处理策略的中药活性成分体内代谢产物确证的研究进展

Identification of MetabolitesinVivo of Traditional Chinese Medicine Active Ingredients Based on High Resolution Mass Spectrometry Data Processing Strategy

中药有效组分体内代谢产物的鉴别是推动中药现代化的关键一步,其不仅能够阐明中药的药效物质基础,同时许多代谢产物由于其稳定的化学性质、良好吸收分布特点和可能更优的活性作用已成为相关健康产品的重要开发方向。然而因中药成分复杂、体内代谢多样化,代谢物浓度低以及内源性物质干扰大等问题,其代谢产物的鉴定受到阻碍。基于此,建立符合中医药理论的数据处理新策略,从而能快速、准确、全面地定性定量分析中药体内代谢产物显得尤为重要。近年来,高分辨质谱的数据处理策略极大地推动了中药物质基础的阐明。本文分别从高分辨质谱的代谢物预测、提取离子流、质量亏损过滤技术、质谱树状图相似度过滤技术、特征离子过滤技术、多元统计分析策略以及同位素标记等方面系统综述高分辨质谱数据处理策略在中药活性成分体内代谢产物确证中的研究进展,为中药活性成分和体内代谢产物的快速发现和结构表征提供方法参考。

Identification of metabolites in vivo of traditional Chinese medicine(TCM)active ingredients is a key step to promote the modernization of TCM.It can not only clarify the pharmacodynamic substance basis of TCM,but also many metabolites have become an important development direction of related health products due to their stable chemical properties,good absorption and distribution characteristics and possibly better activity.However,the identification of the metabolites of TCM is hindered by the complex composition,the diversity of metabolism,the low concentration of metabolites and the interference of endogenous substances.Based on this,it is particularly important to establish new techniques and data processing strategies,which can quickly,accurately and comprehensively analyze the metabolites of TCM in vivo.In recent years,the data processing strategy of high resolution mass spectrometry has greatly promoted the clarification of the material basis of TCM.This paper respectively from the metabolites of high resolution mass spectrometry to predict,extract ion flow,quality loss filtration,filtration technology,mass spectrum tree similarity characteristics of ionic filtration,multivariate statistical analysis,isotope labeling and strategy of non-target metabolomics etc system in high resolution mass spectrometry data processing strategy active ingredients in Chinese medicine research progress of metabolites identified in vivo.It provides a referential method for the rapid discovery and structural characterization of the active ingredients and metabolites of TCM.