Zeng Zhong-Da, Liang Yi-Zeng, Chau Foo-Tim, Chen Shuo, Daniel Mok Kam-Wah, Chan Chi-On
Chemometrics and Herbal Medicine Laboratory, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, PR China.
Anal Chim Acta. 2007 Dec 5;604(2):89-98. doi: 10.1016/j.aca.2007.09.057. Epub 2007 Oct 6.
Quality control of herbal medicines (HMs) is a big big headache because of the high complexity and unknown mechanism on disease treatment. In this work, mass spectral profiling, a new tool for data processing is proposed to help a lot in solving this problem as gas chromatography-mass spectroscopy (GC-MS) is used to detect both the active and non-active ingredients buried in HMs. The main idea of mass spectral profiling is employment of target m/z points of GC-MS data on the extraction of chromatographic profiles of pure and/or mixed compositions concerned. Further, the absolute or relative abundance at these m/z points can be utilized for results interpretation. With the help of this tool, the qualitative and quantitative information of chemical components within complicated HMs will be mined out effectively. It can then be recommended as reference indices to assess the importance of target compositions in HMs, such as efficacy evaluation on disease treatment of the active constituents. Mass spectral profiling with less data points significantly improves the possibility to get the rich information with no strong requirements of data preprocessing procedures, like alignment of shift of retention times among different chromatographic profiles. It is powerful for quality control of HMs coupled with pattern recognition techniques on high-throughput data sets. In this study, a commonly used herbal medicine, Houttuynia cordata Thunb and its finished injection products, were used to deliver the strategies. Absolutely, the working principles can be extended to the investigation of metabonomics with gas chromatography-time-of-flight-mass spectrometry (GC-MS-TOF). The good performance of mass spectral profiling shows that it can be a promising tool in the future studies of complex mixture systems.
由于中药材(HMs)的高度复杂性以及其疾病治疗机制的未知性,中药材的质量控制是一个非常棘手的问题。在这项工作中,提出了一种新的数据处理工具——质谱轮廓分析,它有助于解决这个问题,因为气相色谱 - 质谱联用(GC - MS)可用于检测中药材中所含的活性成分和非活性成分。质谱轮廓分析的主要思想是利用GC - MS数据中的目标质荷比(m/z)点来提取相关纯成分和/或混合成分的色谱图。此外,这些m/z点处的绝对或相对丰度可用于结果解释。借助该工具,复杂中药材中化学成分的定性和定量信息将被有效挖掘出来。然后,这些信息可作为参考指标,用于评估中药材中目标成分的重要性,例如对活性成分疾病治疗效果的评估。质谱轮廓分析使用较少的数据点,显著提高了获取丰富信息的可能性,且对数据预处理程序(如不同色谱图之间保留时间偏移的对齐)没有严格要求。结合高通量数据集的模式识别技术,它在中药材质量控制方面具有强大功能。在本研究中,以常用中药材鱼腥草及其成品注射剂为例阐述了相关策略。当然,其工作原理可扩展到气相色谱 - 飞行时间质谱联用(GC - MS - TOF)的代谢组学研究。质谱轮廓分析的良好性能表明,它在未来复杂混合物系统的研究中可能成为一种很有前景的工具。