复杂色谱-质谱联用数据准确快速定性分析新方法研究

项目名称： 复杂色谱-质谱联用数据准确快速定性分析新方法研究

项目编号： No.21205118

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 分析化学

项目作者： 张良晓

作者单位： 中国农业科学院油料作物研究所

项目金额： 25万元

中文摘要： 色谱质谱联用技术因结合色谱的高效分离能力和质谱的高灵敏度，高选择性等优点广泛应用于系统生物学，环境科学，食品化学，医药化学等等领域。目前，复杂样本中未知化合物的结构鉴定难题已成为制约色谱质谱联用技术广泛应用的瓶颈。传统上数据库搜索的方法已明显不能满足高通量高复杂度样本定性分析的要求。本项目正是针对化合物结构鉴定中存在困难，在原有大量探索工作基础上，以人类代谢物为研究对象，就发展快速准确的数据定性分析方法进行系统而细致的研究。与传统方法中仅把质谱作为指纹谱进行相似度匹配进行结构鉴定相比，本项目拟采用化学计量学方法，从样本与实验信息使用，质谱特征挖掘，色谱保留指数预测，质谱数据和保留指数校正等方面开发新的定性分析方法。这项基础研究的成功完成对于色谱质谱技术的研究和应用将具有十分重要的意义。

中文关键词： 代谢组学；结构鉴定；化学计量学；数据库；

英文摘要： Combining the advantages of high-performance separation, high sensitivity and selectivity, the coupled chromatographic and mass spectrometric techniques were extensively employed in various fields such as systems biology, environmental science, food chemistry, medicinal chemistry and so on as the most important approach of instrumental analysis. To date, in contrast to the routine and automated data acquisition steps, the identification requires extensive manual analysis with doubtful results and therefore forms a major bottleneck in data interpretation. Since it could not differentiate the compounds with very similar mass spectra and not sever the identification of compounds out of library, the traditional method of spectral library searches could obviously not satisfy the requirement of automatic identification of unknown compounds in complex samples. In this project, taking human metabolites as research object, we intend to propose a serial of novel methods for automatic identification of unknown compounds after systemic and punctilious investigation to overcome the disadvantages of spectral library searches. Briefly, several parts including proper usage of sample and experiments information, mining mass spectral characteristics, prediction of retention indices and calibration of mass spectra and retention in

英文关键词： Metabolomics；Identification；chemometrics；database；