A multiple-dimension liquid chromatography coupled with mass spectrometry data strategy for the rapid discovery and identification of unknown compounds from a Chinese herbal formula (Er-xian decoction)

被引:16
|
作者
Wang, Caihong
Zhang, Jinlan [1 ,2 ]
Wu, Caisheng
Wang, Zhe
机构
[1] Chinese Acad Med Sci, Inst Mat Med, State Key Lab Bioact Subst & Funct Nat Med, 2 Nanwei Rd, Beijing 100050, Peoples R China
[2] Peking Union Med Coll, Beijing 100050, Peoples R China
基金
中国国家自然科学基金;
关键词
Multiple-dimension LC-MS data; Mass spectral tree similarity filter; Discriminant analysis; Sub-structure intersection; Er-xian decoction; HYDROPHILIC INTERACTION CHROMATOGRAPHY; STRUCTURE-RETENTION RELATIONSHIPS; CHEMICAL-CONSTITUENTS; MULTIVARIATE-ANALYSIS; FRAGMENTATION TREES; METABOLOMICS; METABOLITES; MS; COMPONENTS; EPIMEDIUM;
D O I
10.1016/j.chroma.2017.08.072
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
It is very important to rapidly discover and identify the multiple components of traditional Chinese medicine (TCM) formula. High performance liquid chromatography with high resolution tandem mass spectrometry (HPLC-HRMS/MS) has been widely used to analyze TCM formula and contains multiple dimension data including retention time (RT), high resolution mass (HRMS), multiple-stage mass spectrometric (MSn), and isotope intensity distribution (IID) data. So it is very necessary to exploit a useful strategy to utilize multiple-dimension data to rapidly probe structural information and identify chemical compounds. In this study, a new strategy to initiatively use the multiple-dimension LC-MS data has been developed to discover and identify unknown compounds of TCM in many styles. The strategy guarantees the fast discovery of candidate structural information and provides efficient structure clues for identification. The strategy contains four steps in sequence: (1) to discover potential compounds and obtain sub-structure information by the mass spectral tree similarity filter (MTSF) technique, based on HRMS and MSn data; (2) to classify potential compounds into known chemical classes by discriminant analysis (DA) on the basis of RT and HRMS data; (3) to hit the candidate structural information of compounds by intersection sub-structure between MTSF and DA (M,D-INSS); (4) to annotate and confirm candidate structures by IID data. This strategy allowed for the high exclusion efficiency (greater than 41%) of irrelevant ions in er-xian decoction (EXD) while providing accurate structural information of 553 potential compounds and identifying 66 candidates, therefore accelerating and simplifying the discovery and identification of unknown compounds in TCM formula. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:59 / 69
页数:11
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