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  2. 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)

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)

  • J Chromatogr A. 2017 Oct 6;1518:59-69. doi: 10.1016/j.chroma.2017.08.072.
Caihong Wang 1 Jinlan Zhang 2 Caisheng Wu 1 Zhe Wang 1
Affiliations

Affiliations

  • 1 State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
  • 2 State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China. Electronic address: [email protected].
Abstract

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.

Keywords

Discriminant analysis; Er-xian decoction; Mass spectral tree similarity filter; Multiple-dimension LC–MS data; Sub-structure intersection.

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