Rapid identification of polyphenols in Kudiezi injection with a practical technique of mass defect filter based on high-performance liquid chromatography coupled with linear ion trap/orbitrap mass spectrometry

Abstract

In the present study, a practical approach of mass defect filter (MDF), a data-mining technique, was developed and evaluated for the rapid classification of complicated peaks into well-known chemical families based on the exact mass acquired by high-resolution mass spectrometry. The full-scan mass data of Kudiezi injection was acquired by high-performance liquid chromatography coupled with a linear ion trap-orbitrap mass spectrometer system (HPLC-LTQ-Orbitrap) that features high resolution, mass accuracy and sensitivity. To screen the polyphenols including chlorogenic acids (CGAs) and flavonoids in the injection, the MDF approach was employed to rapidly screen them from the complex system. First, two filtering templates and several filters were set to remove the interference ions of a complex matrix by MetWorks 1.3 Software. Then, the filtered target peaks were characterized according to their accurate mass data and MSⁿ fragment ions. Utilizing the proposed approach, 14 CGAs and 16 flavonoids could be screened and identified. The results of rapid screening and detection showed that the developed MDF approach based on high-resolution mass spectrometry would be adaptable to the analysis of a complex system of traditional Chinese medicines.