Characterization of Morinda officinalis How. by UPLC-Q-TOF MS^E Coupled with UNIFI Database Filter

Liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) was widely used for the identification of components from traditional Chinese medicine (TCM), but the characterization of the unknown compounds was still a great challenge currently. Therefore, there is an urgent need to establish a strategy for rapid and comprehensive identification of chemical ingredients in TCMs. In this study, a multiple ingredients identification strategy was proposed based on the UPLC-Q-TOF MS^E coupled with the UNIFI informatics platform. This method includes three steps: the first step was to set up an in-house library based on the literature to complement the UNIFI database. The second step was to screen and verify the known ingredients from raw data. The peaks were screened preliminarily by UNIFI^TM platform based on the in-house database. For the known compounds, based on the accurate mass, fragment ions, neutral losses, retention behaviors, reference standards, previous reports, the compounds were validated furtherly. The last step was to identify or characterize the chemical structures of the potential novel components with similar MS fragmentation pattern of the identified ingredients. The possible molecular formula was obtained by the accurate mass. The candidate compounds were obtained by the online database possible structure was verified by “Fragment match” function and characteristic fragments. This strategy was successfully applied to identify and deduct components of Morinda officinalis How.. A total of 110 chemical components are identified from Morinda officinalis How., including 8 oligosaccharides, 12 iridoids, 58 anthraquinones and 32 other compounds. 8 components are tentatively characterized, including 5 iridoids, 2 glycosides compounds and 1 organic acid. Four of them are potential new compounds, the other components are found in Morinda officinalis How. for the first time. This study provides an efficient data processing strategy to rapidly profile the chemical constituents of complicated herbal extracts.