Data-Dependent Analysis Approach in LC/HRMS: Annotation of Natural Product Components

User Benefits

- LCMS-9030 Q-TOF provides high quality and high purity MS/MS spectra by employing data-dependent analysis approach for component annotation of natural product - Combination of Shimadzu’s powerhouse software, LabSolutions LCMS and LabSolutions Insight Explore, demonstrates efficient data acquisition and processing workflow of complex HRMS data

Introduction

LC/HRMS is currently the most prominent analytical tool for untargeted analysis. Combination of soft ionization technique and versatile mass analyser, working in tandem or hybrid configuration, enables aid for component annotation by providing highly-resolved and accurate MS/MS spectra. Resourceful data acquisition approaches have been developed to further facilitate a more time-efficient for data collection including data-dependent analysis (DDA) and dataindependent analysis (DIA). Both approaches are commonly used and proved to be complementary. DDA approach has been recognized for providing a higher purity MS/MS spectrum. It includes survey scan followed by automated fragmentation for precursor ions above a pre-set abundance threshold. Chemists have made tremendous efforts to annotate components in natural products especially herbal medicines. These components may exhibit therapeutic effects and thus it is important to carry out complete characterization. In this article, a simplified DDA-based LC/HRMS workflow was demonstrated for component annotation of herbal medicine, Aconitum carmichaeli.

June 21, 2021 GMT