1P-22 PDF
Development of Chemometric Approach for the Bioactive Evaluation of Multicomponent Foods and the Selection of the Bioactivity-predictive Chemical Combinations
Understanding chemical composition is indispensable for accurate prediction of the bioactivity of multicomponent drugs, nutraceuticals, and foods, but no analytical approach exists to easily predict the bioactivity of multicomponent systems from complex behaviors of multiple coexisting factors. Herein we represent a metabolic profiling (MP) strategy for evaluating bioactivity in systems containing various small molecules. We attempted to establish a rapid and simple matrix-assisted laser desorption ionization–mass spectrometry (MALDI–MS)-MP technique for the chemometrics-driven evaluation of bioactivity based on composition profiles using diverse green tea extract (GTE) panels with different antioxidant activity. This work investigated the applicability of such a technique for the selection of bioactivity-predictive or -discriminative multicomponent factors and the determination of a bioactivity-predictive chemical combination from multivariate data obtained by MALDI–MS measurement. Chemometric procedures allowed the evaluation of GTE bioactivity by multicomponent rather than single-component information. The bioactivity could be easily evaluated by calculating the summed abundance of a few selected components that contributed most to constructing the prediction model. This approach enabled us to easily extract a bioactivity-predictive chemical combination from multicomponent information.