Multivariate data analysis using magnetic resonance spectroscopy for the in silico analysis of the Mexican anxiolytic and sedative plant Galphimia glauca

Abstract

Galphimia glauca is popularly employed in Mexico to treat central nervous system disorders. The anxiolytic and sedative principle of this species consists of a mixture of nor-secofriedelanes, named the galphimine series1. These active constituents were found in plants collected in the vicinity of a restricted region in Central Mexico. A metabolic profiling carried out by means of 1H NMR spectroscopy and multivariate data analysis was applied to crude extracts from wild plant populations, from six different locations, in order to differentiate their chemical profile. Principal component analysis (PCA) of the 1H NMR spectra revealed clear variations among the populations, with two populations out of the six studied manifesting differences, when the principal components PC-1 and PC-2 were analyzed. PC-1 permitted the differentiation of the various sample populations, depending on the presence of galphimines. This information consistently correlated with the corresponding HPLC analysis. PC-2 better defined the separation in terms of differential concentrations of galloylquinic acid derivatives. The neuropharmacological effects of the crude extracts were evaluated by using ICR mice in the elevated plus-maze, as well as the sodium pentobarbital-induced hypnosis models, demostrating anxiolytic and sedative responses on those sample populations which had been differentiated by PC-1. Partial least square regression-discriminant analysis also confirmed a strong correlation between the observed effects and the metabolic profiles of the plants. The overall results of this study confirm the benefits of using metabolic profiling for the in silico analysis of active principles in medicinal plants.