Metabolic Profiling of the Mexican Anxiolytic and Sedative Plant Galphimia glauca Using Nuclear Magnetic Resonance Spectroscopy and Multivariate Data Analysis

 

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Abstract

Galphimia glauca is popularly employed in Mexico for the treatment of central nervous system disorders. Pharmacological and phytochemical studies have resulted in the identification of the anxiolytic and sedative principle consisting of a mixture of nor-secofriedelanes, named the galphimine series (1 – 9). These active constituents were found in plants collected in the vicinity of a restricted region in Central Mexico, where this species is abundant. A metabolic profiling carried out by means of ¹H-NMR spectroscopy and multivariate data analysis was applied to crude extracts from wild plant populations, collected from six different locations as a quality control assessment, 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. These two PCs permitted the differentiation of the various sample populations, depending on the presence of galphimines. This information consistently correlated with the corresponding HPLC analysis. 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. Both assays demonstrated anxiolytic and sedative responses only among those sample populations which had previously been differentiated by PC-1. Partial least square regression-discriminant analysis (PLS-DA) 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.

Abbreviations

GM:Dr. Mora, Guanajuato sample

i. p.:intraperitoneal

JG:Guadalajara, Jalisco sample

MC:Cuernavaca, Morelos sample

MS:San Andrés de la Cal, Morelos sample

MT:Tepoztlán, Morelos sample

PC-1:principal component 1

PC-2:principal component 2

PCA:principal component analysis

PLS-DA:partial least square regression-discriminant analysis

QJ:Jalpan, Querétaro sample

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Prof. Dr. María Luisa Villarreal

Centro de Investigación en Biotecnología

Universidad Autónoma del Estado de Morelos

Avenida Universidad 1001

Col. Chamilpa

Cuernavaca

Morelos 62210

México

Phone: +52/777/329/7057

Fax: +52/777/329/7030

Email: luisav@buzon.uaem.mx

Email: luisav@cib.uaem.mx

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