Analysis of Antioxidant Constituents of Filtering Infusions from Oak (Quercus sideroxyla Bonpl. and Quercus eduardii Trel.) and Yerbaniz (Tagetes lucida (Sweet) Voss) as Monoamine Oxidase Inhibitors

Abstract

The antioxidant constituents of ancestral products with ethnobotanical backgrounds are candidates for the study of filtering infusions to aid in pharmacotherapies focused on the treatment of depression and anxiety. Monoamine oxidase A (MAO-A) is an enzyme that regulates the metabolic breakdown of serotonin and noradrenaline in the nervous system. The goal of this study was to evaluate in vitro and in silico the effect of antioxidant constituents of filtering infusions from yerbaniz (Tagetes lucida (Sweet) Voss) and oak (Quercus sideroxyla Bonpl. and Quercus eduardii Trel.) as monoamine oxidase inhibitors. Materials were dried, ground, and mixed according to a simplex-centroid mixture design for obtaining infusions. Differential analysis of the phenolic constituent's ratio in the different infusions indicates that among the main compounds contributing to MAO-A inhibition are the gallic, chlorogenic, quinic, and shikimic acids, quercetin glucuronide and some glycosylated derivatives of ellagic acid and ellagic acid methyl ether. Infusions of Q. sideroxyla Bonpl. leaves, because of their content (99.45 ± 5.17 µg/mg) and synergy between these constituents for MAO-A inhibition (52.82 ± 3.20%), have the potential to treat depression and anxiety. Therefore, future studies with pharmacological approaches are needed to validate them as therapeutic agents with applications in mental health care.

Keywords: anxiety; depression; in silico; phenolic compounds.

Figure 1

Physicochemical parameters in infusions of Tagetes lucida (Sweet) Voss, Quercus sideroxyla Bonpl., Quercus eduardii Trel., and their mixtures. Different letters indicate significant statistical differences between samples (Tukey, p < 0.05, n = 3).

Figure 2

Partial least-square-discriminant (PLS–DA) of the influence of leaf content on the main phenolic profile identified by UPLC–ESI–MS/MS in mixtures. (a) MAO–A inhibition (%); (b) the results are presented as principal component score plots, and the explained variances are shown in brackets; (c) important features identified by PLS–DA. The color boxes on the right indicate the relative abundance of the corresponding compound in each leaf content.

Figure 3

Molecular docking simulation obtained with the lowest energy conformation for important features identified by PLS–DA.

Figure 4

Schematic demonstration for the simplex–centroid mixture designed in percentage and acronyms assigned to each sample.