Prediction of Antimicrobial and Antioxidant Activities of Mexican Propolis by 1H-NMR Spectroscopy and Chemometrics Data Analysis

A feasibility study to predict antimicrobial and antioxidant activity properties of propolis extracts using 700-MHz 1H-NMR spectra and multivariate regression data analysis is presented. The study was conducted with thirty-five propolis samples to develop a rapid and reliable method for the evaluati...

Full description

Bibliographic Details
Main Authors: J. Fausto Rivero-Cruz, Eduardo Rodríguez de San Miguel, Sergio Robles-Obregón, Circe C. Hernández-Espino, Blanca E. Rivero-Cruz, José Pedraza-Chaverri, Nuria Esturau-Escofet
Format: Article
Language:English
Published: MDPI AG 2017-07-01
Series:Molecules
Subjects:
Online Access:https://www.mdpi.com/1420-3049/22/7/1184
Description
Summary:A feasibility study to predict antimicrobial and antioxidant activity properties of propolis extracts using 700-MHz 1H-NMR spectra and multivariate regression data analysis is presented. The study was conducted with thirty-five propolis samples to develop a rapid and reliable method for the evaluation of their quality. The extracts have been evaluated by measuring phenolic and flavonoid contents; the antioxidant activity; and the antimicrobial activity. The obtained spectral data were submitted to multivariate calibration (partial least squares (PLS) and orthogonal partial least squares (OPLS)) to correlate the relative intensity and position of NMR resonance peaks with the metabolites contents and biological activities. The developed PLS and OPLS model were successfully applied to the determination of the target properties for proof of the concept. The OPLS observed vs. predicted properties plots indicate the absence of systematic errors with determination coefficients between the ranges 0.7207 to 0.9990. Up to 86.1% of explication of variation in the spectral data and 99.9% in the measured properties were attained with 88.6% of prediction capabilities in the best case (S. mutans activity) according to the cross-validation procedure. The figures of merit of the developed PLS and OPLS methods were evaluated and compared as well.
ISSN:1420-3049