Abstract
This work aimed to unravel the retention mechanisms of 30 structurally different flavonoids separated on three chromatographic columns: conventional Kinetex C18 (K-C18), Kinetex F5 (K-F5), and IAM.PC.DD2. Interactions between analytes and chromatographic phases governing the retention were analyzed and mechanistically interpreted via quantum chemical descriptors as compared to the typical ‘black box’ approach. Statistically significant consensus genetic algorithm-partial least squares (GA-PLS) quantitative structure retention relationship (QSRR) models were built and comprehensively validated. Results showed that for the K-C18 column, hydrophobicity and solvent effects were dominating, whereas electrostatic interactions were less pronounced. Similarly, for the K-F5 column, hydrophobicity, dispersion effects, and electrostatic interactions were found to be governing the retention of flavonoids. Conversely, besides hydrophobic forces and dispersion effects, electrostatic interactions were found to be dominating the IAM.PC.DD2 retention mechanism. As such, the developed approach has a great potential for gaining insights into biological activity upon analysis of interactions between analytes and stationary phases imitating molecular targets, giving rise to an exceptional alternative to existing methods lacking exhaustive interpretations.
Highlights
Flavonoids as secondary plant metabolites perform various functions in growth, development, reproduction, and abiotic responses [1]
We presented a novel approach for predicting the retention of 30 structurally-different flavonoids on three chemically-bonded stationary phases using genetic algorithms–partial least squares quantitative structure retention relationship (QSRR) modeling [10,16,22] based on density functional theory (DFT)-derived QM molecular descriptors
Results of Genetic Algorithms (GAs) hyper-parameter optimization showed that the minimum root mean square error of cross-validation root mean square error of CV (RMSECV) values were obtained for a population size of 20, cross-over fraction of 0.8, and the mutation rate of 0.2
Summary
Flavonoids as secondary plant metabolites perform various functions in growth, development, reproduction, and abiotic responses [1]. The structural diversity, biological and ecological significance, and health-promoting and anti-cancer properties of flavonoids have been attractive for scientists from different disciplines [2]. Special attention to flavonoids is paid by analytical chemists because of their bio- and nutraceutical-activity, as well as benefits for dietary supplementation. There is increased interest in the advancement of analytical techniques for plant extract and food quality analysis. The structural diversity of flavonoids can lead to challenges in separation and, thereby, their analysis. Based on the possible substitution patterns of ten carbon atoms comprising the flavonoid skeleton, the number of theoretically-viable structures is monumental [2]
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