Multidisciplinary approach based on capillary electrophoresis, nuclear magnetic resonance spectroscopy, and molecular modeling to study the enantioselective recognition of erythro-mefloquine enantiomers by cyclodextrins

Computational chemistry has evolved into a powerful and increasingly reliable tool for elucidating chemical phenomena and predicting molecular properties. Nevertheless, accurately modeling enantioselective recognition remains one of the most demanding challenges in separation science. The fundamental obstacle lies in the exceptionally small free-energy differences that distinguish competing enantioselective pathways, typically ranging from only 0.01 to 1 kcal·mol -1 . Such subtle energetic variations push current theoretical approaches to their limits, making experimental validation indispensable for assessing and refining computational models. Considering this, we investigated the enantioselective recognition of erythro -mefloquine (MQ) by β-cyclodextrin (β-CD) and heptakis (2,3-di- O -acetyl)-β-cyclodextrin (HDA-β-CD) through an integrated strategy combining capillary electrophoresis (CE), nuclear magnetic resonance (NMR) spectroscopy, and quantum mechanics (QM)-based molecular modeling. This multidisciplinary approach serves a dual purpose: first, to critically evaluate the consistency and complementarity of results obtained from experimental and theoretical methodologies; second, to identify possible existing limitations in our understanding of the molecular mechanisms and noncovalent interactions governing enantioselective recognition. The long-term goal of this work is to establish a robust and systematic framework that integrates orthogonal experimental and computational techniques, providing a more reliable protocol for explaining, validating, and ultimately predicting enantioselective recognition processes.