Cyclodextrins are well known in supramolecular chemistry as host molecules capable of engulfing molecules in their hydrophobic cavity via noncovalent interactions. Although cyclodextrins are frequently used for chiral separation of racemates, the mechanism of chiral recognition has not yet been fully characterised. The current investigation was aimed at examining chiral recognition mechanism in order to construct an in silico method for prediction of chiral recognition. Amino acids were selected as model guest, whereas αCD was used as model host. The results of molecular docking and molecular dynamic calculations were compared to results of stability constant determination and capillary electrophoresis measurements of enantioseparations. Positive correlation between binding strength and chiral separation ability was found. However, the small energy differences between interaction energy of each enantiomer with αCD fell into the range of standard error of molecular docking calculations limiting its applicability for in silico prediction. Examining the stability of complex geometry during molecular dynamics simulation revealed that stable complex geometry is likely to be a prerequisite for chiral recognition. This hypothesis was tested on methylderivatized tryptophan. Indeed, chiral separation of β-methyl-tryptophans by αCD could be successfully predicted by examining the complex geometries during molecular dynamic simulation.
Keywords: Alpha-Cyclodextrin, amino acids, β-Me-Tryptophan, complexation, capillary electrophoresis, molecular docking, molecular dynamics
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