Billiot, FereshtehGarcia, MauroBlack, NathanBilliot, EugeneMorris, Kevin F.Fang, Yayin2021-06-212021-06-212021-05-26Garcia, M., Black, N., Billiot, E., Billiot, F., Morris, K.F. and Fang, Y.Y. (2021) Chiral Recognition of Dansyl Derivatives with an Amino Acid- Based Molecular Micelle: A Molecular Dynamics Investigation. Open Journal of Physical Chemistry, 11, 64-86. https://doi.org/10.4236/ojpc.2021.112004https://hdl.handle.net/1969.6/89689In this study, the chiral separation mechanisms of Dansyl amino acids, including Dansyl-Leucine (Dans-Leu), Dansyl-Norleucine (Dans-Nor), Dansyl-Tryptophan (Dans-Trp) and Dansyl-Phenylalanine (Dans-Phe) binding to poly-sodium N-undecanoyl-(L)-Leucylvalinate, poly (SULV), were investigated using molecular dynamics simulations. Micellar electrokinetic chromatography (MEKC) has previously shown that when separating the enantiomers of these aforementioned Dansyl amino acids, the L-enantiomers bind stronger to poly (SULV) than the D-enantiomers. This study aims to investigate the molecular interactions that govern chiral recognition in these systems using computational methods. This study reveals that the computationally- calculated binding free energy values for Dansyl enantiomers binding to poly (SULV) are in agreement with the enantiomeric order produced in experimental MEKC studies. The L-enantiomers of Dans-Leu, Dans-Nor, Dans-Trp, and Dans-Phe binding to their preferred binding pockets in poly (SULV) yielded binding free energy values of −21.8938, −22.1763, −21.3329 and −13.3349 kJ∙mol−1, respectively. The D-enantiomers of Dans-Leu, Dans-Nor, Dans-Trp, and Dans-Phe binding to their preferred binding pockets in poly (SULV) yielded binding free energy values of −14.5811, −15.9457, −13.6408, and −12.0959 kJ∙mol−1, respectively. Furthermore, hydrogen bonding analyses were used to investigate and elucidate the molecular interactions that govern chiral recognition in these molecular systems.en-USAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/amino acid based molecular micellesmolecular modelingcomputational chemistrychiral recognitionArticlehttps://doi.org/10.4236/ojpc.2021.112004