3D-QSAR and docking studies of the stability constants of different guest molecules with beta-cyclodextrin

Abstract

This study aims at developing a three dimensional quantitative structure–activity relationship (3D-QSAR) model for predicting complexation of a variety of 126 organic compounds with β-cyclodextrins (β-CD). Molecular descriptors were computed using GRid INdependent Descriptors (GRIND) approach. After variable selection via genetic algorithm method, GRIND are correlated with β-CD complexes stability constants by PLS regression. Kennard–Stone algorithm selected a training dataset comprised of 98 guest molecules. This strategy led to a final QSAR model that showed good internal cross-validation statistics and good predictivity on external data. Those GRIND information which influencing the complexation with β-CD were also confirmed by the 3D-QSAR and docking studies. All these information revealed that the presence of hydrogen bond acceptor and hydrogen bond donor groups in the molecules caused a more difficult and/or unfavorable complexation reaction with β-CDs. The size and shape of the molecules as well as hydrogen bonding interactions effects on the stabilities of β-CDs in inclusion complexes are discussed.