Abstract
Comparative molecular field analysis region focusing (CoMFA-RF) and VolSurf methods were employed to develop 3D-QSAR models for prediction of stability constants of mono- and 1,4-disubstituted benzenes with α-Cyclodextrin. The combination of CoMFA fields with some physicochemical descriptors ultimate to a more predictive model. We applied two effective feature selection techniques, genetic algorithm (GA) and successive projection algorithm (SPA), to extract more informative VolSurf descriptors. Partial least square and support vector machine (SVM) were used to model construction and SPA–SVM based VolSurf descriptors showed excellent performance in predicting stability constants. The predictive ability of modified CoMFA-RF and VolSurf models were determined using a test set of 18 compounds result in correlation coefficients of 0.604 and 0.889 respectively. For further model validation, the cross validation (leave one out), progressive scrambling and bootstrapping were also applied. Results of both methods showed that electrostatic and hydrophobic effects and shape parameters are main influencing factors in inclusion complexation of benzenes derivatives with α-Cyclodextrin. The results of docking study, which can predict the binding mode and orientation of guest molecules in Cyclodextrin cavity, are in agreement with of combined 3D-QSAR models results.
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We gratefully appreciate to professor S. Kamitori (Rare Sugar Research Center and Faculty of Agriculture, Kagawa University, Japan) for granting permission to access the Crystallographic Information File (CIF) format of crystallographic structure of α-CD-p-bromophenol complex.
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Ghasemi, J.B., Salahinejad, M., Rofouei, M.K. et al. Docking and 3D-QSAR study of stability constants of benzene derivatives as environmental pollutants with α-cyclodextrin. J Incl Phenom Macrocycl Chem 73, 405–413 (2012). https://doi.org/10.1007/s10847-011-0078-4
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DOI: https://doi.org/10.1007/s10847-011-0078-4