Enantiophore modeling in 3D-QSAR. A data mining application on Whelk-O1 chiral stationary phase

A combination of the enantiophore concept described in a previous study and a quantitative structure enantioselective relationship (QSER) based on partial least squares (PLS) analysis is presented. In the present study, a comprehensive approach for describing the enantioselective binding properties of the Whelk-O1 chiral HPLC receptor is achieved using molecular descriptors calculated by the GRID program. The GRID descriptors allow us to describe the molecules in terms of their ability to form favorable interactions with independent chemical groups (probes) that can be related to receptor sites. For each molecule, we compute 120 enantiophore descriptors representing the energy contributions from all possible pairwise combinations of probes. The overall procedure was simplified by considering only the most energetically favorable locations and converting selected grid-point energies into alignment-independent descriptors. By using a training set of 143 diverse chiral compounds, an optimal PLS model requiring seven components was chosen by using the cross-validation method resulting in a correlation coefficient R2= 0.88 and a cross validated correlation coefficient Q2= 0.85. An interpretation of the model is proposed based upon a visual inspection of the regression coefficient plots. From these plots, the influence of particular molecular features for selective binding of solutes was estimated and used to outline the chiral recognition sites in the Whelk-O1 receptor. The predictive power of our model has been estimated by means of an external data set emphasizing the suitability of the procedure also for predictive aims.