Multidimensional (3D/4D-QSAR) probability-guided pharmacophore mapping: investigation of activity profile for a series of drug absorption promoters

In the current study a hybrid approach that combines 3D and 4D-QSAR methods based on grid and neural (SOM) paradigms with automated variable elimination IVE-PLS procedure was examined to identify the pharmacophore pattern for cholic acid derivatives as potential drug absorption promoters. In particular, the outcome of multidimensional structure-activity modelling of the transdermal penetration effect (SKIN) and intestinal absorption enhancement (PAMPA) using the classical CoMFA and Hopfinger's cube formalisms has been compared with the neural CoMSA and SOM-4D-QSAR methodology for a set of cholic derivatives. The comparison of the corresponding statistic characteristics generally confirms the previously observed trends in pairs of q(cv)(2)/q(test)(2) values where 3D/4D SOM-based protocols with a fuzzy molecular representation for various training/test subset distributions outperforms the standard cubic 3D/4D procedures. A systematic model space inspection with splitting data collection into training/test subsets to monitor statistical performance in the effort for mapping of the probabilistic pharmacophore geometry was conducted using the stochastic SMV procedure. The iterative variable elimination procedure (IVE-PLS) represents a filter for specifying descriptors having potentially the highest individual weightings for the observed potency of cholic acid analogues as drug absorption promoters. A simplified visual inspection of pharmacophore sites gives the clear picture of regions that might be modified to modulate the compound potency. A pseudo-consensus 3D/4D-QSAR methodology was used to extract an average 3D pharmacophore hypothesis by exploration of the most densely populated training/test subpopulations to indicate the relevant factors contributing to the drug absorption potency of cholic acid derivatives.