Abstract
A set of 30 structurally diverse molecules, for which Caco-2 cell permeation coefficients were determined, formed the training set for construction of Caco-2 cell permeation models based upon membrane-interaction (MI) QSAR analysis and a new QSAR method called 4D-fingerprint QSAR analysis. The descriptor terms of the 4D-fingerprints equation are molecular similarity eigenvalues, and this set of descriptors is being evaluated as a potential "universal" QSAR descriptor set. The 4D-fingerprint model suggests that Caco-2 cell permeation is governed by the spatial distribution of hydrogen bonding and nonpolar groups over the molecular shape of a molecule. Moreover, a complementary resampling of the original Caco-2 cell permeation training set, followed by the construction of several "clustered" MI-QSAR models, led to a consensus model consistent in interpretation with the 4D-fingerprint model.
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