Abstract
Poor intestinal permeability of drugs constitutes a major bottleneck in the successful development of candidate drugs. Fast computational tools to help in designing compounds with increased probability of oral absorption are required, since both medicinal and combinatorial chemists are under pressure to consider increasing numbers of virtual and existing compounds. The QSAR paradigm for drug absorption is expressed as a function of molecular size, hydrogen-bonding capacity, and lipophilicity. A nonlinear PLS model that can be achieved with minimal computational efforts is described. The QSAR model correlates human intestinal absorption (%HIA) data, and apparent Caco-2 cell permeability data, to parameters calculated from molecular structures. Two properties were found to be relevant for absorption predictions, namely H-bonding capacity, and hydrophobic transferability. The parsimony principle was applied in several aspects: single conformers were used to compute molecular surface areas; the definitions of “polar” and “nonpolar” surfaces were done in a simplistic fashion; simple and fast 2D descriptors were used to estimate other properties; the 1 PLS component model was selected. These choices result in a minimalistic model for oral absorption. The use of both %HIA and Caco-2 permeability data was found to stabilize and improve the model. This QSAR model can serve as a simple, quantitative extension of the “rule of five” scheme (Lipinski, C.A., Lombardo, F., Dominy, B.W., and Feeney, P.J. Adv. Drug Deliv. Rev. 1997, 23, 3–25), in a manner that can prove beneficial to the drug discovery process.
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