In silico Prediction of Human Oral Absorption Based on QSAR Analyses of PAMPA Permeability

Abstract

The parallel artificial membrane permeation assay (PAMPA) was developed as a model for the prediction of transcellular permeation in the process of drug absorption. Our research group has measured the PAMPA permeability of peptide-related compounds, diverse drugs, and agrochemicals. This work led to a classical quantitative structure-activity relationship (QSAR) equation for PAMPA permeability coefficients of structurally diverse compounds based on simple physicochemical parameters such as lipophilicity at a particular pH (log P(oct) and |pKa-pH|), H-bond acceptor ability (SA(HA)), and H-bond donor ability (SA(HD)). Since the PAMPA permeability of lipophilic compounds decreased with their apparent lipophilicity due to the unstirred water layer (UWL) barrier on membrane surfaces and to membrane retention, a bilinear QSAR model was introduced to explain the permeability of a broader set of compounds using the same physicochemical parameters as those used for the linear model. We also compared PAMPA and Caco-2 cell permeability coefficients of compounds transported by various absorption mechanisms. The compounds were classified according to their absorption pathway (passively transported compounds, actively transported compounds, and compounds excreted by efflux systems) in the plot of Caco-2 vs. PAMPA permeability. Finally, based on the QSAR analyses of PAMPA permeability, an in silico prediction model of human oral absorption for possibly transported compounds was proposed, and the usefulness of the model was examined.