QSAR study on permeability of hydrophobic compounds with artificial membranes.

We previously reported a classical quantitative structure-activity relationship (QSAR) equation for permeability coefficients (P(app-pampa)) by parallel artificial membrane permeation assay (PAMPA) of structurally diverse compounds with simple physicochemical parameters, hydrophobicity at a particular pH (logP(oct) and |pK(a)-pH|), hydrogen-accepting ability (SA(HA)), and hydrogen-donating ability (SA(HD)); however, desipramine, imipramine, and testosterone, which have high logP(oct) values, were excluded from the derived QSAR equation because their measured P(app-pampa) values were lower than calculated. In this study, for further investigation of PAMPA permeability of hydrophobic compounds, we experimentally measured the P(app-pampa) of more compounds with high hydrophobicity, including several pesticides, and compared the measured P(app-pampa) values with those calculated from the QSAR equation. As a result, compounds having a calculated logP(app-pampa)>-4.5 showed lower measured logP(app-pampa) than calculated because of the barrier of the unstirred water layer and the membrane retention of hydrophobic compounds. The bilinear QSAR model explained the PAMPA permeability of the whole dataset of compounds, whether hydrophilic or hydrophobic, with the same parameters as the equation in the previous study. In addition, PAMPA permeability coefficients correlated well with Caco-2 cell permeability coefficients. Since Caco-2 cell permeability is effective for the evaluation of human oral absorption of compounds, the proposed bilinear model for PAMPA permeability could be useful for not only effective screening for several drug candidates but also the risk assessment of chemicals and agrochemicals absorbed by humans.

High-throughput screening of ecdysone agonists using a reporter gene assay followed by 3-D QSAR analysis of the molting hormonal activity.

In this study, 172 diacylhydrazine analogs were examined for their ability to activate an ecdysone (molting hormone)-dependent reporter gene in a silkworm (Bombyx mori) cell-based high-throughput screening assay. The measured EC(50) values (concentration required to cause an effect in 50% of the cells) were used to construct a 3-D QSAR model that describes the ecdysone agonist activities of the diacylhydrazine analogs. Of these compounds, 14 exhibited no activity and were excluded from the 3-D QSAR analysis. The resulting equation described approximately 74% of the activity for 158 compounds. The final equation consisted of 42% electrostatic and 58% steric effects (r(2) = 0.74 and q(2) = 0.45). Comparative molecular field analysis (CoMFA) was used to visualize the steric and electrostatic potential fields that were favorable and unfavorable for biological activity. Of particular interest was the observation that the hydrophobic parameter (logP) was not necessary for describing the observed activities, although previous studies have cited the importance of hydrophobic parameters in both classical and 3-D QSAR analyses of these compounds. Modeling studies of the B. mori ecdysone receptor supported the observed physicochemical parameters required for activity reported by the CoMFA models. Comparison of the present analysis with those performed using other lepidopteran assay systems evidenced a high degree of correlation (r(2) = 0.81 for a Sf-9 cell-based assay and r(2) = 0.89 for a Chilo suppressalis integument-based assay), indicating that it is valid to compare the results generated with the B. mori cell-based system to those generated with previous lepidopteran assays. This novel assay system is amendable to a high-throughput screening format and should greatly increase our ability to discover novel agonists of molting hormone (ecdysone) activity.

Relationships between structure and high-throughput screening permeability of diverse drugs with artificial membranes: application to prediction of Caco-2 cell permeability.

To evaluate the absorption of drugs with diverse structures across a membrane via the transcellular route, their permeability was measured using the parallel artificial membrane permeation assay (PAMPA). The permeability coefficients obtained by PAMPA were analyzed using a classical quantitative structure-activity relationship (QSAR) approach with simple physicochemical parameters and 3D-QSAR, VolSurf. We formulated correlation equations for diverse drugs similar to the equation obtained for peptide-related compounds in our previous study. The hydrogen-bonding ability of molecules, not only the hydrogen-accepting ability but also the hydrogen-donating ability, in addition to hydrophobicity at a particular pH, was significant in determining variations in PAMPA permeability coefficients. Based on this result, an in silico good prediction model for the passive transcellular permeability of diverse structural compounds was obtained. The artificial lipid-membrane permeability coefficients of the drugs, except salicylic acid, were well correlated with the Caco-2 permeability in a previous report suggesting the importance of absorption by the transcellular mechanism for these drugs.