In silico prediction of human oral absorption based on QSAR analyses of PAMPA permeability.

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.

QSAR application for the prediction of compound permeability with in silico descriptors in practical use.

The parallel artificial membrane permeation assay (PAMPA) was developed as a model for the prediction of transcellular permeation in the process of drug absorption. In our previous report, it was revealed that PAMPA permeability is governed by log P, pK (a), and the hydrogen-bonding ability of compounds. In order to construct a new filtering method for selecting informative compounds from the whole combinatorial library, this study tried to predict PAMPA permeability with in silico descriptors. Log P, pK(a), and polar surface areas (PSA) as a hydrogen-bonding descriptor were calculated by commercially available or free-accessible web programs. Five-fold cross-validations and conventional regression analyses were examined with the training set for the entire 81 combinations with nine log P, three pK(a) and three PSA descriptors. By comparison of statistical indices, four equations were selected and then the model with the best combination of in silico descriptors was determined based on the external validation. The PAMPA prediction equation obtained in this report could be applied for the prediction of both Caco-2 cell permeability and human intestinal absorption of mainly passively-transported drugs.

The usefulness of an artificial membrane accumulation index for estimation of the bioconcentration factor of organophosphorus pesticides.

The bioconcentration factor (BCF) is an important ecotoxicological parameter that describes the accumulation of chemicals in organisms. As many studies have reported, logBCF has good correlation with the logarithm of the 1-octanol/water partition coefficient, logP(oct), for chemicals that have logP(oct) values below about 6 and are not significantly metabolized in organisms. In this study we measured a membrane accumulation index, that is, the membrane partition (P(M)) of organophosphorus pesticides using the parallel artificial membrane permeation assay (PAMPA) to clarify whether this index is useful for the estimation of BCF. As a result, logP(M) had good correlation with logP(oct) except for iprobenfos and edifenphos. Furthermore, logBCF in five kinds of fish, especially male guppy correlated better with logP(M) than logP(oct). The results indicate that logP(M) is a better index for predicting logBCF than logP(oct). We have already reported that PAMPA permeability coefficients could predict human oral absorption of compounds, including hydrophobic chemicals and agrochemicals. Since it is expected that both human oral absorption and BCF can be estimated simultaneously using PAMPA, PAMPA is useful for exposure estimation to humans of chemicals in the environment.

Reactive oxygen species assay-based risk assessment of drug-induced phototoxicity: classification criteria and application to drug candidates.

We have previously demonstrated that the phototoxic potential of chemicals could be partly predicted by the determination of reactive oxygen species (ROS) from photo-irradiated compounds. In this study, ROS assay strategy was applied to 39 marketed drugs and 210 drug candidates in order to establish provisional classification criteria for risk assessment of drug-induced phototoxicity. The photosensitizing properties of 39 model compounds consisting of phototoxic and non-phototoxic chemicals, as well as ca. 210 drug candidates including 11 chemical series were evaluated using ROS assay and the 3T3 neutral red uptake phototoxicity test (NRU PT). With respect to marketed drugs, most phototoxic drugs tended to cause type I and/or II photochemical reactions, resulting in generation of singlet oxygen and superoxide. There seemed to be a clear difference between phototoxic drugs and non-phototoxic compounds in their abilities to induce photochemical reactions. A plot analysis of ROS data on the marked drugs provided classification criteria to discriminate the photosensitizers from non-phototoxic substances. Of all drug candidates tested, 35.2% compounds were identified as phototoxic or likely phototoxic on the basis of the 3T3 NRU PT, and all ROS data for these phototoxic compounds were found to be over the threshold value. Furthermore, 46.3% of non-phototoxic drug candidates were found to be in the subthreshold region. These results verify the usefulness of the ROS assay for understanding the phototoxicity risk of pharmaceutical substances, and the ROS assay can be used for screening purposes in the drug discovery stage.

Evaluation of human hepatocyte chimeric mice as a model for toxicological investigation using panomic approaches--effect of acetaminophen on the expression profiles of proteins and endogenous metabolites in liver, plasma and urine.

Toxicological responses to acetaminophen (APAP) overdose were evaluated in human hepatocytes transplanted chimeric mice using 2-dimensional gel electrophoresis (2DE)-based proteomics and (1)H-nuclear magnetic resonance (NMR)-based metabonomics. Huge variations, which were supported by histopathological findings, were observed in proteins expression in chimeric mice liver. The proteomic analysis of the livers showed that the proteins involved in the pathways of lipid/fatty acid metabolism, glycolysis and energy metabolism/production were affected. In addition, oxidative stress-related proteins showed altered expression. The metabonomic analysis of urine and plasma revealed alterations of endogenous metabolites, which were the intermediates involved in the tricarboxylic acid (TCA) cycle. Those findings were already confirmed in normal mice. We hypothesized that the mechanism of APAP-induced effects on chimeric mice liver was in accordance with the mechanism observed in normal mice. Therefore, these toxicopanomic approaches successfully revealed that the mechanisms in humans were identical with "known" APAP-induced hepatotoxicity detected in chimeric mice. Further investigations are needed to detect idiosyncratic hepatotoxicity in humans using chimeric mice.

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.

In vivo hepatotoxicity study of rats in comparison with in vitro hepatotoxicity screening system.

For the establishment of a high throughput screening system using primary cell cultures, investigation of elucidated toxicities to assess the correlation between in vitro and in vivo hepatotoxicity is necessary in the safety evaluation of the compound. In the previous study, we reported the usability of rat primary cultured hepatocytes for establishment of high throughput screening system. To confirm the reliability of rat primary hepatocytes culture screening system, we conducted a single-dose in vivo study with relatively high dose of hepatotoxicant in rats using 4 reference compounds (acetaminophen, amiodarone, tetracycline, carbon tetrachloride), and investigated histopathological changes and expression of oxidative stress-related proteins by immunohistochemistry. We also carried out a proteomics analysis for estimating the reliable and sensitive biomarkers. Histopathologically, compound-specific hepatotoxicity was detected at 24 hr after administration in all compounds except amiodarone, which is known to induce phospholipidosis. Immunohistochemically, oxidative stress-related proteins were increased within 6 hr after administration in all treated groups. Proteomics analysis revealed several protein biomarkers related to oxidative stress and mitochondrial metabolism-regulation, which had been previously detected by proteomics analysis in in vitro screening system. Oxidative stress-related proteins were considered as useful biomarkers of hepatotoxicity; since they were detected by immunohistochemistry and proteomics analysis prior to appearance of compound-specific histopathological changes detected by light microscopy. Considering the relevance of in vitro system to in vivo system from the aspect of new biomarkers related to the toxicogenomics/toxicoproteomics, in vitro primary cell culture system would be sufficient to detect hepatotoxicity in the early stage of drug discovery.

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.