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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.
Chemistry & Biodiversity 11/2009; 6(11):1845-66. · 1.80 Impact Factor
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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. 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.
Journal of Computer-Aided Molecular Design 03/2009; 23(5):309-19. · 3.39 Impact Factor
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Journal of Computer-Aided Molecular Design. 01/2009; 23:309-319.
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ABSTRACT: 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.
Chemosphere 01/2009; 74(6):751-7. · 3.21 Impact Factor
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ABSTRACT: 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.
Bioorganic & Medicinal Chemistry 07/2007; 15(11):3756-67. · 2.92 Impact Factor
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ABSTRACT: 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.
Bioorganic & Medicinal Chemistry 09/2005; 13(15):4721-32. · 2.92 Impact Factor
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Masaaki Fujikawa
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ABSTRACT: Kyoto University (京都大学) 0048 新制・課程博士 博士(農学) 甲第13859号 農博第1674号 新制/農/952 UT51-2008-C775 2008-03-24 京都大学大学院農学研究科地域環境科学専攻 (主査)准教授 赤松 美紀, 教授 東 順一, 教授 宮川 恒 学位規則第4条第1項該当
