期刊
INTERNATIONAL JOURNAL OF PHARMACEUTICS
卷 197, 期 1-2, 页码 203-211出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/S0378-5173(00)00326-4
关键词
principal component analysis; multivariate regression analysis; human stratum corneum; partial charge; molecular modelling; diffusion
Principal components analysis (PCA) and multivariate regression analysis (MRA) are used to assess the predictors of permeant diffusion across human stratum corneum. Log(D/h), was estimated from log k(p) + 0.024 - 0.59 log K-oct,, where D = diffusion coefficient (cm(2)/h), h = path length (cm), k(p) permeability coefficient (cm/h), K-oct = partition coefficient (octanol/water). Molecular weight (MW) with (1) scaled H-bonding parameters alpha and beta, or (2) summed modulus of partial charge from molecular modelling were tested as predictors of (D/h). Charge may be computed for any molecule, whilst alpha and beta values are generally unavailable for molecules of biological interest. PCA suggests a dominant permeation pathway since 93% of data variation is in PC1 of log (D/h), MW and charge and 82% in PC1 of log (D/h), MW, alpha and beta. MRA using MW, alpha and beta is unsatisfactory because of collinearity amongst predictors. The best predictor was the product MW*charge. Similarity of the eigenvectors in PCA and normalised coefficients in MRA indicates that charge and MW are equally important predictors of diffusion. (C) 2000 Elsevier Science B.V. All rights reserved.
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