Epidermal permeability–penetrant structure relationships: 4, QSAR of permeant diffusion across human stratum corneum in terms of molecular weight, H-bonding and electronic charge

• Published in: International journal of pharmaceutics Vol. 197; no. 1; pp. 203 - 211
• Main Authors: Pugh, W.John, Degim, I.Tuncer, Hadgraft, Jonathan
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 20-03-2000; Elsevier
• Subjects: Biological and medical sciences; Data Interpretation, Statistical; Diffusion; General pharmacology; Human stratum corneum; Hydrogen Bonding; Medical sciences; Molecular modelling; Molecular Weight; Multivariate regression analysis; Partial charge; Pharmaceutical technology. Pharmaceutical industry; Pharmacology. Drug treatments; Principal component analysis; Regression Analysis; Skin - chemistry; Skin Absorption; Structure-Activity Relationship; Human stratum corneum; Molecular modelling; Multivariate regression analysis; Diffusion; Principal component analysis; Partial charge; Human; Stratum corneum; Estimation; Permeation; Prediction; Multivariate analysis; Modeling; Molecular weight; Skin; Diffusion coefficient; Hydrogen bond
• ISSN: 0378-5173; 1873-3476
• DOI: 10.1016/S0378-5173(00)00326-4

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
α and
β, 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
α and
β 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,
α and
β. MRA using MW,
α and
β 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.