| Abstract
| - QSAR models for four skin penetration enhancer data sets of 61, 44, 42, and 17 compounds were constructedusing classic QSAR descriptors and 4D-fingerprints. Three data sets involved skin penetration enhancementof hydrocortisone and hydrocortisone acetate. The other data set involved skin penetration enhancement offluorouracil. The measure of penetration enhancement is the ratio of the net permeation of the penetrantwith and without a common fixed concentration of enhancer. Significant QSAR models could be built usingmultidimensional linear regression fitting and genetic function model optimization for all four data setswhen both classic and 4D-fingerprint descriptors were used in the trial descriptor pool. Reasonable QSARmodels could be built when only 4D-fingerprint descriptors were employed, and no significant QSAR modelscould be built using only classic descriptors for two of the four data sets. Comparison analyses of thedescriptor terms, and their respective regression coefficients, across the pairs of the best QSAR models ofthe four skin penetration enhancer data sets did not reveal any significant extent of similar terms. Overall,the QSAR models for the penetration-enhancer systems appear meaningfully different from one another,suggesting that there are distinct mechanisms of skin penetration enhancement that depend on the chemistryof both the enhancer and the penetrant.
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