Skin permeation rate as a function of chemical structure.
Multilinear and nonlinear QSAR models were built for the skin permeation rate (Log K(p)) of a set of 143 diverse compounds. Satisfactory models were obtained by three approaches applied: (i) CODESSA PRO, (ii) Neural Network modeling using large pools of theoretical molecular descriptors, and (iii) ISIDA modeling based on fragment descriptors. The predictive abilities of the models were assessed by internal and external validations. The descriptors involved in the equations are discussed from the physicochemical point of view to illuminate the factors that influence skin permeation.
Katritzky
Alan R
AR
Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, Florida 32611, USA. katritzky@chem.ufl.edu
Dobchev
Dimitar A
DA
Fara
Dan C
DC
Hür
Evrim
E
Tämm
Kaido
K
Kurunczi
Ludovic
L
Karelson
Mati
M
Varnek
Alexandre
A
Solov'ev
Vitaly P
VP
D003198:Computer Simulation; D016014:Linear Models; D015394:Molecular Structure; D016571:Neural Networks, Computer; D010539:Permeability; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000378:metabolism; D010599:Pharmacokinetics; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D012867:Skin / Q000378:metabolism*; D012869:Skin Absorption
D004364:Pharmaceutical Preparations