Application of RP-18 TLC Retention Data to the Prediction of the Transdermal Absorption of Drugs

Several chromatographic parameters (R-M(0) and S obtained from RP-18 TLC with methanol-pH 7.4 phosphate buffer mobile phases by extrapolation to zero concentration of methanol; R-f and R-M obtained from RP-18 TLC with acetonitrile-pH 7.4 phosphate buffer 70:30 v/v as a mobile phase) and calculated molecular descriptors (molecular weight-M-W; molar volume-V-M; polar surface area-PSA; total count of nitrogen and oxygen atoms-(N+O); H-bond donor count-HD; H-bond acceptor count-HA; distribution coefficient-log D; total energy-E-T; binding energy-E-b; hydration energy-E-h; energy of the highest occupied molecular orbital-E-HOMO; energy of the lowest unoccupied orbital-E-LUMO; electronic energy-E-e; surface area-S-a; octanol-water partition coefficient-log P; dipole moment-DM; refractivity-R, polarizability-alpha) and their combinations (R-f/PSA, R-M/M-W, R-M/V-M) were tested in order to generate useful models of solutes' skin permeability coefficient log K-p. It was established that neither R-M(0) nor S obtained in the conditions used in this study is a good predictor of the skin permeability coefficient. The chromatographic parameters R-f and R-f/PSA were also unsuitable for this purpose. A simple and potentially useful, purely computational model based on (N+O), log D and HD as independent variables and accounting for ca. 83% of total variability was obtained. The evaluation of parameters derived from R-M (R-M, R-M/M-W, R-M/V-M) as independent variables in log K-p models proved that R-M/V-M is the most suitable descriptor belonging to this group. In a search for a reliable log K-p model based on this descriptor two possibilities were considered: a relatively simple model based on 5 independent variables: (N+O), log D, R-M/V-M, E-T and E-h and a more complex one, involving also E-b, M-W and PSA.

Automated summary

In this study, various chromatographic parameters and calculated molecular descriptors were tested to generate models for predicting solutes' skin permeability coefficient log Kp. It was found that parameters such as RM(0) and S were not good predictors for skin permeability coefficient, while a computational model based on (N+O), log D, and HD showed potential with an accuracy of around 83%.