Evaluation of selected quantitative structure permeability relationship (QSPR) based mathematical models for the prediction of skin permeability of Camellia sinensis (tea) compounds

Abstract

Background: Skin permeability coefficient (logKp) is a major determinant for topical drugs. In vitro and ex vivo determination of logKp is expensive, time and labour intensive, and difficult to apply to large databases. QSPR models derived from statistical correlation between descriptors of the compounds with the in vitro or ex vivo permeation data, are therefore used extensively. Vast number of QSPR equations makes the selection of a particular equation to screen a database, difficult choice. Objective: This study has evaluated common descriptor based equations for selection of the best suitable equation for screening phytochemical library of Camellia sinensis. Methods: Seven QSPR based models were used to estimate and compare the logKp of tea compounds. The best method was selected with respect to the gold standard logKp. Result: The model of Potts and Guy showed close proximation with the gold standard logKp and had highest association along with least RMSE value and least deviation. According to this method, approximately, 37.38%, 35.35% and 27.27% of the tea compounds were found to have high, good and poor logKp respectively. Conclusion: Potts and Guy equation can be effectively used to screen the phytochemical library of Camellia sinensis. This study has potential application in the field of topical medicine and cosmetics.