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

Abstract

Background: Skin permeability coefficient (logK_p) is a major determinant for topical drugs. In vitro and ex vivo determination of logK_p 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 logK_p of tea compounds. The best method was selected with respect to the gold standard logK_p.

Result: The model of Potts and Guy showed close proximation with the gold standard logK_p 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 logK_p 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.