In Silico Prediction of Human Intestinal Permeability (Caco-2) using QSPR Modelling for Efficient Drug Discovery.

Background: The quantitative structure-property relationship (QSPR) modelling can be helpful in the in-silico prediction and pre-determination of the drug permeability values of a large number of compounds through human intestinal enterocytes for screening of potential candidate drugs, thereby enhancing oral drug development.

Methods: The present study involved the development of a regression-based QSPR model for the prediction of Caco-2 cell-permeability values of compounds. The training of the model was carried out on a novel large dataset of 1272 compounds with 30 selected 2D descriptors.