Computer evaluation of drug interactions with P-glycoprotein

Abstract

The (Q)SAR models for evaluating the structure-property relationships, fit for prediction of drug interactions with P-glycoprotein as inhibitors or substrates, were constructed using PASS and GUSAR software. The models were constructed and validated on the basis of information on the structure and characteristics of 256 and 94 compounds used as P-glycoprotein substrates and inhibitors, respectively. The initial samples were divided 80:20 into training and test samples. The best prediction accuracy for the test samples was 78% for P-glycoprotein substrate prediction (PASS) and 89% for inhibitor prediction (GUSAR).