A topological substructural molecular design approach (TOPS-MODE) has been used to formulate structural rules for binding of substrates of P-glycoprotein (P-gp). We first review some of the models developed in the recent literature for predicting binding to Pgp. Then, we develop a model using TOPS-MODE, which is able to identify 88.4% of substrates and 84.2% of non-substrates. When the model is presented to an external prediction set of 100 substrates and 77 nonsubstrates it identifies correctly 81.8% of all cases. Using TOPS-MODE strategy we found structural contributions for binding to P-gp, which identifies 24 structural fragments responsible for such binding. We then carried out a chemico-biological analysis of some of the structural fragments found as contributing to P-gp binding of substrates. We show that in general the model developed so far can be used as a virtual screening method for identifying substrates of P-gp from large libraries of compounds.
Keywords: TOPS-MODE, knowledge generation, P-glycoprotein, QSAR, molecular modeling, Spectral Moments, graph-theory descriptors, DEREK, TOPKAT, natural detoxification system, (MDRR), linear discriminant analysis (LDA), Automated Rule-Extraction, Randi, ’, s method, biophore, TSET, PSET, P-gp Efflux, MULTICASE, orthogonalization