Discovery of novel EphB4 inhibitors based on pharmacophore modeling and virtual screening techniques

The objective of this paper was to discover new potent inhibitors against EphB4 for cancer therapy via computer-aided drug design strategies including 3D-QSAR modeling, virtual screening and molecular docking. The first step was to generate pharmacophore models based on Catalyst/HypoGen algorithm. The best model, Hypo1, had the highest Correl value(0. 96), the lowest RMS value(0. 89), the closest total cost(101. 26)to fixed cost(89. 20), and the best Δcost(89. 14). Subsequently, Hypo1 was subjected to test set validation and Fischer′s randomization verification and was then used as a 3D query to screen database. In order to further narrow the number of hits, drug-likeness screening and molecular docking techniques were applied. Finally, 23 novel molecules with diverse scaffolds were selected as possible candidates against EphB4 for further studies based on predicted activity analysis, docking scores, and binding mode analysis.