Progress toward virtual screening for drug side effects

Abstract

The development and application of a computational protocol for conducting virtual screens of drug side interactions is described. A conventional drug-docking algorithm (AutoDock) is used to conduct two separate studies. First, a series of docking simulations is performed by using guanosine diphosphate and adenosine diphosphate as prototype drugs with the goal of successfully differentiating known receptors from a large number of bait receptors. Using the electrostatic energy of the purine ring as a basis for discrimination allows the correct identification of receptors in blind studies with 100% specificity and 94% sensitivity. In a second study, similar methodology is used to investigate the binding of clinically relevant inhibitors (Gleevec, purvalanol A, and hymenialdisine) to a variety of protein kinase targets. Overall, excellent agreement between experimental and predicted preferences for kinase targets is obtained. An important conclusion from the latter study is that homology-modeled structures of putative receptors may reasonably be used as targets for docking when directly solved crystal structures are not available. The prospects for routine application of the methodology as a means of identifying potential side interactions of candidate drugs are discussed.