Identifying Novel Targets by using Drug-binding Site Signature: A Case Study of Kinase Inhibitors

Abstract

7Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to 2 8 the mechanism-independent effects of these drugs. Identifying these mechanism-independent 2 9 interactions could improve drug safety and support drug repurposing. We have developed 3 0 "iDTPnd", a computational approach for large-scale discovery of novel targets for known drugs. 1For a given drug, we construct a positive and a negative structural signature that captures the 3 2 weakly conserved structural features of drug binding sites. To facilitate assessment of unintended 3 3 targets iDTPnd also provides a docking-based interaction score and its statistical significance. 4We were able to confirm the interaction of sorafenib, imatinib, dasatinib, sunitinib, and 3 5 pazopanib with their known targets at a sensitivity and specificity of 52% and 55% respectively. 6We have validated 10 predicted novel targets, using in vitro experiments. Our results suggest that 3 7 proteins other than kinases, such as nuclear receptors, cytochrome P450 or MHC Class I 3 8 molecules can also be physiologically relevant targets of kinase inhibitors. Our method is general 3 9 and broadly applicable for the identification of protein-small molecule interactions, when 4 0 sufficient drug-target 3D data are available. 4 1 Keywords 4 2 Protein-drug interactions; iDTPnd; Kinase inhibitors; Drug binding site signatures 4 3