Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors
Fig 5
Prediction of target interactions for an investigational kinase inhibitor tivozanib.
(a) Predicted and measured bioactivity profiles of tivozanib against its 3 established on-targets (FLT1, FLT4, KDR; average bioactivity from ChEMBL; S3 Table) and 7 predicted off-target kinases tested in our experimental assay. Pearson correlation r = 0.668 (p = 0.035). When no clear compound-kinase interaction was observed in our assay, the pIC50 value was set to 4.9 M, corresponding to the highest drug concentration used (12,500 nM). Predicted values belong to approximately constant range because we focused on experimental validation of the model-predicted off-target interactions. Three of them turned out to be false positives, and therefore the range of experimental results varies more than the range of predicted values. (b) Evaluation of negative interaction predictions from the model. Among 82 kinases with low predicted binding affinities (pKi < 6 M), 64 were screened by Gao et al., and 59 of these are not likely targets of tivozanib (as they have at least 50% of the activity remaining at the high compound concentration of 1 μM).