Tackling polypharmacology of kinase inhibitors by transcription factor activity profiling.

Abstract

Protein kinase inhibitors (PKI) are promising drug candidates for many diseases. However, even selective PKIs interact with multiple kinases and non-kinase targets. Existing technologies detect these interactions but not the resultant biological effects. Here, we describe an orthogonal PKI evaluation approach that entails fingerprinting of cell signaling responses. As the readout, we profiled the activity of 45 transcription factors linking signaling pathways to genes. We found that inhibitors of the same kinase family exhibited a consensus TF activity profile (TFAP) invariant to PKI chemistry and mode of action (allosteric, ATP-competitive, or genetic). Specific PKI consensus signatures were found for multiple kinase families (Akt, CDK, Aurora, RAF, MEK, and ERK) with high-similarity consensus signatures of signaling cascade kinases. Thus, the PKI consensus signatures provide bona fide markers of cell response to on-target PKI activity. However, the consensus signatures appeared only at certain inhibitor concentrations ( on-target windows). Using concentration-response signature analysis, we identified PKI interactions dominating cell response at other concentrations. Finally, we illustrate this approach by selecting putative chemical probes for evaluated kinases. Therefore, the effect-based TFAP approach illuminates PKI biology invisible to target-based technologies and provides clear quantitative metrics to aid the selection of polypharmacological PKIs as chemical probes and drug leads.