Recent advances in mass spectrometry-based chemical proteomics allow unbiased analysis of drug-target interactions under close to physiological conditions. In this study, we designed and synthesized two small molecule probes targeting fibroblast growth factor receptors (FGFRs) and applied them to evaluate the selectivity profiles of the FGFR inhibitors Dovitinib and Orantinib. Probe F2 was capable of enriching all members of the FGF receptor family as well as other kinases involved in cancer such as KDR, FLT4 and RET from lysates of cancer cells or human placenta tissue. In combination with the established Kinobeads™ approach, probe F2 facilitated the identification of the target spectrum of the two inhibitors confirming many of the previously identified (off-) targets such as AURKA, FLT4-VEGFR3, IKBKE and PDGFRβ. The newly synthesized probe enlarges the arsenal of chemical proteomic tools for the expression profiling of kinases and selectivity profiling of their inhibitors. It will also be useful in applications aiming at a better understanding of a drug's cellular mechanisms of action as well as highlighting potential beneficial or adverse side effects.
The synthesis of a new chemical affinity probe targeting FGF-receptors and many other kinases improved the general scope of drug selectivity profiling by chemical proteomics. The application of the developed chemical tool identified most of the known targets for the advanced clinical kinase inhibitors Dovitinib and Orantinib thus exemplify the practical utility of the developed probe and the results obtained shed further light on how these drugs exert their anti-cancer activity in cells. More generally speaking, the significance of the work is that the molecular tools presented here extend the application scope of kinobeads based kinase profiling to FGFR/VEGFR/PDGFR families, which thus may be generically employed for selectivity profiling of kinase inhibitors using chemical proteomics. The overall aim of such studies is to improve our understanding of how target as well as off-target profiles can be used to assess or predict the therapeutic efficacy of a drug.
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