Mapping the Full Kinase Landscape: Beyond Druggable Targets

Over 100 kinase inhibitors have now been approved by the FDA, transforming the treatment of cancer and other diseases.¹ Yet despite this progress, a key question remains underexplored: can these drugs be repurposed to target newly identified oncogenic kinase variants or those emerging through strong drug resistance, and how can a deeper understanding of their broader target profiles inform the next generation of kinase-targeted therapies? 

A new study published in Nature Biotechnology, conducted in collaboration between Fred Hutchinson Cancer Center and Reaction Biology, offers the most comprehensive answer to date.² By profiling 92 clinical kinase inhibitors against 758 kinases, including 409 wild-type enzymes and 349 oncogenic variants derived from patient tumor samples, the research team generated over 65,000 kinase-drug interactions, revealing selectivity patterns, repurposing opportunities, and mutation-specific gaps that had not been systematically characterized until now. 

Beyond Primary Targets 

Most kinase inhibitors are developed, labeled, and marketed for a single primary target. Imatinib is a BCR-ABL inhibitor. Osimertinib targets EGFR. But the reality of kinase pharmacology is more complex: many approved drugs bind and inhibit additional kinases beyond their intended target. This “polypharmacology” has traditionally been viewed as a liability and a source of off-target toxicity. However, in some contexts, multi-target activity correlates with improved efficacy, particularly in diseases like cancer, where inhibiting an entire signaling cascade may be more effective than blocking a single node. 

The challenge has been a lack of systematic data. Previous profiling efforts were limited in scale, often covering a few dozen approved drugs or focusing almost exclusively on wild-type kinases. For example, one of the most comprehensive prior studies profiled 243 clinical kinase inhibitors but assessed binding against only 253 wild-type kinases, with minimal evaluation of mutant variants.³ However, clinically relevant oncogenic mutations remained largely uncharted. 

This study changes that. By applying Reaction Biology’s HotSpot radiometric assay platform across the full inhibitor set and an expanded kinase panel that includes 311 point mutations and 38 gene fusions identified in patient tumors, the research team was able to map the true selectivity landscape of approved kinase drugs. 

Expanding the Druggable Kinome 

One of the study’s most striking findings is the expansion of the druggable kinase space. The 92 profiled inhibitors were originally designed to target 86 primary kinases. But by analyzing off-target activity using validated selectivity metrics, the team identified an additional 146 kinases that can be effectively inhibited by at least one existing drug—expanding the actionable target landscape from 86 to 235. 

This has immediate implications for drug repurposing. For example, the study identified tepotinib, an approved MET inhibitor, as a potent dual inhibitor of IRAK1 and IRAK4—kinases implicated in glioblastoma, inflammatory diseases, and cholesterol metabolism. The finding was validated in glioblastoma neurosphere models and in vivo, demonstrating that tepotinib significantly reduced tumor growth through modulation of cholesterol-related pathways. 

Similarly, brigatinib, approved as an ALK inhibitor, was shown to potently inhibit MARK2/3, kinases involved in Hippo/YAP signaling and implicated in pancreatic cancer. Single-agent brigatinib treatment suppressed YAP target gene expression and reduced tumor growth in mouse models, suggesting a new application for an existing drug. 

Mutation-Specific Selectivity 

Perhaps the most clinically urgent insight from the study concerns mutation-specific drug activity. Not all inhibitors designed for a given kinase are equally effective against all variants of that kinase. The data revealed that approved FGFR inhibitors: futibatinib, pemigatinib, and infigratinib, fail to adequately cover six clinically reported FGFR variants. Similarly, certain MET mutations at residue D1228 confer resistance to approved MET inhibitors like capmatinib and tepotinib. 

In both cases, the profiling data enabled identification of alternative approved drugs that retain activity against the resistant variants. Gilteritinib, a FLT3 inhibitor, was validated as effective against hard-to-treat MET mutations. Erdafitinib and pralsetinib (a known RET kinase inhibitor) showed activity against resistant FGFR variants. These findings underscore the value of comprehensive profiling in guiding precision oncology decisions, particularly for patients whose tumors harbor resistance mutations. 

An Open Resource for the Research Community 

To make the full dataset accessible, the research team developed KIRHub (kirhub.org), an interactive web-based platform that allows researchers to explore kinase inhibitor selectivity, identify drugs targeting specific mutations, and visualize kinase dependencies across cancer lineages. The platform is freely available and requires no data uploads, enabling immediate exploration of the results. 

What’s Next 

For researchers navigating kinase target selection, resistance profiling, or repurposing hypotheses, this dataset offers a new foundation. For Reaction Biology, it reflects the scientific depth behind our kinase profiling capabilities and our commitment to generating data that advances the field. 

We invite you to explore the findings in detail at an upcoming live webinar featuring the study’s authors from Fred Hutchinson Cancer Center and Reaction Biology. Register here. 

References

1. Mullard A. FDA approves 100th small-molecule kinase inhibitor. Nat Rev Drug Discov. 2025;24:891-895.
2. Saifudeen M, Zhu S, Liang S, et al. Comprehensive profiling of clinical kinase inhibitors reveals opportunities for drug repurposing and uncovering new biology. Nature Biotechnology. 2026. https://doi.org/10.1038/s41587-026-03090-8
3. Klaeger S, Heinzlmeir S, Wilhelm M, et al. The target landscape of clinical kinase drugs. Science. 2017;358(6367):eaan4368.