Protein kinase-focused drug discovery efforts are escalating rapidly as research continues to elucidate and define the role of kinases in a growing list of diseases. To date, these research efforts have yielded eight FDA-approved small molecule kinase inhibitors with over 500 more in active development. While kinase inhibitors demonstrate great promise for disease treatment and management, target selectivity is a common challenge in drug development.
High-throughput screening in kinase inhibitor discovery is an effective platform for hit identification, compound annotation, and selectivity profiling. In the traditional kinase inhibitor discovery paradigm, however, a compound library is typically interrogated against a single kinase.
The disadvantage with this approach is that it may overlook off-target interactions that may be important for understanding biological activity. Additionally, only a limited view of a library’s kinome-wide inhibition potential is provided, which may prevent identification of other therapeutically relevant interactions.
Continued advances in high-throughput screening technologies, assay platforms, and kinase panel size have enabled researchers to make broader assessments of compound/ kinase selectivity earlier in the discovery and development process. This offers the benefit of thorough library annotation of privileged kinase-focused compound libraries and the ability to quickly identify novel candidates. It can also reveal opportunities to expand therapeutic utility of existing compounds.
Although a number of service providers and kit options have emerged to facilitate discovery efforts, most provide limited kinase assay breadth, and many utilize varying assay formats within the panel, making it difficult to compare results.
Moreover, assays are not performed under standardized assay conditions, which can reduce assay sensitivity while making it difficult to compare data across kinases.
To bridge the gulf between small molecule compound libraries and quantitative kinase selectivity profiling, KINOMEscan™ (a division of Ambit Biosciences) has developed a high-throughput, active site-dependent competition-binding assay platform. Available as a custom service, this technology provides scientists with access to a large commercially available panel of robust kinase assays (Figure 1) and reproducible, high-quality data.
This approach permits a large number of compounds to be run in parallel as a single experiment with highly standardized assay conditions and reagents. It also allows scientists to quantitatively evaluate and compare compounds against a large number of distinct kinases and important mutant forms to obtain necessary potency and selectivity data to support discovery programs.
In the KINOMEscan platform a test compound is combined with human kinases tagged with DNA and an active-site directed ligand that is immobilized on a solid support (Figure 2). During equilibration, if the test compound binds to the kinase and either directly or indirectly competes with the ligand, fewer kinase molecules are able to interact with the active site directed ligand.
Conversely, if the test compound does not compete, kinase molecules are free to bind to the immobilized ligand. The results are then read out by quantifying the amount of tagged kinase bound to the solid support using highly sensitive quantitative PCR.
To assess assay performance of the KINOMEscan platform, we examined the Z´ values for each of the 402 assays. Z´ values were calculated for each kinase based on 16 control wells per experiment in more than 135 independent primary screen experiments spanning a period of 10 months. The average Z´ value across all of the 402 assays ranges from 0.58 to 0.82 with an average of 0.74 (Figure 3). Z´ values > 0.5 are indicative of a highly robust assay.
To evaluate data consistency, Sunitinib, a multikinase inhibitor, was profiled in 14 independent experiments against the 402-kinase panel over a one-year period at a standard 10 µM concentration.
Correlation analysis was performed in a pair-wise manner to calculate the correlation coefficients for all possible combinations (Figure 4). The correlation coefficients range from 0.92 to 0.99 with an average of 0.96. Studies using Sorafenib, Erlotinib, and Gefitinib showed similar results (data not shown). These results illustrate the high level of data consistency over time utilizing KINOMEscan.
The number of kinases shown to be directly involved in disease processes—either singly or in concert—is growing; as signal transduction pathways continue to be unraveled, more kinases will emerge as potential targets of therapeutic relevance.
Therefore, gaining as much information about the kinase profile of an inhibitor is critical and underscores the importance of early-stage profiling against large assay panels. By using a larger kinase panel researchers are afforded a more complete view of compound selectivity, which can assist in uncovering interactions with other therapeutically relevant kinases, thus unlocking greater opportunities for a broader range of clinical applications.
Small molecule kinase inhibitors offer considerable promise as therapeutics in a number of chronic and acute diseases. However, discovery and development of targeted, selective inhibitors remains a challenge.
KINOMEscan provides a robust high-throughput competitive binding assay platform that allows screening of compounds in parallel as a single experiment using highly standardized assay conditions and reagents. This permits quantitative analysis of compound selectivity and potency against a large number of distinct kinases and important mutant forms as part of a comprehensive kinase inhibitor discovery process.
Mazen Karaman, Ph.D., is a research scientist, Dan Jones (email@example.com) is director of marketing and sales, and Paul Gallant is senior director of screening operations for KINOMEscan™ (a division of Ambit Biosciences). Web: www.kinomescan.com.