Kinase Inhibitor Profiling Against Disease-Associated Mutant Kinases

Kinase Inhibitor Profiling against Disease-Associated Mutant Kinases

Kinases participate in many signaling pathways, including those involved in cell proliferation, growth, metabolism, apoptosis, and differentiation. Not surprisingly, kinases are mutationally activated in a number of disorders. Small-molecule inhibitor development represents a major focus of drug discovery efforts to treat these disorders.
Well over two dozen kinase inhibitors are approved for clinical use by the Food and Drug Administration (FDA) and many others are in clinical development. A major challenge challenge is target promiscuity because most small-molecule kinase inhibitors target the ATP binding site, a highly conserved region in kinases.
Therefore, compounds designed to target this site often inhibit other kinases as well. Indeed, several recent large-scale screens have revealed numerous off-target effects for both commonly used research tool compounds and clinical kinase inhibitors.
In some cases, these studies have identified unexpected kinase targets inhibited more potently by a compound than that compound’s intended target. Therefore, broad profiling of compounds against kinase libraries can be used for repurposing existing agents based on unexpected activity against unrelated kinases.
One particularly exciting application of broad profiling is the identification of potent and selective inhibitors of mutant kinases. Disease-associated kinase domain mutations can increase kinase activity.

To identify opportunities to repurpose inhibitors against disease-associated mutant kinases, researchers conducted a large-scale functional screen of 183 known kinase inhibitors against 76 recombinant mutant kinases.

The results revealed lead compounds with activity against clinically important mutant kinases, including ALK, LRRK2, RET, and EGFR, as well as unexpected opportunities for repurposing FDA-approved kinase inhibitors as leads for additional indications.

Furthermore, using T674I PDGFRα as an example, authors show how single-dose screening data can provide predictive structure-activity data to guide subsequent inhibitor optimization.

This study provides a resource for the development of inhibitors against numerous disease-associated mutant kinases and illustrates the potential of unbiased profiling as an approach to compound-centric inhibitor development.