Kinases are dynamic proteins, adopting different conformations that are associated with their catalytic activity and preference for particular Kinase Inhibitors (KIs) structures. KIs are typically classified based on the kinase conformation they bind, where different types of KIs may exhibit distinct biophysical, biochemical, and pharmacokinetic properties. Despite considerable effort, the current known chemical space of KIs is limited, partly due to the high costs of both chemical synthesis and activity profiling of KIs, as well as high-throughput determination of kinase structures. Here we present newly developed computational tools to advance kinase drug discovery. We first assessed a range of structural features derived from key structural motifs of the kinases (e.g., the aC-helix and DFG-motif) to define the conformational space of the catalytic domain of protein kinases. We then constructed Kinformation, a random forest classifier that annotates the conformation of over 3,500 protein kinase structures in the PDB. Our classification scheme captures known active and inactive kinase conformations and defines an additional conformational state, thereby refining the current understanding of the kinase conformational space. Second, we analyzed the small molecules co-crystalized with kinases. Our analysis identified chemical scaffolds that are correlated with conformational selectivity of the kinase targets. Subsequently, we developed KinaMetrix, a comprehensive publicly accessible web-resource for studying kinase pharmacology and drug discovery. KinaMetrix serves as a repository for small molecule substructures that are significantly associated with each conformation type as well as homology models of inactive kinase conformations. Finally, we use these methods to tackle challenges in kinase pharmacology. Particularly, we combine our predictions with Drosophila genetics, to rationally design clinically relevant multi-kinase inhibitors targeting reprogrammed networks in thyroid cancer, as well as inhibitors against an emerging diabetes drug target. Our studies improve our understanding of protein kinase structure and dynamics and expand the pharmacological space of the kinome.

Strategies to design conformation-specific kinase inhibitors

2019 Fall National Meeting

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