A data analytics framework for mining the dark kinome

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Project Summary The overall goal of this proposal is to generate and experimentally test models of understudied “dark” kinase evolution and function, and to develop a data-analytics framework for hypothesis generation and testing on the dark kinome. Our working hypothesis is that integrative mining of available sequence, structure, and functional data on the entire kinome from diverse organisms (both well-studied and dark kinases) will provide important context for defining sequence and structural features associated with dark kinase functions. As a preliminary test of our hypothesis, we have integrated and conceptualized diverse forms of data related to protein kinase structure, function, and evolution in the form of the Protein Kinase Ontology (ProKinO), and successfully demonstrated the application of an ontological framework in identifying key knowledge gaps in the human kinome and in discovering key residues/motifs associated with protein kinase regulation. We propose to build on these successful studies to accomplish the following two aims. Aim1 will develop a novel comparative kinomics framework in which natural and disease variants in dark kinases will be correlated and visualized in the context of PTMs and protein-protein interactions to investigate the relationships connecting sequence, structure, function and regulation. Models of functional specialization will be experimentally tested in selected dark and pseudokinases using biochemical and cell-based assays and made publically available in human and machine-readable format, adhering to Findable, Accessible, Interoperable and Reusable (FAIR) data rules. Aim2 will build a unique framework for complex aggregate queries on semantically linked protein kinase data from disparate sources and formats using graphical, easy to use interfaces. Researchers will interact with the framework and formulate queries based on a familiar and intuitive view of the data. A knowledge map-based interactive query interface will be developed using which researchers can interact with ProKinO using semantics they use and understand. ProKinO will be formally linked with Pharos, the Drug Target Ontology (DTO) and the Protein Ontology (PRO) to expand community outreach and user base. The proposed studies are expected to provide a unified data analytics framework for knowledge discovery and hypothesis generation on the dark kinome and enhance the ability of the Illuminating the Druggable Genome (IDG) consortium to make accurate predictions about the physiological roles of dark kinases. The proposed integration of ProKinO with DTO and PRO will enhance the application of these ontologies in drug discovery and provide open source software for building data instantiated ontologies for other IDG targets such as ion- channels and GPCRs. These outcomes, in turn, are expected to accelerate the functional characterization of the druggable “dark” proteome and address the IDG initiative of translating genomic data into knowledge for drug discovery.