PeerJBioinformaticsPeer-reviewed journal article
Dark kinase annotation, mining and visualization using the Protein Kinase Ontology
Saber SoleymaniiD, Nathan GraveliD, Liang‐Chin HuangiD, Wayland YeungiD, Elika Bozorgi, N. George Bendzunas, Krzysztof KochutiD, Natarajan KannaniD
Abstract
The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships connecting protein kinase sequence, structure, function, and disease in a human and machine-readable format. Here we extend the scope of ProKinO as a discovery tool by including new classes and relationships capturing information on kinase ligand binding sites, expression patterns, and functional features, and demonstrate its application in uncovering new knowledge regarding understudied members of the protein kinase family. Specifically, through graph mining and aggregate SPARQL queries, we identify the p21-activated protein kinase 5 (PAK5) as one of the most frequently mutated dark kinase in human cancers with abnormal expression in multiple cancers, including an unappreciated role in acute myeloid leukemia. We identify recurrent oncogenic mutations in the PAK5 activation loop predicted to alter substrate binding and phosphorylation and identify common ligand/drug binding residues in PAK family kinases, highlighting the potential application of ProKinO in drug discovery. The updated ontology browser and a web component, ProtVista, which allows interactive mining of kinase sequence annotations in 3D structures and Alphafold models, provide a valuable resource for the signaling community. The updated ProKinO database is accessible at http://prokino.uga.edu/browser/.
- organism: human
- assay: protein structure
- research focus: database / resource
- approach: statistical model
- Citations
- 13
- FWCI
- 1.07
- Field percentile
- top 25%
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