| URL: | https://prokino.uga.edu |
| Full name: | The Protein Kinase Ontology |
| Description: | The Protein Kinase Ontology (ProKinO) is an ontology and knowledge graph, which provides a controlled vocabulary of terms, their hierarchy, and relationships unifying sequence, structure, function, mutation and pathway information on kinases. The conceptual representation of such diverse information in one place enables not only rapid discovery of significant information related to a specific protein kinase, but also enables large scale integrative analysis of the protein kinase family. |
| Year founded: | 2023 |
| Last update: | 2023-12-05 |
| Version: | v1.0 |
| Accessibility: |
Accessible
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| Country/Region: | United States |
| Data type: | |
| Data object: |
NA
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| Database category: | |
| Major species: |
NA
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| Keywords: |
| University/Institution: | University of Georgia |
| Address: | |
| City: | |
| Province/State: | |
| Country/Region: | United States |
| Contact name (PI/Team): | Krzysztof J. Kochut |
| Contact email (PI/Helpdesk): | kkochut@uga.edu |
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Dark kinase annotation, mining, and visualization using the Protein Kinase Ontology. [PMID: 38077442]
The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships among protein kinase sequence, structure, function, and disease in a human and machine-readable format. In this study, we have significantly expanded ProKinO by incorporating additional data on expression patterns and drug interactions. Furthermore, we have developed a completely new browser from the ground up to render the knowledge graph visible and interactive on the web. We have enriched ProKinO with new classes and relationships that capture information on kinase ligand binding sites, expression patterns, and functional features. These additions extend ProKinO's capabilities as a discovery tool, enabling it to uncover novel insights about understudied members of the protein kinase family. We next demonstrate the application of ProKinO. 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 kinases in human cancers with abnormal expression in multiple cancers, including a previously unappreciated role in acute myeloid leukemia. We have identified recurrent oncogenic mutations in the PAK5 activation loop predicted to alter substrate binding and phosphorylation. Additionally, we have identified common ligand/drug binding residues in PAK family kinases, underscoring ProKinO's potential application in drug discovery. The updated ontology browser and the addition of a web component, ProtVista, which enables 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 https://prokino.uga.edu. |