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Dark kinase annotation, mining and visualization using the Protein Kinase Ontology

View ORCID ProfileSaber Soleymani, View ORCID ProfileNathan Gravel, View ORCID ProfileLiang-Chin Huang, View ORCID ProfileWayland Yeung, Elika Bozorgi, View ORCID ProfileNathaniel G. Bendzunas, View ORCID ProfileKrzysztof J. Kochut, Natarajan Kannan
doi: https://doi.org/10.1101/2022.02.25.482021
Saber Soleymani
3Department of Computer Science, University of Georgia, Athens, GA 30602, USA
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Nathan Gravel
2Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
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  • ORCID record for Nathan Gravel
Liang-Chin Huang
2Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
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  • ORCID record for Liang-Chin Huang
Wayland Yeung
2Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
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Elika Bozorgi
3Department of Computer Science, University of Georgia, Athens, GA 30602, USA
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Nathaniel G. Bendzunas
1Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602, USA
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  • ORCID record for Nathaniel G. Bendzunas
Krzysztof J. Kochut
3Department of Computer Science, University of Georgia, Athens, GA 30602, USA
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  • For correspondence: nkannan@uga.edu kkochut@uga.edu
Natarajan Kannan
1Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602, USA
2Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
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  • For correspondence: nkannan@uga.edu kkochut@uga.edu
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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/.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 01, 2022.
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Dark kinase annotation, mining and visualization using the Protein Kinase Ontology
Saber Soleymani, Nathan Gravel, Liang-Chin Huang, Wayland Yeung, Elika Bozorgi, Nathaniel G. Bendzunas, Krzysztof J. Kochut, Natarajan Kannan
bioRxiv 2022.02.25.482021; doi: https://doi.org/10.1101/2022.02.25.482021
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Dark kinase annotation, mining and visualization using the Protein Kinase Ontology
Saber Soleymani, Nathan Gravel, Liang-Chin Huang, Wayland Yeung, Elika Bozorgi, Nathaniel G. Bendzunas, Krzysztof J. Kochut, Natarajan Kannan
bioRxiv 2022.02.25.482021; doi: https://doi.org/10.1101/2022.02.25.482021

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