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Dark kinase annotation, mining, and visualization using the Protein Kinase Ontology.
Soleymani, Saber; Gravel, Nathan; Huang, Liang-Chin; Yeung, Wayland; Bozorgi, Elika; Bendzunas, Nathaniel G; Kochut, Krzysztof J; Kannan, Natarajan.
Afiliação
  • Soleymani S; Department of Computer Science, University of Georgia, Athens, GA, United States.
  • Gravel N; Institute of Bioinformatics, University of Georgia, Athens, GA, United States.
  • Huang LC; Institute of Bioinformatics, University of Georgia, Athens, GA, United States.
  • Yeung W; Institute of Bioinformatics, University of Georgia, Athens, GA, United States.
  • Bozorgi E; Department of Computer Science, University of Georgia, Athens, GA, United States.
  • Bendzunas NG; Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States.
  • Kochut KJ; Department of Computer Science, University of Georgia, Athens, GA, United States.
  • Kannan N; Institute of Bioinformatics, University of Georgia, Athens, GA, United States.
PeerJ ; 11: e16087, 2023.
Article em En | MEDLINE | ID: mdl-38077442
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas Quinases / Neoplasias Limite: Humans Idioma: En Revista: PeerJ Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas Quinases / Neoplasias Limite: Humans Idioma: En Revista: PeerJ Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos