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ProKinO: A Unified Resource for Mining the Cancer Kinome
Authors:Daniel Ian McSkimming  Shima Dastgheib  Eric Talevich  Anish Narayanan  Samiksha Katiyar  Susan S Taylor  Krys Kochut  Natarajan Kannan
Institution:1. Institute of Bioinformatics, University of Georgia, Athens, Georgia;2. Department of Computer Science, University of Georgia, Athens, Georgia;3. Department of Dermatology, UCSF School of Medicine, San Francisco, California;4. Department of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia;5. Department of Chemistry and Biochemistry, Department of Pharmacology, La Jolla, California
Abstract:Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challenge. Here, we describe an ontological framework for integrating and conceptualizing diverse forms of information related to kinase activation and regulatory mechanisms in a machine readable, human understandable form. We demonstrate the utility of this framework in analyzing the cancer kinome, and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify a novel mutational hotspot in the αC‐β4 loop of the kinase domain and demonstrate the functional impact of the identified variants in epidermal growth factor receptor (EGFR) constitutive activity and inhibitor sensitivity. We provide a unified resource for the kinase and cancer community, ProKinO, housed at http://vulcan.cs.uga.edu/prokino .
Keywords:personalized medicine  cancer therapy  database  drug discovery  big data  disease  mutation  resistance  kinase  conformation  regulation
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