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    Three-Dimentional Structures of Autophosphorylation Complexes in Crystals of Protein Kinases

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    Type
    Presentation
    Authors
    Dumbrack, Roland
    Date
    2016-01-26
    Permanent link to this record
    http://hdl.handle.net/10754/601418
    
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    Abstract
    Protein kinase autophosphorylation is a common regulatory mechanism in cell signaling pathways. Several autophosphorylation complexes have been identified in crystals of protein kinases, with a known serine, threonine, or tyrosine autophosphorylation site of one kinase monomer sitting in the active site of another monomer of the same protein in the crystal. We utilized a structural bioinformatics method to identify all such autophosphorylation complexes in X-ray crystallographic structures in the Protein Data Bank (PDB) by generating all unique kinase/kinase interfaces within and between asymmetric units of each crystal and measuring the distance between the hydroxyl oxygen of potential autophosphorylation sites and the oxygen atoms of the active site aspartic acid residue side chain. We have identified 15 unique autophosphorylation complexes in the PDB, of which 5 complexes have not previously been described in the relevant publications on the crystal structures (N-terminal juxtamembrane regions of CSF1R and EPHA2, activation loop tyrosines of LCK and IGF1R, and a serine in a nuclear localization signal region of CLK2. Mutation of residues in the autophosphorylation complex interface of LCK either severely impaired autophosphorylation or increased it. Taking the autophosphorylation complexes as a whole and comparing them with peptide-substrate/kinase complexes, we observe a number of important features among them. The novel and previously observed autophosphorylation sites are conserved in many kinases, indicating that by homology we can extend the relevance of these complexes to many other clinically relevant drug targets.
    Conference/Event name
    KAUST Research Conference on Computational and Experimental Interfaces of Big Data and Biotechnology
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    KAUST Research Conference on Computational and Experimental Interfaces of Big Data and Biotechnology, January 2016

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