Integrating mutation data and structural analysis of the TP53 tumor-suppressor protein

Authors

  • Andrew C.R. Martin,

    Corresponding author
    1. School of Animal and Microbial Sciences, University of Reading, Reading, UK
    • School of Animal and Microbial Sciences, University of Reading, Whiteknights, PO Box 228, Reading RG6 6AJ, UK
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  • Angelo M. Facchiano,

    1. CRISCEB-Research Center of Computational and Biotechnological Sciences, Second University of Naples, Naples, Italy
    Current affiliation:
    1. Istituto di Scienze dell’Alimentazione, CNR, via Roma 52 A/C, 83100 Avellino, Italy
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  • Alison L. Cuff,

    1. School of Animal and Microbial Sciences, University of Reading, Reading, UK
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  • Tina Hernandez-Boussard,

    1. International Agency for Research on Cancer, Lyon, France
    Current affiliation:
    1. Department of Genetics, Stanford University, Stanford, CA 94305-5120
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  • Magali Olivier,

    1. International Agency for Research on Cancer, Lyon, France
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  • Pierre Hainaut,

    1. International Agency for Research on Cancer, Lyon, France
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  • Janet M. Thornton

    1. Biomolecular Structure and Modelling Unit, Department of Biochemistry and Molecular Biology, University College London, London, UK
    2. Department of Crystallography, Birkbeck College, London, UK
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Abstract

TP53 encodes p53, which is a nuclear phosphoprotein with cancer-inhibiting properties. In response to DNA damage, p53 is activated and mediates a set of antiproliferative responses including cell-cycle arrest and apoptosis. Mutations in the TP53 gene are associated with more than 50% of human cancers, and 90% of these affect p53-DNA interactions, resulting in a partial or complete loss of transactivation functions. These mutations affect the structural integrity and/or p53-DNA interactions, leading to the partial or complete loss of the protein’s function. We report here the results of a systematic automated analysis of the effects of p53 mutations on the structure of the core domain of the protein. We found that 304 of the 882 (34.4%) distinct mutations reported in the core domain can be explained in structural terms by their predicted effects on protein folding or on protein-DNA contacts. The proportion of “explained” mutations increased to 55.6% when substitutions of evolutionary conserved amino acids were included. The automated method of structural analysis developed here may be applied to other frequently mutated gene mutations such as dystrophin, BRCA1, and G6PD. Hum Mutat 19:149–164, 2002. © 2002 Wiley-Liss, Inc.

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