• DocumentCode
    932311
  • Title

    Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants

  • Author

    Danziger, S.A. ; Swamidass, S.J. ; Jue Zeng ; Dearth, L.R. ; Qiang Lu ; Chen, J.H. ; Cheng, James ; Hoang, V.P. ; Saigo, H. ; Luo, R. ; Baldi, P. ; Brachmann, R.K. ; Lathrop, R.H.

  • Author_Institution
    California Univ., Irvine, CA
  • Volume
    3
  • Issue
    2
  • fYear
    2006
  • Firstpage
    114
  • Lastpage
    125
  • Abstract
    Many biomedical problems relate to mutant functional properties across a sequence space of interest, e.g., flu, cancer, and HIV. Detailed knowledge of mutant properties and function improves medical treatment and prevention. A functional census of p53 cancer rescue mutants would aid the search for cancer treatments from p53 mutant rescue. We devised a general methodology for conducting a functional census of a mutation sequence space by choosing informative mutants early. The methodology was tested in a double-blind predictive test on the functional rescue property of 71 novel putative p53 cancer rescue mutants iteratively predicted in sets of three (24 iterations). The first double-blind 15-point moving accuracy was 47 percent and the last was 86 percent; r = 0.01 before an epiphanic 16th iteration and r = 0.92 afterward. Useful mutants were chosen early (overall r = 0.80). Code and data are freely available (http://www.igb.uci.edu/research/research.html, corresponding authors: R.H.L. for computation and R.K.B. for biology)
  • Keywords
    cancer; codes; iterative methods; medical computing; molecular biophysics; prediction theory; proteins; HIV; cancer; cancer treatments; code; double-blind predictive test; flu; functional census; iteration; medical prevention; medical treatment; mutation sequence spaces; p53 cancer rescue mutants; Cancer; DNA; Genetic mutations; Human immunodeficiency virus; Immune system; Influenza; Medical treatment; Neoplasms; Sequences; Testing; Biology and genetics; feature extraction or construction; machine learning; medicine and science.; Artificial Intelligence; Binding Sites; Computational Biology; Humans; Internet; Models, Molecular; Models, Statistical; Mutation; Mutation, Missense; Neoplasms; Protein Folding; Protein Structure, Tertiary; ROC Curve; Suppression, Genetic; Surface Properties; Tumor Suppressor Protein p53;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2006.22
  • Filename
    1631993