• DocumentCode
    3571583
  • Title

    Parameterizing genetic algorithms for protein folding simulation

  • Author

    Schulze-Kremer, S. ; Tiedemann

  • Author_Institution
    Brainware GmbH, Berlin
  • fYear
    1994
  • fDate
    2/28/1994 12:00:00 AM
  • Firstpage
    42583
  • Lastpage
    42589
  • Abstract
    A genetic algorithm is used to search energetically and structurally favorable conformations. The authors use a hybrid protein representation, three operators to manipulate the protein `genes´, and a fitness function based on a simple force field. The prototype was applied to the ab initio prediciton of Crambin. None of the conformations generated with a non-biased fitness function are similar to the native conformation but all of them show a much better overall fitness than the native structure. If guided by r.m.s. deviation the native conformation was reproduced at 1.3 Å. Therefore, the genetic algorithm´s search was successful but the fitness function was no good indicator for native structure. In a side chain placement experiment Crambin was reproduced at 1.86 Å r.m.s deviation
  • Keywords
    biology computing; genetic algorithms; macromolecular configurations; molecular biophysics; proteins; Crambin; ab initio prediciton; algorithm parameterizing; energetically favorable conformations; fitness function; genetic algorithm; hybrid protein representation; native conformation; protein folding simulation; structurally favorable conformations;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Molecular Bioinformatics, IEE Colloquium on
  • Type

    conf

  • Filename
    297403