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
Link To Document