DocumentCode :
2074475
Title :
Parameterizing genetic algorithms for protein folding simulation
Author :
Schulze-Kremer, Steffen ; Tiedemann
Author_Institution :
Brainware GmbH, Berlin, Germany
Volume :
5
fYear :
1994
fDate :
4-7 Jan. 1994
Firstpage :
345
Lastpage :
354
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 prediction 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 /spl Aring/. 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 /spl Aring/ r.m.s. deviation.<>
Keywords :
biology computing; genetic algorithms; molecular biophysics; molecular configurations; pattern recognition; physics computing; proteins; ab initio prediction; conformations; favorable conformations; genetic algorithm; genetic algorithms; protein; protein folding simulation; structure evaluation; tertiary structure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on
Conference_Location :
Wailea, HI, USA
Print_ISBN :
0-8186-5090-7
Type :
conf
DOI :
10.1109/HICSS.1994.323562
Filename :
323562
Link To Document :
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