NDLI: Improved genetic algorithm for the protein folding problem by use of a Cartesian combination operator.

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Improved genetic algorithm for the protein folding problem by use of a Cartesian combination operator.

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Improved genetic algorithm for the protein folding problem by use of a Cartesian combination operator.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Scheraga, H. A. Rabow, A. A.
Description	Country affiliation: United States Author Affiliation: Rabow AA ( Baker Laboratory of Chemistry, Cornell University, Ithaca, New York 14853-1301, USA.)
Abstract	We have devised a Cartesian combination operator and coding scheme for improving the performance of genetic algorithms applied to the protein folding problem. The genetic coding consists of the C alpha Cartesian coordinates of the protein chain. The recombination of the genes of the parents is accomplished by: (1) a rigid superposition of one parent chain on the other, to make the relation of Cartesian coordinates meaningful, then, (2) the chains of the children are formed through a linear combination of the coordinates of their parents. The children produced with this Cartesian combination operator scheme have similar topology and retain the long-range contacts of their parents. The new scheme is significantly more efficient than the standard genetic algorithm methods for locating low-energy conformations of proteins. The considerable superiority of genetic algorithms over Monte Carlo optimization methods is also demonstrated. We have also devised a new dynamic programming lattice fitting procedure for use with the Cartesian combination operator method. The procedure finds excellent fits of real-space chains to the lattice while satisfying bond-length, bond-angle, and overlap constraints.
ISSN	09618368
e-ISSN	1469896X
Journal	Protein Science
Issue Number	9
Volume Number	5
Language	English
Publisher	Wiley-Blackwell (on behalf of The Protein Society)
Publisher Date	1996-09-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Algorithms Protein Folding Proteins Genetics Mathematics Models, Molecular Monte Carlo Method Thermodynamics Comparative Study Research Support, Non-u.s. Gov't Research Support, U.s. Gov't, Non-p.h.s. Research Support, U.s. Gov't, P.h.s. Discipline Biochemistry
Content Type	Text
Resource Type	Article
Subject	Medicine Molecular Biology Biochemistry

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