title: Improved genetic algorithm for the protein folding problem by use of a Cartesian combination operator.
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.
authors.affiliation: Baker Laboratory of Chemistry, Cornell University, Ithaca, New York 14853-1301, USA.
authors.forename: A A
authors.initials: AA
authors.lastname: Rabow
authors.forename: H A
authors.initials: HA
authors.lastname: Scheraga
mesh_terms: D000465:Algorithms; D008433:Mathematics; D008958:Models, Molecular; D009010:Monte Carlo Method; D017510:Protein Folding; D011506:Proteins / Q000235:genetics*; D013816:Thermodynamics
chemical_list: D011506:Proteins