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

被引:48
作者
Rabow, AA [1 ]
Scheraga, HA [1 ]
机构
[1] CORNELL UNIV,BAKER LAB CHEM,ITHACA,NY 14853
关键词
conformational search; dynamic programming; genetic algorithms; lattice fitting; Monte Carlo optimization; protein folding; protein structure prediction;
D O I
10.1002/pro.5560050906
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:1800 / 1815
页数:16
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