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Use of a novel Hill-climbing genetic algorithm in protein folding simulations

Cooper, L. R., Corne, D. W. and Crabbe, M. J. C. (2003) Use of a novel Hill-climbing genetic algorithm in protein folding simulations. Computational Biology and Chemistry, 27 (6). pp. 575-580. ISSN 1476-9271

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To link to this item DOI: 10.1016/s1476-9271(03)00047-1


We have developed a novel Hill-climbing genetic algorithm (GA) for simulation of protein folding. The program (written in C) builds a set of Cartesian points to represent an unfolded polypeptide's backbone. The dihedral angles determining the chain's configuration are stored in an array of chromosome structures that is copied and then mutated. The fitness of the mutated chain's configuration is determined by its radius of gyration. A four-helix bundle was used to optimise simulation conditions, and the program was compared with other, larger, genetic algorithms on a variety of structures. The program ran 50% faster than other GA programs. Overall, tests on 100 non-redundant structures gave comparable results to other genetic algorithms, with the Hill-climbing program running from between 20 and 50% faster. Examples including crambin, cytochrome c, cytochrome B and hemerythrin gave good secondary structure fits with overall alpha carbon atom rms deviations of between 5 and 5.6 Angstrom with an optimised hydrophobic term in the fitness function. (C) 2003 Elsevier Ltd. All rights reserved.

Item Type:Article
Divisions:Life Sciences > School of Biological Sciences
ID Code:10707
Uncontrolled Keywords:fitness function, crambin, gamma crystallin, supercomputer, GA, SECONDARY STRUCTURE, SEQUENCE

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