A new genetic algorithm for simplified protein structure prediction

Authors:
Mahmood A. Rashid;Md. Tamjidul Hoque;M. A. Hakim Newton;Duc Nghia Pham;Abdul Sattar
Affiliations:
Queensland Research Lab, National ICT Australia, Australia, Institute for Integrated & Intelligent Systems, Griffith University, Australia;Computer Science, University of New Orleans;Queensland Research Lab, National ICT Australia, Australia, Institute for Integrated & Intelligent Systems, Griffith University, Australia;Queensland Research Lab, National ICT Australia, Australia, Institute for Integrated & Intelligent Systems, Griffith University, Australia;Queensland Research Lab, National ICT Australia, Australia, Institute for Integrated & Intelligent Systems, Griffith University, Australia
Venue:
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Year:
2012

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Abstract

In this paper, we present a new genetic algorithm for protein structure prediction problem using face-centred cubic lattice and hydrophobic-polar energy model. Our algorithm uses i) an exhaustive generation approach to diversify the search; ii) a novel hydrophobic core-directed macro move to intensify the search; and iii) a random-walk strategy to recover from stagnation. On a set of standard benchmark proteins, our algorithm significantly outperforms the state-of-the-art algorithms for the same models.