A New Genetic Algorithm for Simplified Protein Structure Prediction

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Author(s)
Rashid, MA
Hoque, MT
Newton, MAH
Pham, DN
Sattar, A
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M. Thielscher, D. Zhang

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2012
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384102 bytes

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Sydney, Australia

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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.

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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7691 LNAI

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© 2012 Springer Berlin/Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com

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Artificial intelligence not elsewhere classified

Information and computing sciences

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