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  • The Road Not Taken: Retreat and Diverge in Local Search for Simplified Protein Structure Prediction

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    Author(s)
    Shatabda, Swakkhar
    Newton, MA Hakim
    Rashid, Mahmood A
    Pham, Duc Nghia
    Sattar, Abdul
    Griffith University Author(s)
    Sattar, Abdul
    Rashid, Mahmood A.
    Year published
    2013
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    Abstract
    Background: Given a protein's amino acid sequence, the protein structure prediction problem is to find a three dimensional structure that has the native energy level. For many decades, it has been one of the most challenging problems in computational biology. A simplified version of the problem is to find an on-lattice self-avoiding walk that minimizes the interaction energy among the amino acids. Local search methods have been preferably used in solving the protein structure prediction problem for their efficiency in finding very good solutions quickly. However, they suffer mainly from two problems: re-visitation and ...
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    Background: Given a protein's amino acid sequence, the protein structure prediction problem is to find a three dimensional structure that has the native energy level. For many decades, it has been one of the most challenging problems in computational biology. A simplified version of the problem is to find an on-lattice self-avoiding walk that minimizes the interaction energy among the amino acids. Local search methods have been preferably used in solving the protein structure prediction problem for their efficiency in finding very good solutions quickly. However, they suffer mainly from two problems: re-visitation and stagnancy. Results: In this paper, we present an efficient local search algorithm that deals with these two problems. During search, we select the best candidate at each iteration, but store the unexplored second best candidates in a set of elite conformations, and explore them whenever the search faces stagnation. Moreover, we propose a new non-isomorphic encoding for the protein conformations to store the conformations and to check similarity when applied with a memory based search. This new encoding helps eliminate conformations that are equivalent under rotation and translation, and thus results in better prevention of re-visitation. Conclusion: On standard benchmark proteins, our algorithm significantly outperforms the state-of-the art approaches for Hydrophobic-Polar energy models and Face Centered Cubic Lattice.
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    Conference Title
    BMC BIOINFORMATICS
    Volume
    14
    Publisher URI
    http://www.apbc2013.org/
    DOI
    https://doi.org/10.1186/1471-2105-14-S2-S19
    Copyright Statement
    © 2013 Shatabda et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Note
    Page numbers are not for citation purposes. Instead, this article has the unique article number of S19.
    Subject
    Mathematical sciences
    Biological sciences
    Information and computing sciences
    Artificial intelligence not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/53588
    Collection
    • Conference outputs

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