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Inventi Impact - Bioinformatics

Articles

  • Inventi:ebi/8837/14
    A PARALLEL FRAMEWORK FOR MULTIPOINT SPIRAL SEARCH IN AB INITIO PROTEIN STRUCTURE PREDICTION
    Mahmood A Rashid, Swakkhar Shatabda, M A Hakim Newton, Md Tamjidul Hoque, Abdul Sattar

    Protein structure prediction is computationally a very challenging problem. A large number of existing search algorithms attempt to solve the problem by exploring possible structures and finding the one with the minimum free energy.However, these algorithms perform poorly on large sized proteins due to an astronomically wide search space. In this paper, we present a multipoint spiral search framework that uses parallel processing techniques to expedite exploration by starting fromdifferent points. In our approach, a set of random initial solutions are generated and distributed to different threads. We allow each thread to run for a predefined period of time. The improved solutions are stored threadwise.When the threads finish, the solutions are merged together and the duplicates are removed. A selected distinct set of solutions are then split to different threads again. In our ab initio protein structure prediction method, we use the three-dimensional face-centred-cubic lattice for structure-backbone mapping.We use both the low resolution hydrophobic-polar energy model and the high-resolution 20 × 20 energy model for search guiding. The experimental results show that our new parallel framework significantly improves the results obtained by the state-of-the-art single-point search approaches for both energy models on three-dimensional face-centred-cubic lattice.We also experimentally show the effectiveness of mixing energy models within parallel threads.

    How to Cite this Article
    CC Compliant Citation: Mahmood A. Rashid, Swakkhar Shatabda, M. A. Hakim Newton, Md Tamjidul Hoque, and Abdul Sattar, “A Parallel Framework for Multipoint Spiral Search in ab Initio Protein Structure Prediction,” Advances in Bioinformatics, vol. 2014, Article ID 985968, 17 pages, 2014. doi:10.1155/2014/985968. Copyright © 2014 Mahmood A. Rashid et al. This is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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