The road not taken: retreat and diverge in local search for simplified protein structure prediction

BMC Bioinformatics

Proceedings

Mahmood A Rashid¹  Swakkhar Shatabda¹  MA Hakim Newton¹  Duc Nghia Pham¹  Abdul Sattar¹ 

[1] Institute of Intelligent and Integrated Systems, Griffith University, Queensland, Australia;Queensland Research Laboratory, National ICT of Australia, Australia;

关键词: Local Search;    Tabu Search;    Tabu List;    Protein Structure Prediction;    Face Center Cubic;   

DOI  :  10.1186/1471-2105-14-S2-S19

来源: Springer

【 摘 要 】

BackgroundGiven 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.ResultsIn 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.ConclusionOn standard benchmark proteins, our algorithm significantly outperforms the state-of-the art approaches for Hydrophobic-Polar energy models and Face Centered Cubic Lattice.

【 授权许可】

CC BY   
© Shatabda et al.; licensee BioMed Central Ltd. 2013