Abstract
Proteins are essentially sequences of amino acids. They adopt specific folded 3-dimensional structures to perform specific tasks. The formation of 3-dimensional structures is largely guided by the constituent amino acids. Therefore, the positional presence of amino acids in a sequence might play important roles during the protein folding process. In this paper, we present a new heuristic derived from the positional patterns of amino acids in a sequence. With the help of a biased tabu tenure, we apply this heuristic within a spiral search algorithm. The spiral search is an efficient algorithm to develop hydrophobic core in a protein structure pulling hydrophobic amino acids towards the core centre in a spiral fashion. On a set of standard benchmark proteins, we experimentally show that applying our new heuristic improves the performance of a spiral search algorithm consistently.
Keywords
- Protein Structure Prediction
- Spiral Search
- Local Search
- Lattice Models
- Amino Acid Patterns
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Rashid, M.A., Polash, M.M.A., Newton, M.A.H., Hoque, M.T., Sattar, A. (2014). Amino Acids Pattern-Biased Spiral Search for Protein Structure Prediction. In: Pham, DN., Park, SB. (eds) PRICAI 2014: Trends in Artificial Intelligence. PRICAI 2014. Lecture Notes in Computer Science(), vol 8862. Springer, Cham. https://doi.org/10.1007/978-3-319-13560-1_12
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DOI: https://doi.org/10.1007/978-3-319-13560-1_12
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