ENHANCED HONEY BEES COLONY- ALGORITHMS FOR PROTEIN TERTIARY STRUCTURE PREDICTION

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Date
2011-04
Authors
ABDALLAH BAHAMISH, HESHAM A WADH
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Abstract
There is no doubt about the role that protein plays in the biological processes inside the human body. Proteins are able to perform their biological functions when they fold into their tertiary structure. Experimental protein tertiary structure prediction methods are time consuming and expensive and it is not always possible to determine the protein structure experimentally. Scientists from many fields work to develop theoretical and computational methods which provide cost effective solutions to the protein structure prediction problem. Computationally, the protein structure prediction problem is formulated as an optimisation problem and the goal is to search the protein conformational search space to find the lowest free energy conformation (protein structure). The aim of this study is to investigate and explore for the first time, the capability of the honey bees colony-based algorithms in searching the protein conformational search space to find the lowest free energy conformation, and to incorporate parallel techniques into the protein conformational search algorithms to enhance the protein conformational search. The principles of marriage in the honey bees' colony (MBO algorithm) and the honey bee colony's foraging behaviour (ABC algorithm) were adapted to solve protein conformational search problem. Parallel algorithms were developed to enhance the performance of the search algorithms. The adapted algorithms were able to find the reported lowest free energy conformation for the test proteins. The lowest free energy conformation of Met-enkephalin was found (-12.42 and -12.9101 kcal/mol). Lower free energy conformations for C-peptide and good structures for the 12 bioactive peptides were found. The parallel MBO algorithm gained near linear speedup and the parallel ABC algorithm gained linear speed-up.
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ENHANCED HONEY BEES COLONY- ALGORITHMS
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