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