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Abstract
BackgroundProtein folding structure prediction is one of the most challenging problems in the bioinformatics domain. Because of the complexity of the realistic protein structure, the simplified structure model and the computational method should be adopted in the research. The AB off-lattice model is one of the simplification models, which only considers two classes of amino acids, hydrophobic (A) residues and hydrophilic (B) residues.ResultsThe main work of this paper is to discuss how to optimize the lowest energy configurations in 2D off-lattice model and 3D off-lattice model by using Fibonacci sequences and real protein sequences. In order to avoid falling into local minimum and faster convergence to the global minimum, we introduce a novel method (SATS) to the protein structure problem, which combines simulated annealing algorithm and tabu search algorithm. Various strategies, such as the new encoding strategy, the adaptive neighborhood generation strategy and the local adjustment strategy, are adopted successfully for high-speed searching the optimal conformation corresponds to the lowest energy of the protein sequences. Experimental results show that some of the results obtained by the improved SATS are better than those reported in previous literatures, and we can sure that the lowest energy folding state for short Fibonacci sequences have been found.ConclusionsAlthough the off-lattice models is not very realistic, they can reflect some important characteristics of the realistic protein. It can be found that 3D off-lattice model is more like native folding structure of the realistic protein than 2D off-lattice model. In addition, compared with some previous researches, the proposed hybrid algorithm can more effectively and more quickly search the spatial folding structure of a protein chain.
Highlights
Protein folding structure prediction is one of the most challenging problems in the bioinformatics domain
This paper describes a protein structure prediction method that is based on the AB offlattice model in two dimension and three dimension, which combines the tabu search algorithm and local adjust simulation annealing
In the experiments of protein folding structure prediction, the Fibonacci sequences are usually selected as the experiment data to test the performance of the optimization algorithm
Summary
Protein folding structure prediction is one of the most challenging problems in the bioinformatics domain. Due to the polypeptide chain forms such large number of different spatial structure, it is still difficult to search for the global minimum energy conformations of proteins from its sequence of amino acids [2]. The most important problem is how to establish a highly simplified but effective model which can reflect the relation between the free energy and tertiary structure of the protein. One of the simplified protein models is the hydrophobic-polar (HP) model which has been widely used to study protein structure and understand protein folding process. The HP-lattice model represents the amino acid chains of a protein using two types of residue, non-polar or hydrophobic (H) residue and polar (P) or hydrophilic residue are on the vertices of a simple cubic lattices[3]. The main reason lies in that local interactions are neglected in the simplified models, while local interactions might be important for the local structure of the chains [6]
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