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The biological role of a protein is defined through the specific structure of this protein, which is known as the native structure. The challenge of protein structure prediction (PSP) is the identification of the native structure of proteins from their amino acid sequences. Although a number of experimental methods have been successfully applied to solve some small instances or those with specific properties of the protein structure prediction problem, they require huge computational time and resources. Given the limitations of existing experimental methods, computational methods have become the key to solving this problem. Several optimization algorithms have been successfully applied to solve the PSP in simplified models. In this paper, we propose an efficient hybrid genetic algorithm to predict the three-dimensional conformation of the protein in the hydrophobic-polar model.
