Protein Structure Prediction Based on an Improved Genetic Algorithm

Protein structure prediction problem has been focused much attention upon. Genetic algorithm as a useful computational tool for addressing optimization tasks has been applied to this domain. In this paper, considering the deficiency of simple genetic algorithm, such as prematurity and slow convergence, we propose HPGA/GBX which is an improvement of GA and the algorithm is evaluated with three standard test functions. The experimental results show the effectiveness of the proposed method. Then HPGAGBX is applied to protein tertiary structure prediction and compared with other methods. The target protein in this paper is Met-enkephalin. The results show that HPGAGBX is a very good method in finding the minimum energy of small protein.