篇名 | Protein 3D HP Model Folding Simulation Using a Hybrid of Genetic Algorithm and Particle Swarm Optimization |
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卷期 | 13:2 |
作者 | Cheng-Jian Lin 、 Shih-Chieh Su |
頁次 | 140-147 |
關鍵字 | Protein structure prediction 、 three- dimensional HP lattice model 、 particle swarm optimization 、 genetic algorithm 、 EI 、 SCI 、 SCIE 、 Scopus |
出刊日期 | 201106 |
Given the amino-acid sequence of a protein, the prediction of a protein’s tertiary structure is known as the protein folding problem. The protein folding problem in the hydrophobic-hydrophilic lattice model is the problem of finding the lowest energy conformation. This is the NP-complete problem. In order to enhance the procedure performance for predicting protein structures, a hybrid genetic-based particle swarm optimization (PSO) is proposed. Simulation results indicate that our approach outperforms the existing evolutionary algorithms. The method can be applied successfully to the protein folding problem based on the three-dimensional hydrophobic- hydrophilic lattice model.