An Improved Particle Swarm Optimization for Protein Folding Prediction

In this paper, we combine particle swarm optimization (PSO) and levy flight to solve the problem of protein folding prediction, which is based on 3D AB off- lattice model. PSO has slow convergence speed and low precision in its late period, so we introduce levy flight into it to improve the precision and enhance the capability of jumping out of the local optima through particle mutation mechanism. Experiments show that the proposed method outperforms other algorithms on the accuracy of calculating the protein sequence energy value, which is turned to be an effective way to analyze protein structure.