Protein Folding Prediction with Genetic Algorithms

Hydrophobic-hydrophilic model (HP model) is one of the most simplified and popular protein folding models. This model considers the hydrophobichydrophobic interactions of protein structures, but the results of prediction are not encouraged enough. Therefore, we suggest that some other features should be considered, such as SSEs, charges, and disulfide bonds. In this paper we propose a genetic algorithm (GA) with more possible considerations based on the lattice model to predict the 3D structure of an unknown protein, target protein, whose primary sequence and secondary structure elements (SSEs) are assumed known. Experimental results show that these additional features indeed improve the prediction accuracy by comparing our prediction results with their real structures with RMSD.