Protein Folding Structure Prediction Based On Genetic Annealing Algorithm In AB Off-Lattice Model

The biological functions of protein are determined by their dimensional folding structures, and understanding the folding of natural protein remains one of the most challenging objectives in bioinformatics research. In recent years there has been an increasing interest in introducing minimalistic models based on thermodynamic hypothesis that the native structure of protein is the one in which the free energy of the whole system is lowest. Various theoretical computing methods have been applied to formulations of the ab-initio folding problem that are based on simplified models of protein structure. These methods still have some disadvantages in practical applications. They can hardly converge to the global optimum with the increasing of parameters. On the basis of AB off-lattice model consisting of hydrophobic and hydrophilic residues, a novel hybrid algorithm that combines genetic algorithm and simulated annealing is presented for dealing with multi-extremum and multi-parameter problem in this thesis. A kind of optimization of the crossover and mutation operators in the genetic annealing algorithm is implemented, and a new sort strategy of the current hypotheses is designed. The optimization hybrid algorithm is feasible to predict protein folding structure, and can insure the solution quality when used to search for the global minimum energy conformations of proteins with AB off-lattice model.An extension of a two dimensions (2D) to three dimensions (3D) AB off-lattice model is also given. The 3D model also has only two types of residues, hydrophobic and hydrophilic, which considered the torsional energy implicitly. The research results indicate that comparing with 2D AB off-lattice model, the AB off-lattice model in three dimensions displays the important feature of the real proteins.We design and implement the genetic annealing algorithm, and the application of the algorithm in 2D AB off-lattice model and 3D AB off-lattice model. Experimental results demonstrate that genetic annealing algorithm is of better performance and accuracy compared to the previous methods.