Protein folding structure optimization based on GAPSO algorithm in the off-lattice model

Predicting the spacial folding structure of a protein, given its sequence of amino acids, is one of the central problems in computational biology field. This paper studies the AB off-lattice model with two species of monomers, called hydrophobic (A) and hydrophilic (B). Based on this simplified model, the low energy configurations are searched by using the GAPSO. A kind of optimization about the mutation mechanism and the Euclidean interference mechanism are presented, where a novel local adjustment strategy is also used to enhance the searching ability of the global minimum within the AB off-lattice model. Starting from random conformations, the GAPSO method can find the low-energy conformation of the Fibonacci sequences and the real protein sequences. Compared with other optimization methods, the proposed novel method could converge to the lower energy folds. It appears that the proposed method can used for solving protein folding problem, which is based on the thermodynamic hypothesis.