Elitist Animal Migration Optimization for Protein Structure Prediction based on 3D Off-Lattice Model

Abstract

Predicting the structure of protein has been the center of attraction for the researchers. The aim is to make a reliable prediction of the protein structure by obtaining the minimum energy values among amino acids interactions. According to the generated shape of amino acids, the functionality of the proteins can be determined. However, it is known as one of the most challenging tasks in the field of bioinformatics considering its high computation complexity. Metaheuristic algorithms are mainly preferred by researchers from various fields, since their performances are quite satisfactory in solving such complex problems. Animal Migration Optimization (AMO) algorithm is a metaheuristic approach which mimics the behavior of animals during the migration process. However, in this research to reach a high solution quality, an elitist version of Animal Migration Optimization (ELAMO) algorithm is considered and in particular it is applied to Protein Structure Prediction (PSP) problem. The performance of ELAMO is tested on some well-studied artificial and real protein sequences, and then compared with powerful optimization algorithms which are specially designed for solving PSP problem. The results show that ELAMO is quite capable in solving this problem. Hence, it can be used as an efficient optimizer for solving complex problems that require better solution quality in the field of bioinformatics.