HP Model Protein Folding with Hybrid Algorithm using Genetic Algorithm and Estimation of Distribution Algorithm

This paper describes a hybrid algorithm of Genetic Algorithm (GA) and Estimation of Distribution Algorithm (EDA) to solve the Protein Structure Prediction (PSP) based on lattice Hydrophobic-Polar (HP) models. This system is a hybrid algorithm using GA and EDA. In the system, network constructed by EDA is used in GA to generate effective gene. PSP is one of the challenging problems in bioinformatics. The goal of the problem is to predict the conformation from the given amino acid sequence. However even for a small number of amino acids, the solution space is huge. This paper introduces experimental data about PSP problem on lattice HP models, and the experimental results showed that proposed system searched solutions effectively compare with single population algorithm. These results are concluded that proposed method works effectively for searching candidate solution.