Protein structure prediction in 2D HP lattice model using differential evolutionary Algorithm

Abstract

Protein Structure Prediction (PSP) is a challenging problem in bioinformatics and computational biology research for its immense scope of application in drug design, disease prediction, name a few. Developing a suitable optimization technique for predicting the structure of proteins has been addressed in the paper, using Differential Evolutionary (DE) algorithm applied in the square 2D HP lattice model. In the work, we concentrate on handling infeasible solutions and modify control parameters like population size (NP), scale factor (F), crossover ratio (CR) and mutation strategy of the DE algorithm to improve its performance in PSP problem. The proposed method is compared with the existing methods using benchmark sequence of protein databases, showing very promising and effective performance in PSP problem. © 2012 Springer-Verlag GmbH Berlin Heidelberg.