Protein Structure Prediction in 2D HP Lattice Model Using Differential Evolutionary Algorithm

Abstract

AbstractProtein 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.KeywordsDifferential EvolutionaryLattice ModelDifferential Evolutionary AlgorithmProtein Structure PredictionMutation StrategyThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.