A massively parallel speciation‐based differential evolution algorithm applied to the 3D‐AB protein structure prediction

Abstract

One of the most challenging problems in Bioinformatics is the finding of a protein conformation and it is known as the Protein Structure Prediction (PSP) problem. The main feature present in the AB off‐lattice model is the use of polarity as the main driving force to guide the optimization process. The present work proposes an adaptive evolutionary algorithm based on GPU that is applied to the 3D‐AB off‐lattice PSP problem. The proposed approach is named cuDSMjDE, and is composed of a Dynamic Speciation‐based Mutation Strategies Differential Evolution that employs the jDE mechanism to control F and CR parameters. A crowding strategy is also adopted, increasing competition between individuals and maintaining the diversity of solutions. All routines of the proposed algorithm are developed to run in GPU. During the experiments, eight Protein Data Bank sequences are employed. Results obtained concerning potential energy are competitive when compared with state‐of‐the‐art algorithms. The use of a massively parallel architecture promoted the necessary scalability with speedups up to 708.78×.