Parallel Protein Structure Prediction by Multiobjective Optimization

The protein structure prediction (PSP) problem is considered an open problem as there is no recognized "best" procedure to find solutions. Moreover, this problem presents a vast search space and the analysis of each conformation requires significant amount of computing time. Thus, parallel processing could provide new opportunities to improve the quality of the solutions found until now. In this paper we use a parallel multiobjective evolutionary approach to the problem including a method to decrease the complexity of the problem by reducing the set of variables involved in the optimization process. The proposed parallel procedure provides linear speedups in the structure prediction of the proteins used as benchmarks.