Investigating relevant aspects of MOEAs for protein structures prediction
Christiane Regina Soares Brasil, Alexandre C. B. Delbem, Daniel Bonetti · 2011
Several computational models have been developed in the context of the Protein Structure Prediction (PSP) problem. These methods involve a combinatorial problem and can be solved using optimizing algorithms in order to search for a global minimum energy. Genetic Algorithms (GAs) have produced relevant results in this area. Several energies in the protein are known to be directly responsible for the stabilization of their structures. These energies can represent each objective of multiobjective evolutionary algorithms. Many techniques, as the NSGA-II, are used to deal with the multi-objective approach for proteins, however they are not adequate for the PSP problem. New strategies have been sought with multiple criteria. In this context, this paper introduces the application of multiobjective evolutionary algorithm on tables algorithm to the PSP problem. In order to evaluate this approach, we compare it with the well-known NSGA-II algorithm. The new approach investigated for PSP can generate protein structures with energies significantly smaller than those generated by the NSGA-II.