Comparing Alternative Energy Functions for the HP Model of Protein Structure Prediction

Protein structure prediction is the problem of finding the functional conformation of a protein given only its amino acid sequence. The HP lattice model is an abstract formulation of this problem, which captures the fact that hydrophobicity is one of the major driving forces in the protein folding process. This model represents a hard combinatorial optimization problem and has been widely addressed through metaheuristics such as evolutionary algorithms. However, the conventional energy (evaluation) function of the HP model does not provide an adequate discrimination among potential solutions, which is an essential requirement for metaheuristics in order to perform an effective search. Therefore, alternative energy functions have been proposed in the literature to cope with this issue. In this study, we inquire into the effectiveness of several of such alternative approaches. We analyzed the degree of discrimination provided by each of the studied functions as well as their impact on the behavior of a basic memetic algorithm. The obtained results support the relevance of following this research direction. To our knowledge, this is the first work reported in this regard.