Parallel Algorithm for the HP Protein Folding Problem

Proteins play a key role in cells´ function and metabolism. Their functions are directly related with the three-dimensional (3D) native structure. Different algorithms have been proposed to predict the 3D protein structure from the amino acids sequence by minimizing its free energy, nonetheless, this problem still a great challenge in structural biology. The space of possible conformations becomes very large for long proteins, making it difficult to search for the optimal minimum free energy with the available computational resources. Due to the complexity involved in the protein folding problem the researchers have developed some simplified protein models as the hydrophobic-polar (HP). In this work we propose a parallel algorithm to predict protein conformations in HP model by dividing tasks among processing nodes distributed in a server cluster. With this approach we circumvent the memory constraints observed by other approaches. We discuss the correctness of the algorithm based on the verification results achieved by model checking. The performance of our algorithm was evaluated but although benefits of parallel execution are noticeable for small proteins, we demonstrated that our algorithm has an exponential complexity.