A Memetic Algorithm for Protein Structure Prediction in a 3D-Lattice HP Model. In: Raidl GR, Cagnoni S, Branke J, Corne DW, Drechsler R, Jin Y, Johnson CG, Machado P, Marchiori E, Rothlauf F, Smith GD, Squillero G, editors. Applications of Evolutionary Computing. Berlin: Springer Berlin Heidelberg; 2004. pp. 1-10. [DOI: 10.1007/978-3-540-24653-4_1]

A Novel Branch-and-Bound Algorithm for the Protein Folding Problem in the 3D HP Model

The protein folding problem (PFP) is an important issue in bioinformatics and biochemical physics. One of the most widely studied models of protein folding is the hydrophobic-polar (HP) model introduced by Dill. The PFP in the three-dimensional (3D) lattice HP model has been shown to be NP-complete; the proposed algorithms for solving the problem can therefore only find near-optimal energy structures for most long benchmark sequences within acceptable time periods. In this paper, we propose a novel algorithm based on the branch-and-bound approach to solve the PFP in the 3D lattice HP model. For 10 48-monomer benchmark sequences, our proposed algorithm finds the lowest energies so far within comparable computation times than previous methods.