@article{Backofen:Will:Constraints2006,
author = {Backofen, Rolf and Will, Sebastian},
title = {A Constraint-Based Approach to Fast and Exact Structure
         Prediction in Three-Dimensional Protein Models},
journal = {Journal of Constraints},
year = {2006},
doi = {10.1007/s10601-006-6848-8},
volume = {11},
user = {will},
publisher = {Springer Netherlands},
pages = {5--30},
number = {1},
month = {January},
issn = {1383-7133 (Paper) 1572-9354 (Online)},
abstract = {Simplified protein models are used for investigating general
            properties of proteins and principles of protein
            folding. Furthermore, they are suited for hierarchical
            approaches to protein structure prediction. A well known
            protein model is the HPmodel of Lau and Dill [33], which
            models the important aspect of hydrophobicity. One can
            define the HP-model for various lattices, among them
            two-dimensional and three-dimensional ones. Here, we
            investigate the three-dimensional case. The main motivation
            for studying simplified protein models is to be able to
            predict model structures much more quickly and more
            accurately than is possible for real proteins. However, up
            to now there was a dilemma: the algorithmically tractable,
            simple protein models can not model real protein structures
            with good quality and introduce strong artifacts. <p> We
            present a constraint-based method that largely improves this
            situation. It outperforms all existing approaches for
            lattice protein folding in HP-models. This approach is the
            first one that can be applied to two three-dimensional
            lattices, namely the cubic lattice and the
            face-centered-cubic (FCC ) lattice. Moreover, it is the only
            exact method for the FCC lattice. The ability to use the FCC
            lattice is a significant improvement over the cubic
            lattice. The key to our approach is the ability to compute
            maximally compact sets of points (used as hydrophobic
            cores), which we accomplish for the first time for the FCC
            lattice. <p> Keywords: protein structure prediction,
            HP-model, face-centered cubic lattice, constraint
            programming}
}