@Article{Backofen:Will:Constraints2006,
  author =	 {Rolf Backofen and Sebastian Will},
  title =	 {A Constraint-Based Approach to Fast and Exact Structure
                  Prediction in Three-Dimensional Protein Models},
  journal =	 {Journal of Constraints},
  year =	 2006,
  url =          {http://ai.uwaterloo.ca/~vanbeek/Constraints/constraints.html#volume11},
  volume =       11,
  number =       1,
  pages =        {5--30},
  publisher =    {Springer Netherlands},
  issn =         {1383-7133 (Paper) 1572-9354 (Online)},
  doi =          {10.1007/s10601-006-6848-8},
  month =        {January},
  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},
  user =	 {will}
}