@inproceedings{Will:PSB2002,
author = {Will, Sebastian},
title = {Constraint-based Hydrophobic Core Construction for
         Protein Structure Prediction in the
         Face-Centered-Cubic Lattice},
booktitle = {Proceedings of the Pacific Symposium on Biocomputing
             2002 (PSB 2002)},
year = {2002},
doi = {https://pubmed.ncbi.nlm.nih.gov/11928518/},
user = {will},
publisher = {World Scientific Publishing Co. Pte. Ltd.},
pmid = {11928518},
pages = {661--672},
editor = {Russ B. Altman and A. Keith Dunker and Lawrence
          Hunter and Teri E. Klein},
address = {Singapore},
abstract = {We present an algorithm for exact protein structure
            prediction in the FCC-HP-model. This model is a
            lattice protein model on the face-centered-cubic
            lattice that models the main force of protein
            folding, namely the hydrophobic force. The structure
            prediction for this model can be based on the
            construction of hydrophobic cores. The main focus of
            the paper is on an algorithm for constructing
            maximally and submaximally compact hydrophobic cores
            of a given size. This algorithm treats core
            construction as a constraint satisfaction problem
            (CSP), and the paper describes its constraint
            model. The algorithm employs symmetry excluding
            constraint-based search [Backofen, Will: CP99] and
            relies heavily on good upper bounds on the number of
            contacts. Here, we use and strengthen upper bounds
            presented earlier. [Backofen, Will: CPM2001] The
            resulting structure prediction algorithm (including
            previous work [Backofen, Will: CPM2001, Backofen,
            Will: CP2001]) handles sequences of sizes in the
            range of real proteins fast, i.e. we predict a first
            structure often within a few minutes. The algorithm
            is the first exact one for the FCC, besides full
            enumeration which is impracticable for chain lengths
            greater than about 15. We tested the algorithm
            succesfully up to sequence length of 160, which is
            far beyond the capabilities even of previous
            heuristic approaches.}
}