Chain growth algorithms for HP-type lattice proteins
RECOMB '97 Proceedings of the first annual international conference on Computational molecular biology
Protein folding in the hydrophobic-hydrophilic (HP) is NP-complete
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
On the complexity of protein folding (abstract)
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
Constraint (Logic) Programming: A Survey on Research and Applications
Selected papers from the Joint ERCIM/Compulog Net Workshop on New Trends in Contraints
Fast, Constraint-Based Threading of HP-Sequences to Hydrophobic Cores
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
An Upper Bound for Number of Contacts in the HP-Model on the Face-Centered-Cubic Lattice (FCC)
COM '00 Proceedings of the 11th Annual Symposium on Combinatorial Pattern Matching
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The protein structure prediction problem is one of the most (if not the most) important problem in computational biology. This problem consists of finding the conformation of a protein (i.e., a sequence of amino-acids) with minimal energy. Because of the complexity of this problem, simplified models like Dill's HP-lattice model [12] have become a major tool for investigating general properties of protein folding. Even for this simplified model, the structure prediction problem has been shown to be NP-complete [3, 5]. We describe a constraint formulation of the HP-model structure prediction problem, present the basic constraints and search strategy. We then introduce a novel, general technique for excluding geometrical symmetries in constraint programming. To our knowledge, this is the first general and declarative technique for excluding symmetries in constraint programming that can be added to an existing implementation. Finally, we describe a new lower bound on the energy of an HP-protein. Both techniques yield an efficient pruning of the search tree.