Lattice model refinement of protein structures

To find the best lattice model representation of a given full atom protein structure is a hard computational problem. Several greedy methods have been suggested where results are usually biased and leave room for improvement. In this paper we formulate and implement a Constraint Programming method to refine such lattice structure models. We show that the approach is able to provide better quality solutions. The prototype is implemented in COLA and is based on limited discrepancy search. Finally, some promising extensions based on local search are discussed.Comment: In Proceedings of Workshop on Constraint Based Methods for Bioinformatics (WCB 2010); Jul 21, 2010; Edinburgh, UK (co-located with ICLP 2010); 7 page

Constraint-based Local Move Definitions for Lattice Protein Models Including Side Chains

The simulation of a protein's folding process is often done via stochastic local search, which requires a procedure to apply structural changes onto a given conformation. Here, we introduce a constraint-based approach to enumerate lattice protein structures according to k-local moves in arbitrary lattices. Our declarative description is much more flexible for extensions than standard operational formulations. It enables a generic calculation of k-local neighbors in backbone-only and side chain models. We exemplify the procedure using a simple hierarchical folding scheme.Comment: Published in Proceedings of the Fifth Workshop on Constraint Based Methods for Bioinformatics (WCB09), 2009, 10 page

A Hybrid Local Search for Simplified Protein Structure Prediction

Protein structure prediction based on Hydrophobic-Polar energy model essentially becomes searching for a conformation having a compact hydrophobic core at the center. The hydrophobic core minimizes the interaction energy between the amino acids of the given protein. Local search algorithms can quickly find very good conformations by moving repeatedly from the current solution to its "best" neighbor. However, once such a compact hydrophobic core is found, the search stagnates and spends enormous effort in quest of an alternative core. In this paper, we attempt to restructure segments of a conformation with such compact core. We select one large segment or a number of small segments and apply exhaustive local search. We also apply a mix of heuristics so that one heuristic can help escape local minima of another. We evaluated our algorithm by using Face Centered Cubic (FCC) Lattice on a set of standard benchmark proteins and obtain significantly better results than that of the state-of-the-art methods