Extremal Optimization for protein folding simulations on the lattice

This paper presents a novel guided search strategy Extremal Optimization (EO) with constrained structure for protein folding. In the proposed algorithm, evaluating the fitness of each monomer in an amino-acid sequence is introduced to guide the improvement of the conformation. In addition, a constrained structure is proposed to reduce the complexity of algorithm. We demonstrate that EO can be applied successfully to the protein folding problem. The results show that the algorithm can find the best solutions so far for the listed benchmarks. Within the achieved results, the search converged rapidly and efficiently.

[1]  P. Grassberger,et al.  Testing a new Monte Carlo algorithm for protein folding , 1997, Proteins.

[2]  Frank Thomson Leighton,et al.  Protein folding in the hydrophobic-hydrophilic (HP) is NP-complete , 1998, RECOMB '98.

[3]  Stefan Boettcher,et al.  Extremal optimization at the phase transition of the three-coloring problem. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Mohamed El Bachir Menai,et al.  Efficient Initial Solution to Extremal Optimization Algorithm for Weighted MAXSAT Problem , 2003, IEA/AIE.

[5]  Sue Whitesides,et al.  A complete and effective move set for simplified protein folding , 2003, RECOMB '03.

[6]  P. Grassberger,et al.  Growth algorithms for lattice heteropolymers at low temperatures , 2002, cond-mat/0208042.

[7]  R Unger,et al.  Genetic algorithms for protein folding simulations. , 1992, Journal of molecular biology.

[8]  Stefan Boettcher Extremal Optimization: Heuristics Via Co-Evolutionary Avalanches , 2000, Comput. Sci. Eng..

[9]  Songde Ma,et al.  Protein folding simulations of the hydrophobic–hydrophilic model by combining tabu search with genetic algorithms , 2003 .

[10]  Madhu Chetty,et al.  A new guided genetic algorithm for 2D hydrophobic-hydrophilic model to predict protein folding , 2005, 2005 IEEE Congress on Evolutionary Computation.

[11]  K. Dill,et al.  A lattice statistical mechanics model of the conformational and sequence spaces of proteins , 1989 .

[12]  S. Boettcher Extremal Optimization of Graph Partitioning at the Percolation Threshold , 1999, cond-mat/9901353.

[13]  A. Percus,et al.  Nature's Way of Optimizing , 1999, Artif. Intell..

[14]  U H Hansmann,et al.  New Monte Carlo algorithms for protein folding. , 1999, Current opinion in structural biology.

[15]  W. Wong,et al.  Evolutionary Monte Carlo for protein folding simulations , 2001 .

[16]  B. Vollmayr-Lee,et al.  Fast and accurate coarsening simulation with an unconditionally stable time step. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  C. Anfinsen,et al.  The kinetics of formation of native ribonuclease during oxidation of the reduced polypeptide chain. , 1961, Proceedings of the National Academy of Sciences of the United States of America.