A filter-and-fan approach to the 2D HP model of the protein folding problem

We examine a prominent and widely-studied model of the protein folding problem, the two-dimensional (2D) HP model, by means of a filter-and-fan (F&F) solution approach. Our method is designed to generate compound moves that explore the solution space in a dynamic and adaptive fashion. Computational results for standard sets of benchmark problems show that the F&F algorithm is highly competitive with the current leading algorithms, requiring only a single solution trial to obtain best known solutions to all problems tested, in contrast to a hundred or more trials required in the typical case to evaluate the performance of the best of the alternative methods.

[1]  Fred Glover.  New Ejection Chain and Alternating Path Methods for Traveling Salesman Problems , 1992, Computer Science and Operations Research.

[2]  F. Glover.  HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS , 1977 .

[3]  Vincenzo Cutello,et al.  Immune Algorithms with Aging Operators for the String Folding Problem and the Protein Folding Problem , 2005, EvoCOP.

[4]  Rolf Backofen.  The Protein Structure Prediction Problem: A Constraint Optimization Approach using a New Lower Bound , 2004, Constraints.

[5]  Fred Glover,et al.  Tabu Search and Adaptive Memory Programming — Advances, Applications and Challenges , 1997 .

[6]  Edmund K. Burke,et al.  Multimeme Algorithms for Protein Structure Prediction , 2002, PPSN.

[7]  D. Covell,et al.  Conformations of folded proteins in restricted spaces. , 1990, Biochemistry.

[8]  Holger H. Hoos,et al.  An Ant Colony Optimization Algorithm for the 2D HP Protein Folding Problem , 2002, Ant Algorithms.

[9]  Mihalis Yannakakis,et al.  On the Complexity of Protein Folding , 1998, J. Comput. Biol..

[10]  Fred W. Glover,et al.  A Template for Scatter Search and Path Relinking , 1997, Artificial Evolution.

[11]  Natalio Krasnogor,et al.  Multimeme Algorithms Using Fuzzy Logic Based Memes For Protein Structure Prediction , 2005 .

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

[13]  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.

[14]  P Argos,et al.  Folding the main chain of small proteins with the genetic algorithm. , 1994, Journal of molecular biology.

[15]  T. Dandekar,et al.  Improving genetic algorithms for protein folding simulations by systematic crossover. , 1999, Bio Systems.

[16]  Holger H. Hoos,et al.  An Improved Ant Colony Optimisation Algorithm for the 2D HP Protein Folding Problem , 2003, Canadian Conference on AI.

[17]  Riccardo Poli,et al.  New ideas in optimization , 1999 .

[18]  Erich Bornberg-Bauer,et al.  Chain growth algorithms for HP-type lattice proteins , 1997, RECOMB '97.

[19]  Jack J. Dongarra,et al.  Performance of various computers using standard linear equations software in a FORTRAN environment , 1988, CARN.

[20]  Hsiao-Ping Hsu,et al.  Growth-based optimization algorithm for lattice heteropolymers. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  F. Richards.  The protein folding problem. , 1991, Scientific American.

[22]  J. Hirst,et al.  The evolutionary landscape of functional model proteins. , 1999, Protein engineering.

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

[24]  C. Reeves.  Modern heuristic techniques for combinatorial problems , 1993 .

[25]  Fred W. Glover,et al.  Tabu Thresholding: Improved Search by Nonmonotonic Trajectories , 1995, INFORMS J. Comput..

[26]  Thomas Lengauer,et al.  Algorithmic research problems in molecular bioinformatics , 1993, [1993] The 2nd Israel Symposium on Theory and Computing Systems.

[27]  Vincenzo Cutello,et al.  An Immune Algorithm for Protein Structure Prediction on Lattice Models , 2007, IEEE Transactions on Evolutionary Computation.

[28]  J. Pekny,et al.  A dynamic Monte Carlo algorithm for exploration of dense conformational spaces in heteropolymers , 1997 .

[29]  John S. Hutchinson,et al.  Flexible Lattice Model To Study Protein Folding , 1996 .

[30]  Goodman,et al.  Multigrid Monte Carlo method for lattice field theories. , 1986, Physical review letters.

[31]  F. Glover.  Scatter search and path relinking , 1999 .

[32]  K. Dill.  Theory for the folding and stability of globular proteins. , 1985, Biochemistry.

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

[34]  J. Onuchic,et al.  Folding kinetics of proteinlike heteropolymers , 1994, cond-mat/9404001.

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

[36]  A. Kolinski,et al.  Simulations of the Folding of a Globular Protein , 1990, Science.

[37]  F. Glover,et al.  In Modern Heuristic Techniques for Combinatorial Problems , 1993 .

[38]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[39]  Holger H. Hoos,et al.  An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem , 2005, BMC Bioinformatics.

[40]  William E. Hart,et al.  Recent Advances in Memetic Algorithms , 2008 .

[41]  P. Grassberger.  Pruned-enriched Rosenbluth method: Simulations of θ polymers of chain length up to 1 000 000 , 1997 .

[42]  William E. Hart,et al.  Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction Better than 86% of Optimal , 1997, J. Comput. Biol..

[43]  K. Dill,et al.  The Protein Folding Problem , 1993 .

[44]  George Chikenji,et al.  MULTI-SELF-OVERLAP ENSEMBLE FOR PROTEIN FOLDING : GROUND STATE SEARCH AND THERMODYNAMICS , 1999, cond-mat/9903003.

[45]  William E. Hart,et al.  Fast Protein Folding in the Hydrophobic-Hydrophillic Model within Three-Eights of Optimal , 1996, J. Comput. Biol..

[46]  Jeffery L. Kennington,et al.  Interfaces in Computer Science and Operations Research , 1997 .

[47]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

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

[49]  Jun S. Liu,et al.  Biopolymer structure simulation and optimization via fragment regrowth Monte Carlo. , 2007, The Journal of chemical physics.

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

[51]  F. Glover,et al.  Local Search and Metaheuristics , 2007 .

[52]  Fred W. Glover,et al.  Ejection Chains, Reference Structures and Alternating Path Methods for Traveling Salesman Problems , 1996, Discret. Appl. Math..

[53]  William E. Hart,et al.  Protein structure prediction with evolutionary algorithms , 1999 .

[54]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[55]  Daan Frenkel,et al.  Configurational bias Monte Carlo: a new sampling scheme for flexible chains , 1992 .