Annealing contour Monte Carlo algorithm for structure optimization in an off-lattice protein model.

We present a space annealing version for a contour Monte Carlo algorithm and show that it can be applied successfully to finding the ground states for an off-lattice protein model. The comparison shows that the algorithm has made a significant improvement over the pruned-enriched-Rosenbluth method and the Metropolis Monte Carlo method in finding the ground states for AB models. For all sequences, the algorithm has renewed the putative ground energy values in the two-dimensional AB model and set the putative ground energy values in the three-dimensional AB model.

[1]  Jun S. Liu,et al.  A new sequential importance sampling method and its application to the two-dimensional hydrophobic-hydrophilic model , 2002 .

[2]  B. Berg,et al.  Multicanonical algorithms for first order phase transitions , 1991 .

[3]  K. Dill,et al.  ‘‘Sequence space soup’’ of proteins and copolymers , 1991 .

[4]  Adrian F. M. Smith,et al.  Bayesian Statistics 5. , 1998 .

[5]  Head-Gordon,et al.  Collective aspects of protein folding illustrated by a toy model. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[6]  Hsiao-Ping Hsu,et al.  Structure optimization in an off-lattice protein model. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[8]  Hesselbo,et al.  Monte Carlo simulation and global optimization without parameters. , 1995, Physical review letters.

[9]  K. Dill,et al.  A fast conformational search strategy for finding low energy structures of model proteins , 1996, Protein science : a publication of the Protein Society.

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

[11]  Frank Potthast,et al.  Identification of amino acid sequences with good folding properties in an off-lattice model , 1997 .

[12]  L. Tierney.  Markov Chains for Exploring Posterior Distributions , 1994 .

[13]  Denise Gorse,et al.  Application of a chaperone-based refolding method to two- and three-dimensional off-lattice protein models. , 2002, Biopolymers.

[14]  K Yue,et al.  Forces of tertiary structural organization in globular proteins. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Head-Gordon,et al.  Optimal neural networks for protein-structure prediction. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[16]  Frank Potthast,et al.  Local interactions and protein folding: A three-dimensional off-lattice approach , 1997 .

[17]  STUDIES OF AN OFF-LATTICE MODEL FOR PROTEIN FOLDING: SEQUENCE DEPENDENCE AND IMPROVED SAMPLING AT FINITE TEMPERATURE , 1995, chem-ph/9505003.

[18]  M. Kikuchi,et al.  What is the role of non-native intermediates of beta-lactoglobulin in protein folding? , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Choi,et al.  Optimization by multicanonical annealing and the traveling salesman problem. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[20]  D. Landau,et al.  Determining the density of states for classical statistical models: a random walk algorithm to produce a flat histogram. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

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