Protein Structure Prediction with Stochastic Optimization Methods: Folding and Misfolding the Villin Headpiece

We recently developed an all-atom free energy forcefield (PFF01) for protein structure prediction with stochastic optimization methods. Using this forcefield we were able to reproducibly fold the 20 amino-acid trp-cage protein and the 40-amino acid three-helix HIV accessory protein. We could also demonstrate that PFF01 stabilized the native folds of various other proteins ranging from 40-60 amino acids at the all atom level. Here we report on a folding study on the widely investigated autonomously folding 36-amino acid villin headpiece. Using more than 76000 low-energy decoys to characterize its free-energy landscape, we find several competing low-lying three-helix structures. The existence of these metastable conformations, which are not nearly as prevalent in other proteins, may explain the extreme difficulty in folding this protein in-silico.

[1]  Ulrich H E Hansmann,et al.  Global optimization by energy landscape paving. , 2002, Physical review letters.

[2]  T. Herges,et al.  An all-atom force field for tertiary structure prediction of helical proteins. , 2004, Biophysical journal.

[3]  J. Moult,et al.  Determination of the conformation of folding initiation sites in proteins by computer simulation , 1995, Proteins.

[4]  Harold A. Scheraga,et al.  On the Use of Classical Statistical Mechanics in the Treatment of Polymer Chain Conformation , 1976 .

[5]  Adam Liwo,et al.  Recent improvements in prediction of protein structure by global optimization of a potential energy function , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[6]  A. Roitberg,et al.  All-atom structure prediction and folding simulations of a stable protein. , 2002, Journal of the American Chemical Society.

[7]  M. Karplus,et al.  Folding of a model three-helix bundle protein: a thermodynamic and kinetic analysis. , 1999, Journal of molecular biology.

[8]  J. Jung,et al.  Protein structure prediction. , 2001, Current opinion in chemical biology.

[9]  Eaton E. Lattman CASP4 , 2001 .

[10]  C Kooperberg,et al.  Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. , 1997, Journal of molecular biology.

[11]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[12]  A. Liwo,et al.  A method for optimizing potential-energy functions by a hierarchical design of the potential-energy landscape: Application to the UNRES force field , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Herges Th.,et al.  Low Energy Conformations of a Three-Helix Peptide in a All-Atom Biomolecular Forcefield , 2003 .

[14]  A. Schug,et al.  Reproducible protein folding with the stochastic tunneling method. , 2003, Physical review letters.

[15]  I D Kuntz,et al.  Peter Andrew Kollman , 2001, Proteins.

[16]  A. D. McLachlan,et al.  Solvation energy in protein folding and binding , 1986, Nature.

[17]  A. Sali,et al.  Protein Structure Prediction and Structural Genomics , 2001, Science.

[18]  M. Springer,et al.  NMR structure of bacterial ribosomal protein l20: implications for ribosome assembly and translational control. , 2002, Journal of molecular biology.

[19]  C L Brooks,et al.  Taking a Walk on a Landscape , 2001, Science.

[20]  Ulrich H E Hansmann,et al.  Parallel tempering simulations of HP‐36 , 2003, Proteins.

[21]  J Moult,et al.  Role of electrostatic screening in determining protein main chain conformational preferences. , 1995, Biochemistry.

[22]  T. Hubbard,et al.  Critical assessment of methods of protein structure prediction (CASP)‐round V , 2003, Proteins.

[23]  Wolfgang Wenzel,et al.  Stochastic optimization methods for structure prediction of biomolecular nanoscale systems , 2003 .

[24]  J. Onuchic,et al.  Theory of protein folding: the energy landscape perspective. , 1997, Annual review of physical chemistry.

[25]  S. Bryant,et al.  Critical assessment of methods of protein structure prediction (CASP): Round II , 1997, Proteins.

[26]  J. Doye,et al.  Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms , 1997, cond-mat/9803344.

[27]  Valerie Daggett,et al.  The complete folding pathway of a protein from nanoseconds to microseconds , 2003, Nature.

[28]  H. Scheraga,et al.  Monte Carlo-minimization approach to the multiple-minima problem in protein folding. , 1987, Proceedings of the National Academy of Sciences of the United States of America.

[29]  I. Shimada,et al.  Three-dimensional solution structure of the B domain of staphylococcal protein A: comparisons of the solution and crystal structures. , 1992, Biochemistry.

[30]  H. Scheraga,et al.  Packing helices in proteins by global optimization of a potential energy function , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[31]  M. Karplus,et al.  The topology of multidimensional potential energy surfaces: Theory and application to peptide structure and kinetics , 1997 .

[32]  B Honig,et al.  Extracting hydrophobic free energies from experimental data: relationship to protein folding and theoretical models. , 1991, Biochemistry.

[33]  X. Daura,et al.  Reversible peptide folding in solution by molecular dynamics simulation. , 1998, Journal of molecular biology.

[34]  C L Brooks,et al.  Exploring the origins of topological frustration: design of a minimally frustrated model of fragment B of protein A. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[35]  W F van Gunsteren,et al.  Protein structure prediction force fields: Parametrization with quasi‐newtonian dynamics , 1997, Proteins.

[36]  R. Abagyan,et al.  Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins. , 1994, Journal of molecular biology.

[37]  Richard Bonneau,et al.  Rosetta in CASP4: Progress in ab initio protein structure prediction , 2001, Proteins.

[38]  G L Gilliland,et al.  Structural studies of the engrailed homeodomain , 1994, Protein science : a publication of the Protein Society.

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

[40]  V. Pande,et al.  Absolute comparison of simulated and experimental protein-folding dynamics , 2002, Nature.

[41]  P. Kollman,et al.  Pathways to a protein folding intermediate observed in a 1-microsecond simulation in aqueous solution. , 1998, Science.

[42]  Patrick Aloy,et al.  Predictions without templates: New folds, secondary structure, and contacts in CASP5 , 2003, Proteins.

[43]  Harold A Scheraga,et al.  Atomically detailed folding simulation of the B domain of staphylococcal protein A from random structures , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[44]  H. Scheraga,et al.  Energy parameters in polypeptides. 10. Improved geometrical parameters and nonbonded interactions for use in the ECEPP/3 algorithm, with application to proline-containing peptides , 1994 .

[45]  W. Wenzel,et al.  Stochastic Optimisation Methods for Biomolecular Structure Prediction , 2002 .

[46]  D. Baker,et al.  Protein structure prediction in 2002. , 2002, Current opinion in structural biology.

[47]  C. Anfinsen Principles that govern the folding of protein chains. , 1973, Science.