Sampling of near‐native protein conformations during protein structure refinement using a coarse‐grained model, normal modes, and molecular dynamics simulations

Protein structure refinement from comparative models with the goal of predicting structures at near‐experimental accuracy remains an unsolved problem. Structure refinement might be achieved with an iterative protocol where the most native‐like structure from a set of decoys generated from an initial model in one cycle is used as the starting structure for the next cycle. Conformational sampling based on the coarse‐grained SICHO model, atomic level of detail molecular dynamics simulations, and normal‐mode analysis is compared in the context of such a protocol. All of the sampling methods can achieve significant refinement close to experimental structures, although the distribution of structures and the ability to reach native‐like structures differs greatly. Implications for the practical application of such sampling methods and the requirements for scoring functions in an iterative refinement protocol are analyzed in the context of theoretical predictions for the distribution of protein‐like conformations with a random sampling protocol. Proteins 2008. © 2007 Wiley‐Liss, Inc.

[1]  Ron Goldman,et al.  Improving conformational searches by geometric screening , 2005, Bioinform..

[2]  J. Skolnick,et al.  A distance‐dependent atomic knowledge‐based potential for improved protein structure selection , 2001, Proteins.

[3]  Michael Feig,et al.  Evaluating CASP4 predictions with physical energy functions , 2002, Proteins.

[4]  I. Bahar,et al.  Coarse-grained normal mode analysis in structural biology. , 2005, Current opinion in structural biology.

[5]  Gaetano T. Montelione,et al.  Structural genomics: An approach to the protein folding problem , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Jianpeng Ma,et al.  A New Method for Coarse-Grained Elastic Normal-Mode Analysis. , 2006, Journal of chemical theory and computation.

[7]  M. Karplus,et al.  Simulation of activation free energies in molecular systems , 1996 .

[8]  Song Liu,et al.  A knowledge-based energy function for protein-ligand, protein-protein, and protein-DNA complexes. , 2005, Journal of medicinal chemistry.

[9]  Hongyi Zhou,et al.  What is a desirable statistical energy functions for proteins and how can it be obtained? , 2007, Cell Biochemistry and Biophysics.

[10]  M. Baker,et al.  Refinement of protein structures by iterative comparative modeling and CryoEM density fitting. , 2006, Journal of molecular biology.

[11]  Bonnie Berger,et al.  ChainTweak: Sampling from the Neighbourhood of a Protein Conformation , 2005, Pacific Symposium on Biocomputing.

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

[13]  N Go,et al.  Normal mode refinement: crystallographic refinement of protein dynamic structure. II. Application to human lysozyme. , 1992, Journal of molecular biology.

[14]  F. Tama,et al.  Flexible multi-scale fitting of atomic structures into low-resolution electron density maps with elastic network normal mode analysis. , 2004, Journal of molecular biology.

[15]  Ming Zhang,et al.  A New Method for Fast and Accurate Derivation of Molecular Conformations , 2002, J. Chem. Inf. Comput. Sci..

[16]  Yang Zhang,et al.  The protein structure prediction problem could be solved using the current PDB library. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[17]  J. Skolnick,et al.  What is the probability of a chance prediction of a protein structure with an rmsd of 6 A? , 1998, Folding & design.

[18]  Erik Lindahl,et al.  Refinement of docked protein–ligand and protein–DNA structures using low frequency normal mode amplitude optimization , 2005, Nucleic acids research.

[19]  Yang Zhang,et al.  TASSER: An automated method for the prediction of protein tertiary structures in CASP6 , 2005, Proteins.

[20]  Michael Feig,et al.  MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology. , 2004, Journal of molecular graphics & modelling.

[21]  J. Skolnick,et al.  MONSSTER: a method for folding globular proteins with a small number of distance restraints. , 1997, Journal of molecular biology.

[22]  M. Gerstein,et al.  Structural Genomics: Current Progress , 2003, Science.

[23]  N Go,et al.  Refinement of protein dynamic structure: normal mode refinement. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[24]  K. Takano ON SOLUTION OF , 1983 .

[25]  Hongyi Zhou,et al.  Stability scale and atomic solvation parameters extracted from 1023 mutation experiments , 2002, Proteins.

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

[27]  A. Sali,et al.  Statistical potential for assessment and prediction of protein structures , 2006, Protein science : a publication of the Protein Society.

[28]  N. Grishin,et al.  Practical lessons from protein structure prediction , 2005, Nucleic acids research.

[29]  Finn Drabløs,et al.  Homology-based modelling of targets for rational drug design. , 2004, Mini reviews in medicinal chemistry.

[30]  G. Ciccotti,et al.  Numerical Integration of the Cartesian Equations of Motion of a System with Constraints: Molecular Dynamics of n-Alkanes , 1977 .

[31]  P. Bradley,et al.  Toward High-Resolution de Novo Structure Prediction for Small Proteins , 2005, Science.

[32]  Richard Bonneau,et al.  Functional inferences from blind ab initio protein structure predictions. , 2001, Journal of structural biology.

[33]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[34]  Anna Tramontano,et al.  Assessment of homology‐based predictions in CASP5 , 2003, Proteins.

[35]  Yong Duan,et al.  Comparison between Generalized-Born and Poisson–Boltzmann methods in physics-based scoring functions for protein structure prediction , 2005, Journal of molecular modeling.

[36]  Chris Sander,et al.  Completeness in structural genomics , 2001, Nature Structural Biology.

[37]  S. Nosé A molecular dynamics method for simulations in the canonical ensemble , 1984 .

[38]  K. Ginalski Comparative modeling for protein structure prediction. , 2006, Current opinion in structural biology.

[39]  Z. Xiang,et al.  Advances in homology protein structure modeling. , 2006, Current protein & peptide science.

[40]  M. Karplus,et al.  Effective energy functions for protein structure prediction. , 2000, Current opinion in structural biology.

[41]  Hui Lu,et al.  Application of statistical potentials to protein structure refinement from low resolution ab initio models , 2003, Biopolymers.

[42]  Michael S Lee,et al.  Assessment of Detection and Refinement Strategies for de novo Protein Structures Using Force Field and Statistical Potentials. , 2007, Journal of chemical theory and computation.

[43]  William R. Taylor,et al.  Protein model refinement using structural fragment tessellation , 2006, Comput. Biol. Chem..

[44]  Zukang Feng,et al.  The Protein Data Bank and structural genomics , 2003, Nucleic Acids Res..

[45]  Yong Duan,et al.  Distinguish protein decoys by Using a scoring function based on a new AMBER force field, short molecular dynamics simulations, and the generalized born solvent model , 2004, Proteins.

[46]  J. Skolnick,et al.  Monte carlo simulations of protein folding. I. Lattice model and interaction scheme , 1994, Proteins.

[47]  Michael Feig,et al.  A correlation‐based method for the enhancement of scoring functions on funnel‐shaped energy landscapes , 2006, Proteins.

[48]  G M Crippen,et al.  Size‐independent comparison of protein three‐dimensional structures , 1995, Proteins.

[49]  David E. Kim,et al.  Physically realistic homology models built with ROSETTA can be more accurate than their templates. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[50]  M. Karplus,et al.  Effective energy function for proteins in solution , 1999, Proteins.

[51]  Adam Zemla,et al.  Critical assessment of methods of protein structure prediction (CASP)‐round V , 2005, Proteins.

[52]  N Go,et al.  Normal mode refinement: crystallographic refinement of protein dynamic structure. I. Theory and test by simulated diffraction data. , 1992, Journal of molecular biology.

[53]  Karsten Suhre,et al.  On the potential of normal-mode analysis for solving difficult molecular-replacement problems. , 2004, Acta crystallographica. Section D, Biological crystallography.