How noise in force fields can affect the structural refinement of protein models?

Proteins: Structure, Function and Bioinformatics

Volumn 80, Issue 2, 2012, Pages 335-341

  Gniewek, Pawel ^a,b   Kolinski, Andrzej ^a   Jernigan, Robert L ^b   Kloczkowski, Andrzej ^b,c,d  

^a UNIVERSITY OF WARSAW   (Poland)

^b IOWA STATE UNIVERSITY   (United States)

^c THE RESEARCH INSTITUTE AT NATIONWIDE CHILDREN S HOSPITAL   (United States)

^d THE OHIO STATE UNIVERSITY COLLEGE OF MEDICINE   (United States)

Author keywords

Force field; Knowledge based potentials; Normal modes analysis; Protein structure prediction; Protein structure refinement; White noise

Indexed keywords

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; CONTROLLED STUDY; ENERGY; NOISE; NORMAL DISTRIBUTION; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROCESS DESIGN; PROTEIN CONFORMATION; PROTEIN STRUCTURE; RANDOMIZATION; SAMPLING; CHEMICAL STRUCTURE; CHEMISTRY; STATISTICS;

PROTEIN;

ALGORITHMS; MODELS, MOLECULAR; PROTEIN CONFORMATION; PROTEINS; STOCHASTIC PROCESSES;

EID: 84855713163     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.23240     Document Type: Article

References (22)

1. Moult J, Fidelis K, Zemla A, Hubbard T. Critical assessment of methods of protein structure prediction (CASP)-round V. Proteins 2003; 53: 334-339.
2. Skolnick J, Brylinski M. FINDSITE: a combined evolution/structure-based approach to protein function prediction. Briefings Bioinformatics 2009; 10: 378-391.
3. Brylinski M, Skolnick J. FINDSITE: a threading-based approach to ligand homology modeling. PLoS Comput Biol 2009; 5: e1000405.
4. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protocols 2010; 5: 725-738.
5. Beltrao P, Kiel C, Serrano L. Structures in systems biology. Curr Opin Struct Biol 2007; 17: 378-384.
6. Kolinski A. Protein modeling and structure prediction with a reduced representation. Acta Biochim Polonica 2004; 51: 349-371.
7. Zhang Y. I-TASSER server for protein 3D structure prediction. BMC Bioinformatics 2008; 9: 40.
8. Lee J, Liwo A, Scheraga HA. Energy-based de novo protein folding by conformational space annealing and an off-lattice united-residue force field: application to the 10-55 fragment of staphylococcal protein A and to apo calbindin D9K. Proc Natl Acad Sci USA 1999; 96: 2025-2030.
9. André I, Bradley P, Wang C, Baker D. Prediction of the structure of symmetrical protein assemblies. Proc Natl Acad Sci USA 2007; 104: 17656-17661.
10. Bradley P, Chivian D, Meiler J, Misura KM, Rohl CA, Schief WR, Wedemeyer WJ, Schueler-Furman O, Murphy P, Schonbrun J, Strauss CE, Baker D. Rosetta predictins in CASP5: successes, failures, and prospects for complete automation. Proteins 2003; 53: 457-468.
11. MacCallum JL, Hua L, Schneiders MJ, Pande VS, Jacobson MP, Dill KA. Assessment of the protein-structure refinement category in CASP8. Proteins 2009; 77: 66-80.
12. Fiser A, Do RK, Sali A. Modeling of loops in protein structures. Protein Sci 2000; 9: 1753-1773.
13. Stumpff-Kane AW, Maksimiak K, Lee MS, Feig M. Sampling of near-native protein conformations during protein structure refinment using a coarse-grained model, normal modes, nad molecular dynamics simulations. Proteins 2008; 70: 1345-1356.
14. Kolinski A, Skolnick J. Assembly of protein structure from sparse experimental data: an efficient Monte Carlo model. Proteins 1998; 32: 475-494.
15. Kabsch W. A solution for the best rotation to relate two sets of vectors. Acta Cryst 1976; A32: 922-923.
16. Reva BA, Finkelstein AV, Skolnick J. What is the probability of a chance prediction of a protein structure with an rmsd of 6 A? Folding Des 1997; 3: 141-147.
17. A.V. Finkelstein. 3D protein folds: homologs against errors-a simple estimate based on the random energy model. Phys Rev Lett 1998; 80: 4823-4825.
18. Bryngelson JD, Wolynes PG. Spin glass and statistical mechanics of protein folding. Proc Natl Acad Sci USA 1987; 84: 7524-7528.
19. Frauenfelder H, Sligar S, Wolynes PG. The energy landscapes and motions of proteins. Science 1991; 254: 1598-1603.
20. Kopp J, Bordoli L, Battey JN, Kiefer F, Schwede T. Assessment of CASP7 predictions for template-based modeling targets. Proteins 2007; 69: 38-56.
21. Rost B. Twilight zone of protein sequence alignments. Protein Eng 1999; 12: 85-94.
22. Stumpff-Kane AW, Feig M. A correlation-based method for the enhancement of scoring functions on funnel-shaped energy landscape. Proteins 2006; 63: 155-164.