Journal of Biomolecular NMR

, 51:265 | Cite as

Biomolecular structure refinement using the GROMOS simulation software

  • Nathan Schmid
  • Jane R. Allison
  • Jožica Dolenc
  • Andreas P. Eichenberger
  • Anna-Pitschna E. Kunz
  • Wilfred F. van Gunsteren
Article

Abstract

For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, 3J-couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.

Keywords

GROMOS Structure refinement Crystallography NMR 

References

  1. Artymiuk PJ, Blake CCF, Rice DW, Wilson KS (1982) The structures of the monoclinic and orthorhombic forms of hen egg-white lysozyme at 6 angstroms resolution. Acta Crystallogr Sect B 38:778–783Google Scholar
  2. Blackledge M (2005) Recent progress in the study of biomolecular structure and dynamics in solution from residual dipolar couplings. Prog NMR Spec 46:23–61CrossRefGoogle Scholar
  3. Brünger AT (1992) The free R value: a novel statistical quantity for assessing the accuracy of crystal structures. Nature 355:472–474ADSCrossRefGoogle Scholar
  4. Černy V (1985) A thermodynamical approach to the travelling salesman problem: an efficient simulation algorithm. J Optim Theory Applic 45:41–51MATHCrossRefGoogle Scholar
  5. Chapman MS (1995) Restrained real-space macromolecular atomic refinement using a new resolution-dependent electron-density function. Acta Cryst A51:69–80Google Scholar
  6. Christen M, van Gunsteren WF (2007) On searching in, sampling of, and dynamically moving through conformational space of biomolecular systems: a review. J Comput Chem 29:157–166CrossRefGoogle Scholar
  7. Christen M, Hünenberger PH, Bakowies D, Baron R, Bürgi R, Geerke DP, Heinz TN, Kastenholz MA, Kräutler V, Oostenbrink C, Peter C, Trzesniak D, van Gunsteren WF (2005) The GROMOS software for biomolecular simulation: GROMOS05. J Comput Chem 26:1719–1751CrossRefGoogle Scholar
  8. Christen M, Keller B, van Gunsteren WF (2007) Biomolecular structure refinement based on adaptive restraints using local-elevation simulation. J Biomol NMR 39:265–273CrossRefGoogle Scholar
  9. Cowtan K (2003) The clipper C++ libraries for X-ray crystallography. IUCr Comput Comm Newslett 2:4–9Google Scholar
  10. de Casteljau P (1959) Courbes à poles. INPIGoogle Scholar
  11. de Vlieg J, Boelens R, Scheek RM, Kaptein R, van Gunsteren WF (1986) Restrained molecular dynamics procedure for protein tertiary structure determination from NMR data: a lac repressor headpiece structure based on information on J-coupling and from presence and absence of NOE’s. Isr J Chem 27:181–188Google Scholar
  12. Debye P (1913) Interference of X-rays and heat movement. Annalen der Physik 43(1):49–95ADSCrossRefGoogle Scholar
  13. Dolenc J, Missimer JH, Steinmetz MO, van Gunsteren WF (2010) Methods of NMR structure refinement: molecular dynamics simulations improve the agreement with measured NMR data of a C-terminal peptide of GCN4-p1. J Biomol NMR 47:221–235CrossRefGoogle Scholar
  14. Frühwirth T, Fritz G, Freiberger N, Glatter O (2004) Structure and order in lamellar phases determined by small-angle scattering. J Appl Cryst 37:703–710CrossRefGoogle Scholar
  15. Galassi M, Davies J, Theiler J, Gough B, Jungman G, Booth M, Rossi F (2003) Gnu scientific library: reference manual. Network Theory Ltd, UKGoogle Scholar
  16. Gronenborn AM, Filpula DR, Essig NZ, Achari A, Whitlow M, Wingfield PT, Clore GM (1991) A novel, highly stable fold of the immunoglobulin binding domain of streptococcal protein G. 253(5020):657–661Google Scholar
  17. Gros P, van Gunsteren WF, Hol WGJ (1990) Inclusion of thermal motion in crystallographic structures by restrained molecular dynamics. Science 249:1149–1152ADSCrossRefGoogle Scholar
  18. Higman VA, Boyd J, Smith LJ, Redfield C (2010) Residual dipolar couplings: are multiple independent alignments always possible?. J Biomol NMR 49:53–60CrossRefGoogle Scholar
  19. Hockney RW, Eastwood JW (1981) Computer simulation using particles. McGraw-Hill, New YorkGoogle Scholar
  20. Horta B, Peric-Hassler L, Hünenberger PH (2010) Interaction of the disaccharides trehalose and gentiobiose with lipid bilayers: a comparative molecular dynamics study. J Mol Graph Model 29:331–346CrossRefGoogle Scholar
  21. Huber T, Torda AE, van Gunsteren WF (1994) Local elevation: a method for improving the searching properties of molecular dynamics simulation. J Comput Aided Mol Design 8:695–708ADSCrossRefGoogle Scholar
  22. Hukushima K, Nemoto K (1996) Exchange Monte Carlo method and application to spin glass simulations. J Phys Soc Jpn 65:1604–1608ADSCrossRefGoogle Scholar
  23. Irbäck A, Potthast F (1995) Studies of an off-lattice model for protein folding: sequence dependence and improved sampling at finite temperature. J Chem Phys 103:10298–10305ADSCrossRefGoogle Scholar
  24. Jones TA, Zuo JY, Cowan SW, Kjeldgaard M (1991) Improved methods for building protein models in electron density maps and the location of errors in these models. Acta Cryst 47A:110–119Google Scholar
  25. Karplus M (1959) Interpretation of the electron-spin resonance spectrum of the methyl radical. J Chem Phys 30:11–15ADSCrossRefGoogle Scholar
  26. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680MathSciNetADSCrossRefMATHGoogle Scholar
  27. Kunz A-PE, Eichenberger AP, van Gunsteren WF (2011) A simple, efficient, polarisable molecular model for liquid carbon tetrachloride. Mol Phys 109:365–372ADSCrossRefGoogle Scholar
  28. Lide DR (2007) CRC handbook of chemistry and physics, 88th ed. CRC, Boca RatonGoogle Scholar
  29. Misawa M (1989) Temperature-dependence of structure of liquid carbon-tetrachloride measured by pulsed neutron scattering. J Chem Phys 91:5648–5654ADSCrossRefGoogle Scholar
  30. Nanzer AP, Torda AE, Bisang C, Weber C, Robinson JA, van Gunsteren WF (1997) Dynamical studies of peptide motifs in the plasmodium falciparum circumsporozoite surface protein by restrained and unrestrained MD simulations. J Mol Biol 267:1012–1025CrossRefGoogle Scholar
  31. Okabe T, Kawata M, Okamoto Y, Mikami M (2001) Replica-exchange Monte Carlo method for the isobaric-isothermal ensemble. Chem Phys Lett 335:435–439ADSCrossRefGoogle Scholar
  32. Oostenbrink C, Villa A, Mark AE, van Gunsteren WF (2004) A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J Comp Chem. 25:1656CrossRefGoogle Scholar
  33. Oostenbrink C, Soares TA, van der Vegt NFA, van Gunsteren WF (2005) Validation of the 53A6 GROMOS force field. Eur Biophys J 34:273–284CrossRefGoogle Scholar
  34. Pardi A, Billeter M, Wüthrich K (1984) Calibration of the angular dependence of the amide proton-C alpha proton coupling constants, 3 J H N − Hα, in a globular protein. Use of 3 J H N − Hα for identification of helical secondary structure. J Mol Biol 741–751Google Scholar
  35. Peter C, Daura X, van Gunsteren WF (2001) Calculation of NMR-relaxation parameters for flexible molecules from molecular dynamics simulations. J Biomol NMR 20:297–310CrossRefGoogle Scholar
  36. Pusztai L, McGreevy RL (1997) The structure of liquid CCl4. Mol Phys 90:533–539ADSCrossRefGoogle Scholar
  37. Ryckaert J-P, Ciccotti G, Berendsen HJC (1977) Numerical integration of the cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes. J Comput Phys 23:327–341ADSCrossRefGoogle Scholar
  38. Schmid N, Bolliger C, Smith LJ, van Gunsteren WF (2008) Disulfide bond shuffling in bovine α-lactalbumin: MD simulation confirms experiment. Biochemistry 47(46):12104–12107CrossRefGoogle Scholar
  39. Schmid N, Eichenberger AP, Choutko A, Riniker S, Winger M, Mark AE, van Gunsteren WF (2011) Definition and testing of the GROMOS force-field versions 54A7 and 54B7. Eur Biophys J 40(7):843–856. doi:10.1007/s00249-011-0700-9 Google Scholar
  40. Schuler LD, Daura X, van Gunsteren WF (2001) An improved GROMOS96 force field for aliphatic hydrocarbons in the condensed phase. J Comput Chem 22:1205–1218CrossRefGoogle Scholar
  41. Steinmetz MO, Jelesarov I, Matousek WM, Honnappa S, Jahnke W, Missimer JH, Frank S, Alexandrescu AT, Kammerer RA (2007) Molecular basis of coiled-coil formation. PNAS 104:7062–7067ADSCrossRefGoogle Scholar
  42. Sugita Y, Kitao A, Okamoto Y (2000) Multidimensional replica-exchange method for free-energy calculations. J Chem Phys 113:6042–6052ADSCrossRefGoogle Scholar
  43. Torda AE, Scheek RM, van Gunsteren WF (1989) Time-dependent distance restraints in molecular dynamics simulations. Chem Phys Lett 157:289–294ADSCrossRefGoogle Scholar
  44. Torda AE, Brunne RM, Huber T, Kessler H, van Gunsteren WF (1993) Structure refinement using time-averaged J-coupling constant restraints. J Biomol NMR 3:55–66CrossRefGoogle Scholar
  45. Tropp J (1980) Dipolar relaxation and nuclear Overhauser effects in nonrigid molecules: the effect of fluctuating internuclear distances. J Chem Phys 72:6035–6043ADSCrossRefGoogle Scholar
  46. van Gunsteren WF, Billeter SR, Eising AA, Hünenberger PH, Krüger P, Mark AE, Scott WRP, Tironi IG (1996) Biomolecular simulation: the GROMOS96 manual and user guide. Hochschulverlag AG, ETH ZurichGoogle Scholar
  47. van Hove L (1954) Correlations in space and time and Born approximation scattering in systems of interacting particles. Phys Rev 95:249ADSMATHCrossRefGoogle Scholar
  48. Vijay-Kumar S, Bugg CE, Cook WJ (1987) Structure of ubiquitin refined at 1.8 Å resolution. J Mol Biol 194:531–544CrossRefGoogle Scholar
  49. Waasmaier D, Kirfel A (1995) New analytical scattering-factor functions for free atoms and ions. Acta Cryst A51:416–431Google Scholar
  50. Windsor CG (1973) Chemical applications of thermal neutron scattering. Oxford University Press, OxfordGoogle Scholar
  51. Wlodawer A, Nachman J, Gilliland GL, Gallagher W, Woodward C (1987) Structure of form III crystals of bovine pancreatic trypsin inhibitor. J Mol Biol 198:469–480CrossRefGoogle Scholar
  52. Wüthrich K, Billeter M, Braun W (1983) Pseudo-structures for the 20 common amino acids for use in studies of protein conformations by measurements of intramolecular proton-proton distance constraints with nuclear magnetic resonance. J Mol Biol 169:949–961CrossRefGoogle Scholar
  53. Zuiderweg ERP, Scheek RM, Boelens R, van Gunsteren WF, Kaptein R (1985) Determination of protein structures from nuclear magnetic resonance data using a restrained molecular dynamics approach: the lac repressor DNA binding domain. Biochimie 67:707–715CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Nathan Schmid
    • 1
  • Jane R. Allison
    • 1
  • Jožica Dolenc
    • 1
    • 2
  • Andreas P. Eichenberger
    • 1
  • Anna-Pitschna E. Kunz
    • 1
  • Wilfred F. van Gunsteren
    • 1
  1. 1.Laboratory of Physical ChemistrySwiss Federal Institute of Technology ETHZürichSwitzerland
  2. 2.Faculty of Chemistry and Chemical TechnologyUniversity of LjubljanaLjubljanaSlovenia

Personalised recommendations