Advertisement

Journal of Biomolecular NMR

, 45:413 | Cite as

4D prediction of protein 1H chemical shifts

  • Juuso Lehtivarjo
  • Tommi Hassinen
  • Samuli-Petrus Korhonen
  • Mikael Peräkylä
  • Reino Laatikainen
Article

Abstract

A 4D approach for protein 1H chemical shift prediction was explored. The 4th dimension is the molecular flexibility, mapped using molecular dynamics simulations. The chemical shifts were predicted with a principal component model based on atom coordinates from a database of 40 protein structures. When compared to the corresponding non-dynamic (3D) model, the 4th dimension improved prediction by 6–7%. The prediction method achieved RMS errors of 0.29 and 0.50 ppm for Hα and HN shifts, respectively. However, for individual proteins the RMS errors were 0.17–0.34 and 0.34–0.65 ppm for the Hα and HN shifts, respectively. X-ray structures gave better predictions than the corresponding NMR structures, indicating that chemical shifts contain invaluable information about local structures. The 1H chemical shift prediction tool 4DSPOT is available from http://www.uku.fi/kemia/4dspot.

Keywords

Protein Proton Chemical shift Prediction Molecular dynamics 

Supplementary material

10858_2009_9384_MOESM1_ESM.pdf (132 kb)
Supplementary material 1 (PDF 131 kb)

References

  1. Allen LC (1989) Electronegativity is the average one-electron energy of the valence-shell electrons in ground-state free atoms. J Am Chem Soc 111:9003–9014CrossRefGoogle Scholar
  2. Andrec M, Snyder DA, Zhou Z, Young J, Montelione GT, Levy RM (2007) A large data set comparison of protein structures determined by crystallography and NMR: statistical test for structural differences and the effect of crystal packing. Proteins 69:449–465CrossRefGoogle Scholar
  3. Avbelj F, Kocjan D, Baldwin RL (2004) Protein chemical shifts arising from alpha-helices and beta-sheets depend on solvent exposure. Proc Natl Acad Sci U S A 101:17394–17397CrossRefADSGoogle Scholar
  4. Berjanskii MV, Wishart DS (2008) Application of the random coil index to studying protein flexibility. J Biomol NMR 40:31–48CrossRefGoogle Scholar
  5. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28:235–242CrossRefGoogle Scholar
  6. Case DA, Darden TA, Cheatham TE, Simmerling CLI, Wang J, Duke RE, Luo R, Merz KM, Pearlman DA, Crowley M, Walker RC, Zhang W, Wang B, Hayik S, Roitberg A, Seabra G, Wong KF, Paesani F, Wu X, Brozell S, Tsui V, Gohlke H, Yang L, Tan C, Monga JN, Hornak V, Cui G, Beroza P, Mathews DH, Schafmeister C, Ross WS, Kollman PA (2006) AMBER 9, University of California, San FranciscoGoogle Scholar
  7. Cavalli A, Salvatella X, Dobson CM, Vendruscolo M (2007) Protein structure determination from NMR chemical shifts. Proc Natl Acad Sci U S A 104:9615–9620CrossRefADSGoogle Scholar
  8. Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz KM, Ferguson DM, Spellmeyer DC, Fox T, Caldwell JW, Kollman PA (1995) A 2nd generation force-field for the simulation of proteins, nucleic-acids, and organic-molecules. J Am Chem Soc 117:5179–5197CrossRefGoogle Scholar
  9. de Dios AC, Pearson JG, Oldfield E (1993) Secondary and tertiary structural effects on protein NMR chemical shifts: an ab initio approach. Science 260:1491–1496CrossRefADSGoogle Scholar
  10. Ginzinger SW, Coles M (2009) SimShiftDB; local conformational restraints derived from chemical shift similarity searches on a large synthetic database. J Biomol NMR 43:179–185CrossRefGoogle Scholar
  11. Hooft RWW, Vriend G, Sander C, Abola EE (1996) Errors in protein structures. Nature 381:272CrossRefADSGoogle Scholar
  12. Hornak V, Abel R, Okur A, Strockbine B, Roitberg A, Simmerling C (2006) Comparison of multiple amber force fields and development of improved protein backbone parameters. Proteins 65:712–725CrossRefGoogle Scholar
  13. Joosten RP, Salzemann J, Bloch V, Stockinger H, Berglund A, Blanchet C, Bongcam-Rudloff E, Combet C, Da Costa AL, Deleage G, Diarena M, Fabbretti R, Fettahi G, Flegel V, Gisel A, Kasam V, Kervinen T, Korpelainen E, Mattila K, Pagni M, Reichstadt M, Breton V, Tickle IJ, Vriend G (2009) PDB_REDO: automated re-refinement of X-ray structure models in the PDB. J Appl Crystallogr 42:376–384CrossRefGoogle Scholar
  14. Klepeis JL, Lindorff-Larsen K, Dror RO, Shaw DE (2009) Long-timescale molecular dynamics simulations of protein structure and function. Curr Opin Struct Biol 19:120–127CrossRefGoogle Scholar
  15. Kohlhoff KJ, Robustelli P, Cavalli A, Salvatella X, Vendruscolo M (2009) Fast and accurate predictions of protein NMR chemical shifts from interatomic distances. J Am Chem Soc 131:13894–13895CrossRefGoogle Scholar
  16. Kuszewski J, Gronenborn AM, Clore GM (1995) The impact of direct refinement against proton chemical shifts on protein structure determination by NMR. J Magn Reson B 107:293–297CrossRefGoogle Scholar
  17. Laskowski RA, Rullmannn JA, MacArthur MW, Kaptein R, Thornton JM (1996) AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. J Biomol NMR 8:477–486CrossRefGoogle Scholar
  18. Meiler J (2003) PROSHIFT: protein chemical shift prediction using artificial neural networks. J Biomol NMR 26:25–37CrossRefGoogle Scholar
  19. Montalvao RW, Cavalli A, Salvatella X, Blundell TL, Vendruscolo M (2008) Structure determination of protein–protein complexes using NMR chemical shifts: case of an endonuclease colicin–immunity protein complex. J Am Chem Soc 130:15990–15996CrossRefGoogle Scholar
  20. Moon S, Case DA (2007) A new model for chemical shifts of amide hydrogens in proteins. J Biomol NMR 38:139–150CrossRefGoogle Scholar
  21. Neal S, Nip AM, Zhang H, Wishart DS (2003) Rapid and accurate calculation of protein 1H, 13C and 15N chemical shifts. J Biomol NMR 26:215–240CrossRefGoogle Scholar
  22. Ösapay K, Case DA (1991) A new analysis of proton chemical shifts in proteins. J Am Chem Soc 113:9436–9444CrossRefGoogle Scholar
  23. Parker LL, Houk AR, Jensen JH (2006) Cooperative hydrogen bonding effects are key determinants of backbone amide proton chemical shifts in proteins. J Am Chem Soc 128:9863–9872CrossRefGoogle Scholar
  24. Saarela JTA, Tuppurainen K, Perakyla M, Santa H, Laatikainen R (2002) Correlative motions and memory effects in molecular dynamics simulations of molecules: principal components and rescaled range analysis suggest that the motions of native BPTI are more correlated than those of its mutants. Biophys Chem 95:49–57CrossRefGoogle Scholar
  25. Schwarzinger S, Kroon GJA, Foss TR, Chung J, Wright PE, Dyson HJ (2001) Sequence-dependent correction of random coil NMR chemical shifts. J Am Chem Soc 123:2970–2978CrossRefGoogle Scholar
  26. Schwieters CD, Kuszewski JJ, Clore GM (2006) Using xplor-NIH for NMR molecular structure determination. Prog Nucl Magn Reson Spectrosc 48:47–62CrossRefGoogle Scholar
  27. Shen Y, Bax A (2007) Protein backbone chemical shifts predicted from searching a database for torsion angle and sequence homology. J Biomol NMR 38:289–302CrossRefGoogle Scholar
  28. Shen Y, Lange O, Delaglio F, Rossi P, Aramini JM, Liu G, Eletsky A, Wu Y, Singarapu KK, Lemak A, Ignatchenko A, Arrowsmith CH, Szyperski T, Montelione GT, Baker D, Bax A (2008) Consistent blind protein structure generation from NMR chemical shift data. Proc Natl Acad Sci U S A 105:4685–4690CrossRefADSGoogle Scholar
  29. Shen Y, Vernon R, Baker D, Bax A (2009) De novo protein structure generation from incomplete chemical shift assignments. J Biomol NMR 43:63–78CrossRefGoogle Scholar
  30. Simons KT, Kooperberg C, Huang E, Baker D (1997) Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and bayesian scoring functions. J Mol Biol 268:209–225CrossRefGoogle Scholar
  31. Smock RG, Gierasch LM (2009) Sending signals dynamically. Science 324:198–203CrossRefADSGoogle Scholar
  32. Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, Livny M, Mading S, Maziuk D, Miller Z, Nakatani E, Schulte CF, Tolmie DE, Kent Wenger R, Yao H, Markley JL (2008) BioMagResBank. Nucleic Acids Res 36:D402–D408CrossRefGoogle Scholar
  33. Vranken WF, Rieping W (2009) Relationship between chemical shift value and accessible surface area for all amino acid atoms. BMC Struct Biol 9:20CrossRefGoogle Scholar
  34. Wagner G, Pardi A, Wuthrich K (1983) Hydrogen bond length and proton NMR chemical shifts in proteins. J Am Chem Soc 105:5948–5949CrossRefGoogle Scholar
  35. Wang Y (2004) Secondary structural effects on protein NMR chemical shifts. J Biomol NMR 30:233–244CrossRefGoogle Scholar
  36. Wang Y, Jardetzky O (2002) Investigation of the neighboring residue effects on protein chemical shifts. J Am Chem Soc 124:14075–14084CrossRefGoogle Scholar
  37. Wang L, Markley JL (2009) Empirical correlation between protein backbone 15N and 13C secondary chemical shifts and its application to nitrogen chemical shift re-referencing. J Biomol NMR 44:95–99CrossRefGoogle Scholar
  38. Wang JM, Cieplak P, Kollman PA (2000) How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? J Comput Chem 21:1049–1074CrossRefGoogle Scholar
  39. Wishart DS, Case DA (2001) Use of chemical shifts in macromolecular structure determination. Methods Enzymol 338:3–34Google Scholar
  40. Wishart DS, Bigam CG, Holm A, Hodges RS, Sykes BD (1995) 1H, 13C and 15N random coil NMR chemical shifts of the common amino acids. I. investigations of nearest-neighbor effects. J Biomol NMR 5:67–81CrossRefGoogle Scholar
  41. Wishart DS, Arndt D, Berjanskii M, Tang P, Zhou J, Lin G (2008) CS23D: a web server for rapid protein structure generation using NMR chemical shifts and sequence data. Nucleic Acids Res 36:W496–W502CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Juuso Lehtivarjo
    • 1
  • Tommi Hassinen
    • 1
  • Samuli-Petrus Korhonen
    • 3
  • Mikael Peräkylä
    • 2
  • Reino Laatikainen
    • 1
  1. 1.Department of Biosciences, Laboratory of ChemistryUniversity of KuopioKuopioFinland
  2. 2.Department of Biosciences, Laboratory of BiochemistryUniversity of KuopioKuopioFinland
  3. 3.Perch Solutions Ltd.KuopioFinland

Personalised recommendations