Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction

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Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction


Abstract While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein 1H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6â??17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for 1Hα, 1HN, 13Cα, 13Cβ, 13CO and backbone 15N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at http://www.uef.fi/4dspot.

• Content Type Journal Article
• Category Article
• Pages 1-11
• DOI 10.1007/s10858-012-9609-6
• Authors
  • Juuso Lehtivarjo, School of Pharmacy, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
  • Kari Tuppurainen, School of Pharmacy, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
  • Tommi Hassinen, School of Pharmacy, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
  • Reino Laatikainen, School of Pharmacy, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
  • Mikael Peräkylä, Institute of Biomedicine, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland

• • Journal Journal of Biomolecular NMR
  • Online ISSN 1573-5001
  • Print ISSN 0925-2738

Source: Journal of Biomolecular NMR