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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.
MedLine Citation:
PMID:  22314705     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
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 (1)H 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 6-17% 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 (1)Hα, (1)HN, (13)Cα, (13)Cβ, (13)CO and backbone (15)N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at http://www.uef.fi/4dspot .
Authors:
Juuso Lehtivarjo; Kari Tuppurainen; Tommi Hassinen; Reino Laatikainen; Mikael Peräkylä
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-2-8
Journal Detail:
Title:  Journal of biomolecular NMR     Volume:  -     ISSN:  1573-5001     ISO Abbreviation:  -     Publication Date:  2012 Feb 
Date Detail:
Created Date:  2012-2-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9110829     Medline TA:  J Biomol NMR     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
School of Pharmacy, University of Eastern Finland, P.O. Box 1627, 70211, Kuopio, Finland, juuso.lehtivarjo@uef.fi.
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