Literature DB >> 7602599

Conformational variability of solution nuclear magnetic resonance structures.

A M Bonvin1, A T Brünger.   

Abstract

In structure determination by X-ray crystallography and solution NMR spectroscopy, experimental data are collected as time and ensemble-averages. Thus, in principle, appropriate time and ensemble-averaged models should be used. Refinement of an ensemble of conformers rather than one single structure against the experimental NMR data could, however, result in overfitting the data because of the significantly increased number of parameters. To avoid overfitting, complete cross-validation, which provides an unbiased measure of the fit, has been applied to nuclear Overhauser effect derived distance refinement. Using two synthetic test cases, a correlation was demonstrated between the cross-validated measure to the fit (defined in terms of root-mean-square deviations from the distance restraints and number of violations) and the number of models that best reproduce the conformational variability in solution. A new method, based on a probability map, has been used to generate good representations of the resulting ensembles of structures. The method has also been applied to observed NMR data for two proteins, interleukin 4 and interleukin 8. For interleukin 4, cross-validation indicates that a single-conformer model gives the most accurate representation of the structure, whereas conventional measures of fit between the experimental data and those calculated from the model decrease when increasing the number of conformers, indicating overfitting. For interleukin 8, complete cross-validation predicts a twin-conformer model to be the most faithful representation of the experimental data. Two distinct conformations for the loop formed by residues 16 to 22 emerge from the family of twin-conformer structures. The putative alternate conformation of the loop is not observed in the crystal structure of interleukin 8. However, because of crystal packing contacts in this region this does not necessarily exclude the presence of the alternate conformation in solution. The twin-conformer model is supported by observed chemical exchange line broadening for the amide of His18 obtained by 15N relaxation studies. This region has also been implied to be involved in receptor binding.

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Year:  1995        PMID: 7602599     DOI: 10.1006/jmbi.1995.0360

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  34 in total

1.  Determination of the populations and structures of multiple conformers in an ensemble from NMR data: multiple-copy refinement of nucleic acid structures using floating weights.

Authors:  A Görler; N B Ulyanov; T L James
Journal:  J Biomol NMR       Date:  2000-02       Impact factor: 2.835

2.  Accurate protein structure modeling using sparse NMR data and homologous structure information.

Authors:  James M Thompson; Nikolaos G Sgourakis; Gaohua Liu; Paolo Rossi; Yuefeng Tang; Jeffrey L Mills; Thomas Szyperski; Gaetano T Montelione; David Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-04       Impact factor: 11.205

3.  Methods of NMR structure refinement: molecular dynamics simulations improve the agreement with measured NMR data of a C-terminal peptide of GCN4-p1.

Authors:  Jozica Dolenc; John H Missimer; Michel O Steinmetz; Wilfred F van Gunsteren
Journal:  J Biomol NMR       Date:  2010-06-04       Impact factor: 2.835

4.  FINGAR: A new genetic algorithm-based method for fitting NMR data.

Authors:  D A Pearlman
Journal:  J Biomol NMR       Date:  1996-07       Impact factor: 2.835

5.  Estimating the accuracy of protein structures using residual dipolar couplings.

Authors:  Katya Simon; Jun Xu; Chinpal Kim; Nikolai R Skrynnikov
Journal:  J Biomol NMR       Date:  2005-10       Impact factor: 2.835

6.  Relation between native ensembles and experimental structures of proteins.

Authors:  Robert B Best; Kresten Lindorff-Larsen; Mark A DePristo; Michele Vendruscolo
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-07       Impact factor: 11.205

7.  Solid-State NMR-Restrained Ensemble Dynamics of a Membrane Protein in Explicit Membranes.

Authors:  Xi Cheng; Sunhwan Jo; Yifei Qi; Francesca M Marassi; Wonpil Im
Journal:  Biophys J       Date:  2015-04-21       Impact factor: 4.033

8.  Transmembrane helix orientation and dynamics: insights from ensemble dynamics with solid-state NMR observables.

Authors:  Sunhwan Jo; Wonpil Im
Journal:  Biophys J       Date:  2011-06-22       Impact factor: 4.033

9.  Solid-state NMR ensemble dynamics as a mediator between experiment and simulation.

Authors:  Taehoon Kim; Sunhwan Jo; Wonpil Im
Journal:  Biophys J       Date:  2011-06-22       Impact factor: 4.033

10.  Do NOE distances contain enough information to assess the relative populations of multi-conformer structures?

Authors:  A M Bonvin; A T Brünger
Journal:  J Biomol NMR       Date:  1996-01       Impact factor: 2.835

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