Literature DB >> 19882615

A method to explore protein side chain conformational variability using experimental data.

Jane R Allison1, Wilfred F van Gunsteren.   

Abstract

Experimentally measured values of molecular properties or observables of biomolecules such as proteins are generally averages over time and space, which do not contain sufficient information to determine the underlying conformational distribution of the molecules in solution. The relationship between experimentally measured NMR (3)J-coupling values and the corresponding dihedral angle values is a particularly complicated case due to its nonlinear, multiple-valued nature. Molecular dynamics (MD) simulations at constant temperature can generate Boltzmann ensembles of molecular structures that are free from a priori assumptions about the nature of the underlying conformational distribution. They suffer, however, from limited sampling with respect to time and conformational space. Moreover, the quality of the obtained structures is dependent on the choice of force field and solvation model. A recently proposed method that uses time-averaging with local-elevation (LE) biasing of the conformational search provides an elegant means of overcoming these three problems. Using a set of side chain (3)J-coupling values for the FK506 binding protein (FKBP), we first investigate the uncertainty in the angle values predicted theoretically. We then propose a simple MD-based technique to detect inconsistencies within an experimental data set and identify degrees of freedom for which conformational averaging takes place or for which force field parameters may be deficient. Finally, we show that LE MD is the best method for producing ensembles of structures that, on average, fit the experimental data.

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Year:  2009        PMID: 19882615     DOI: 10.1002/cphc.200900400

Source DB:  PubMed          Journal:  Chemphyschem        ISSN: 1439-4235            Impact factor:   3.102


  7 in total

1.  On the calculation of ³Jαβ-coupling constants for side chains in proteins.

Authors:  Denise Steiner; Jane R Allison; Andreas P Eichenberger; Wilfred F van Gunsteren
Journal:  J Biomol NMR       Date:  2012-06-20       Impact factor: 2.835

2.  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

3.  Exploring the trigger sequence of the GCN4 coiled-coil: biased molecular dynamics resolves apparent inconsistencies in NMR measurements.

Authors:  John H Missimer; Jožica Dolenc; Michel O Steinmetz; Wilfred F van Gunsteren
Journal:  Protein Sci       Date:  2010-12       Impact factor: 6.725

Review 4.  Assessing and refining molecular dynamics simulations of proteins with nuclear magnetic resonance data.

Authors:  Jane R Allison
Journal:  Biophys Rev       Date:  2012-09-01

5.  Solvating atomic level fine-grained proteins in supra-molecular level coarse-grained water for molecular dynamics simulations.

Authors:  Sereina Riniker; Andreas P Eichenberger; Wilfred F van Gunsteren
Journal:  Eur Biophys J       Date:  2012-07-14       Impact factor: 1.733

6.  On the use of time-averaging restraints when deriving biomolecular structure from ³J -coupling values obtained from NMR experiments.

Authors:  Lorna J Smith; Wilfred F van Gunsteren; Niels Hansen
Journal:  J Biomol NMR       Date:  2016-09-15       Impact factor: 2.835

Review 7.  Understanding biomolecular motion, recognition, and allostery by use of conformational ensembles.

Authors:  R Bryn Fenwick; Santi Esteban-Martín; Xavier Salvatella
Journal:  Eur Biophys J       Date:  2011-11-17       Impact factor: 1.733

  7 in total

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