Literature DB >> 21851810

An ensemble dynamics approach to decipher solid-state NMR observables of membrane proteins.

Wonpil Im1, Sunhwan Jo, Taehoon Kim.   

Abstract

Solid-state NMR (SSNMR) is an invaluable tool for determining orientations of membrane proteins and peptides in lipid bilayers. Such orientational descriptions provide essential information about membrane protein functions. However, when a semi-static single conformer model is used to interpret various SSNMR observables, important dynamics information can be missing, and, sometimes, even orientational information can be misinterpreted. In addition, over the last decade, molecular dynamics (MD) simulation and semi-static SSNMR interpretation have shown certain levels of discrepancies in terms of transmembrane helix orientation and dynamics. Dynamic fitting models have recently been proposed to resolve these discrepancies by taking into account transmembrane helix whole body motions using additional parameters. As an alternative approach, we have developed SSNMR ensemble dynamics (SSNMR-ED) using multiple conformer models, which generates an ensemble of structures that satisfies the experimental observables without any fitting parameters. In this review, various computational methods for determining transmembrane helix orientations are discussed, and the distributions of VpuTM (from HIV-1) and WALP23 (a synthetic peptide) orientations from SSNMR-ED simulations are compared with those from MD simulations and semi-static/dynamic fitting models. Such comparisons illustrate that SSNMR-ED can be used as a general means to extract both membrane protein structure and dynamics from the SSNMR measurements. This article is part of a Special Issue entitled: Membrane protein structure and function.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21851810     DOI: 10.1016/j.bbamem.2011.07.048

Source DB:  PubMed          Journal:  Biochim Biophys Acta        ISSN: 0006-3002


  15 in total

1.  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

2.  On the statistical equivalence of restrained-ensemble simulations with the maximum entropy method.

Authors:  Benoît Roux; Jonathan Weare
Journal:  J Chem Phys       Date:  2013-02-28       Impact factor: 3.488

3.  Structural dynamics and conformational equilibria of SERCA regulatory proteins in membranes by solid-state NMR restrained simulations.

Authors:  Alfonso De Simone; Kaustubh R Mote; Gianluigi Veglia
Journal:  Biophys J       Date:  2014-06-17       Impact factor: 4.033

4.  Ensemble MD simulations restrained via crystallographic data: accurate structure leads to accurate dynamics.

Authors:  Yi Xue; Nikolai R Skrynnikov
Journal:  Protein Sci       Date:  2014-04       Impact factor: 6.725

5.  Structural determination of virus protein U from HIV-1 by NMR in membrane environments.

Authors:  Hua Zhang; Eugene C Lin; Bibhuti B Das; Ye Tian; Stanley J Opella
Journal:  Biochim Biophys Acta       Date:  2015-09-08

6.  NMR-based simulation studies of Pf1 coat protein in explicit membranes.

Authors:  Xi Cheng; Sunhwan Jo; Francesca M Marassi; Wonpil Im
Journal:  Biophys J       Date:  2013-08-06       Impact factor: 4.033

7.  Restrained-ensemble molecular dynamics simulations based on distance histograms from double electron-electron resonance spectroscopy.

Authors:  Benoît Roux; Shahidul M Islam
Journal:  J Phys Chem B       Date:  2013-04-11       Impact factor: 2.991

8.  Structural refinement from restrained-ensemble simulations based on EPR/DEER data: application to T4 lysozyme.

Authors:  Shahidul M Islam; Richard A Stein; Hassane S McHaourab; Benoît Roux
Journal:  J Phys Chem B       Date:  2013-04-11       Impact factor: 2.991

9.  Membrane environment modulates the pKa values of transmembrane helices.

Authors:  Afra Panahi; Charles L Brooks
Journal:  J Phys Chem B       Date:  2015-03-22       Impact factor: 2.991

10.  How fast is your camera? Timescales for molecular motion and their role in restraining molecular dynamics.

Authors:  Tod D Romo; Alan Grossfield
Journal:  Biophys J       Date:  2014-06-17       Impact factor: 4.033

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