Literature DB >> 8411178

How consistent are molecular dynamics simulations? Comparing structure and dynamics in reduced and oxidized Escherichia coli thioredoxin.

A Elofsson1, L Nilsson.   

Abstract

In this study we have examined several parameters that can be used for checking the consistency and accuracy of protein structures and molecular dynamics simulations. This is done by comparing: (1) three X-ray structures of oxidized Escherichia coli thioredoxin (Trx-S2); (2) 14 NMR structures of reduced E. coli thioredoxin (Trx-(SH)2); and (3) 30 different simulations, 15 of Trx-S2 and 15 of Trx-(SH)2. The energy, the agreement with NOE data, the root-mean-square deviation between structures, and the surface characteristics of all these structures are analyzed. The 30 simulations, four water simulations, 20 standard vacuum simulations and six alternative vacuum simulations, are examined with respect to mobility, temperature factors and aromatic side-chain mobility. It is shown that although vacuum simulations may reproduce some parameters, all the features of a water simulation cannot be reproduced in any of these simulations. Several of the parameters described above are shown to be good for discriminating between an accurate and an inaccurate simulation. It is also shown that 100 ps is too short a time to obtain statistically certain temperature factors and correlation functions of aromatic side-chain motions. The results also suggest that performing ten 100 ps simulations spans the conformation space better than one 1 ns simulation.

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Year:  1993        PMID: 8411178     DOI: 10.1006/jmbi.1993.1551

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


  30 in total

1.  Analysis of the effect of electrostatic energy truncation in molecular dynamics simulations of immunoglobulin G light chain dimer.

Authors:  Marcin Król
Journal:  J Mol Model       Date:  2003-07-24       Impact factor: 1.810

2.  Nucleotide modifications and tRNA anticodon-mRNA codon interactions on the ribosome.

Authors:  Olof Allnér; Lennart Nilsson
Journal:  RNA       Date:  2011-10-25       Impact factor: 4.942

3.  Molecular dynamics modeling of the sub-THz vibrational absorption of thioredoxin from E. coli.

Authors:  Naser Alijabbari; Yikan Chen; Igor Sizov; Tatiana Globus; Boris Gelmont
Journal:  J Mol Model       Date:  2011-09-27       Impact factor: 1.810

4.  Scrutinizing molecular mechanics force fields on the submicrosecond timescale with NMR data.

Authors:  Oliver F Lange; David van der Spoel; Bert L de Groot
Journal:  Biophys J       Date:  2010-07-21       Impact factor: 4.033

5.  A statistical approach to the interpretation of molecular dynamics simulations of calmodulin equilibrium dynamics.

Authors:  Vladimir A Likic; Paul R Gooley; Terence P Speed; Emanuel E Strehler
Journal:  Protein Sci       Date:  2005-12       Impact factor: 6.725

Review 6.  Molecular dynamics simulations of nucleic acid-protein complexes.

Authors:  Alexander D Mackerell; Lennart Nilsson
Journal:  Curr Opin Struct Biol       Date:  2008-02-20       Impact factor: 6.809

7.  Toward Fast and Accurate Binding Affinity Prediction with pmemdGTI: An Efficient Implementation of GPU-Accelerated Thermodynamic Integration.

Authors:  Tai-Sung Lee; Yuan Hu; Brad Sherborne; Zhuyan Guo; Darrin M York
Journal:  J Chem Theory Comput       Date:  2017-06-23       Impact factor: 6.006

8.  Multiple molecular dynamics simulations of TEM beta-lactamase: dynamics and water binding of the omega-loop.

Authors:  Fabian Bös; Jürgen Pleiss
Journal:  Biophys J       Date:  2009-11-04       Impact factor: 4.033

9.  Locally accessible conformations of proteins: multiple molecular dynamics simulations of crambin.

Authors:  L S Caves; J D Evanseck; M Karplus
Journal:  Protein Sci       Date:  1998-03       Impact factor: 6.725

10.  Application of the random coil index to studying protein flexibility.

Authors:  Mark V Berjanskii; David S Wishart
Journal:  J Biomol NMR       Date:  2007-11-06       Impact factor: 2.835

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