Literature DB >> 20696393

Using NMR chemical shifts as structural restraints in molecular dynamics simulations of proteins.

Paul Robustelli1, Kai Kohlhoff, Andrea Cavalli, Michele Vendruscolo.   

Abstract

We introduce a procedure to determine the structures of proteins by incorporating NMR chemical shifts as structural restraints in molecular dynamics simulations. In this approach, the chemical shifts are expressed as differentiable functions of the atomic coordinates and used to compute forces to generate trajectories that lead to the reduction of the differences between experimental and calculated chemical shifts. We show that this strategy enables the folding of a set of proteins with representative topologies starting from partially denatured initial conformations without the use of additional experimental information. This method also enables the straightforward combination of chemical shifts with other standard NMR restraints, including those derived from NOE, J-coupling, and residual dipolar coupling measurements. We illustrate this aspect by calculating the structure of a transiently populated excited state conformation from chemical shift and residual dipolar coupling data measured by relaxation dispersion NMR experiments. Copyright 2010 Elsevier Ltd. All rights reserved.

Mesh:

Substances:

Year:  2010        PMID: 20696393     DOI: 10.1016/j.str.2010.04.016

Source DB:  PubMed          Journal:  Structure        ISSN: 0969-2126            Impact factor:   5.006


  55 in total

1.  VITAL NMR: using chemical shift derived secondary structure information for a limited set of amino acids to assess homology model accuracy.

Authors:  Michael C Brothers; Anna E Nesbitt; Michael J Hallock; Sanjeewa G Rupasinghe; Ming Tang; Jason Harris; Jerome Baudry; Mary A Schuler; Chad M Rienstra
Journal:  J Biomol NMR       Date:  2011-11-03       Impact factor: 2.835

2.  Alternate states of proteins revealed by detailed energy landscape mapping.

Authors:  Michael D Tyka; Daniel A Keedy; Ingemar André; Frank Dimaio; Yifan Song; David C Richardson; Jane S Richardson; David Baker
Journal:  J Mol Biol       Date:  2010-11-10       Impact factor: 5.469

3.  A robust algorithm for optimizing protein structures with NMR chemical shifts.

Authors:  Mark Berjanskii; David Arndt; Yongjie Liang; David S Wishart
Journal:  J Biomol NMR       Date:  2015-09-07       Impact factor: 2.835

4.  The Exact NOE as an Alternative in Ensemble Structure Determination.

Authors:  Beat Vögeli; Simon Olsson; Peter Güntert; Roland Riek
Journal:  Biophys J       Date:  2016-01-05       Impact factor: 4.033

5.  Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction.

Authors:  Juuso Lehtivarjo; Kari Tuppurainen; Tommi Hassinen; Reino Laatikainen; Mikael Peräkylä
Journal:  J Biomol NMR       Date:  2012-03       Impact factor: 2.835

6.  NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers.

Authors:  Ashok Sekhar; Lewis E Kay
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-18       Impact factor: 11.205

7.  Physics-based method to validate and repair flaws in protein structures.

Authors:  Osvaldo A Martin; Yelena A Arnautova; Alejandro A Icazatti; Harold A Scheraga; Jorge A Vila
Journal:  Proc Natl Acad Sci U S A       Date:  2013-09-30       Impact factor: 11.205

8.  Defining a length scale for millisecond-timescale protein conformational exchange.

Authors:  Ashok Sekhar; Pramodh Vallurupalli; Lewis E Kay
Journal:  Proc Natl Acad Sci U S A       Date:  2013-06-25       Impact factor: 11.205

Review 9.  Chemical exchange in biomacromolecules: past, present, and future.

Authors:  Arthur G Palmer
Journal:  J Magn Reson       Date:  2014-04       Impact factor: 2.229

Review 10.  Describing sequence-ensemble relationships for intrinsically disordered proteins.

Authors:  Albert H Mao; Nicholas Lyle; Rohit V Pappu
Journal:  Biochem J       Date:  2013-01-15       Impact factor: 3.857

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.