Literature DB >> 17225069

The MUMO (minimal under-restraining minimal over-restraining) method for the determination of native state ensembles of proteins.

Barbara Richter1, Joerg Gsponer, Péter Várnai, Xavier Salvatella, Michele Vendruscolo.   

Abstract

While reliable procedures for determining the conformations of proteins are available, methods for generating ensembles of structures that also reflect their flexibility are much less well established. Here we present a systematic assessment of the ability of ensemble-averaged molecular dynamics simulations with ensemble-averaged NMR restraints to simultaneously reproduce the average structure of proteins and their associated dynamics. We discuss the effects that under-restraining (overfitting) and over-restraining (underfitting) have on the structures generated in ensemble-averaged molecular simulations. We then introduce the MUMO (minimal under-restraining minimal over-restraining) method, a procedure in which different observables are averaged over a different number of molecules. As both over-restraining and under-restraining are significantly reduced in the MUMO method, it is possible to generate ensembles of conformations that accurately characterize both the structure and the dynamics of native states of proteins. The application of the MUMO method to the protein ubiquitin yields a high-resolution structural ensemble with an RDC Q-factor of 0.19.

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Year:  2007        PMID: 17225069     DOI: 10.1007/s10858-006-9117-7

Source DB:  PubMed          Journal:  J Biomol NMR        ISSN: 0925-2738            Impact factor:   2.835


  49 in total

Review 1.  Molecular dynamics simulations of biomolecules.

Authors:  Martin Karplus; J Andrew McCammon
Journal:  Nat Struct Biol       Date:  2002-09

2.  Temperature dependence of anisotropic protein backbone dynamics.

Authors:  Tianzhi Wang; Sheng Cai; Erik R P Zuiderweg
Journal:  J Am Chem Soc       Date:  2003-07-16       Impact factor: 15.419

Review 3.  Protein flexibility and computer-aided drug design.

Authors:  Chung F Wong; J Andrew McCammon
Journal:  Annu Rev Pharmacol Toxicol       Date:  2002-01-10       Impact factor: 13.820

Review 4.  Molecular dynamics simulations in biology.

Authors:  M Karplus; G A Petsko
Journal:  Nature       Date:  1990-10-18       Impact factor: 49.962

5.  Inferential structure determination.

Authors:  Wolfgang Rieping; Michael Habeck; Michael Nilges
Journal:  Science       Date:  2005-07-08       Impact factor: 47.728

6.  Comparing atomistic simulation data with the NMR experiment: how much can NOEs actually tell us?

Authors:  Bojan Zagrovic; Wilfred F van Gunsteren
Journal:  Proteins       Date:  2006-04-01

7.  Influence of internal dynamics on accuracy of protein NMR structures: derivation of realistic model distance data from a long molecular dynamics trajectory.

Authors:  T R Schneider; A T Brünger; M Nilges
Journal:  J Mol Biol       Date:  1999-01-15       Impact factor: 5.469

8.  Anisotropy and anharmonicity of atomic fluctuations in proteins: implications for X-ray analysis.

Authors:  T Ichiye; M Karplus
Journal:  Biochemistry       Date:  1988-05-03       Impact factor: 3.162

9.  Assessing the quality of solution nuclear magnetic resonance structures by complete cross-validation.

Authors:  A T Brünger; G M Clore; A M Gronenborn; R Saffrich; M Nilges
Journal:  Science       Date:  1993-07-16       Impact factor: 47.728

10.  Temperature-dependence of protein hydrogen bond properties as studied by high-resolution NMR.

Authors:  Florence Cordier; Stephan Grzesiek
Journal:  J Mol Biol       Date:  2002-04-12       Impact factor: 5.469

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  54 in total

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3.  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
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Journal:  J Biomol NMR       Date:  2015-10-17       Impact factor: 2.835

5.  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

6.  Influence of the fluctuations of the alignment tensor on the analysis of the structure and dynamics of proteins using residual dipolar couplings.

Authors:  X Salvatella; B Richter; M Vendruscolo
Journal:  J Biomol NMR       Date:  2007-11-21       Impact factor: 2.835

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

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

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Journal:  Biophys J       Date:  2011-06-22       Impact factor: 4.033

9.  The expanded FindCore method for identification of a core atom set for assessment of protein structure prediction.

Authors:  David A Snyder; Jennifer Grullon; Yuanpeng J Huang; Roberto Tejero; Gaetano T Montelione
Journal:  Proteins       Date:  2014-02

10.  Doing molecular biophysics: finding, naming, and picturing signal within complexity.

Authors:  Jane S Richardson; David C Richardson
Journal:  Annu Rev Biophys       Date:  2013-02-28       Impact factor: 12.981

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