Literature DB >> 18320330

The war of tools: how can NMR spectroscopists detect errors in their structures?

Edoardo Saccenti1, Antonio Rosato.   

Abstract

Protein structure determination by NMR methods has started in the mid-eighties and has been growing steadily since then. Ca. 14% of the protein structures deposited in the PDB have been solved by NMR. The evaluation of the quality of NMR structures however is still lacking a well-established practice. In this work, we examined various tools for the assessment of structural quality to ascertain the extent to which these tools could be applied to detect flaws in NMR structures. In particular, we investigated the variation in the scores assigned by these programs as a function of the deviation of the structures induced by errors in assignments or in the upper distance limits used. These perturbations did not distort radically the protein fold, but resulted in backbone RMS deviations up to 3 A, which is in line with errors highlighted in the available literature. We found that it is quite difficult to discriminate the structures perturbed because of misassignments from the original ones, also because the spread in score over the conformers of the original bundle is relatively large. varphi-psi distributions and normality scores related to the backbone conformation and to the distribution of side-chain dihedral angles are the most sensitive indicators of flaws.

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Year:  2008        PMID: 18320330     DOI: 10.1007/s10858-008-9228-4

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


  49 in total

1.  The Protein Data Bank.

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Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

Review 2.  Validation of protein crystal structures.

Authors:  G J Kleywegt
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2000-03

3.  Protein NMR structure determination with automated NOE assignment using the new software CANDID and the torsion angle dynamics algorithm DYANA.

Authors:  Torsten Herrmann; Peter Güntert; Kurt Wüthrich
Journal:  J Mol Biol       Date:  2002-05-24       Impact factor: 5.469

4.  Automated assignment of NOESY NMR spectra using a knowledge based method (KNOWNOE).

Authors:  Wolfram Gronwald; Sherif Moussa; Ralph Elsner; Astrid Jung; Bernhard Ganslmeier; Jochen Trenner; Werner Kremer; Klaus-Peter Neidig; Hans Robert Kalbitzer
Journal:  J Biomol NMR       Date:  2002-08       Impact factor: 2.835

5.  BioMagResBank database with sets of experimental NMR constraints corresponding to the structures of over 1400 biomolecules deposited in the Protein Data Bank.

Authors:  Jurgen F Doreleijers; Steve Mading; Dimitri Maziuk; Kassandra Sojourner; Lei Yin; Jun Zhu; John L Markley; Eldon L Ulrich
Journal:  J Biomol NMR       Date:  2003-06       Impact factor: 2.835

6.  Assignment validation software suite for the evaluation and presentation of protein resonance assignment data.

Authors:  Hunter N B Moseley; Gurmukh Sahota; Gaetano T Montelione
Journal:  J Biomol NMR       Date:  2004-04       Impact factor: 2.835

7.  Recommendations for the presentation of NMR structures of proteins and nucleic acids. IUPAC-IUBMB-IUPAB Inter-Union Task Group on the Standardization of Data Bases of Protein and Nucleic Acid Structures Determined by NMR Spectroscopy.

Authors:  J L Markley; A Bax; Y Arata; C W Hilbers; R Kaptein; B D Sykes; P E Wright; K Wüthrich
Journal:  J Biomol NMR       Date:  1998-07       Impact factor: 2.835

8.  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

9.  Torsion angle dynamics for NMR structure calculation with the new program DYANA.

Authors:  P Güntert; C Mumenthaler; K Wüthrich
Journal:  J Mol Biol       Date:  1997-10-17       Impact factor: 5.469

10.  TAP score: torsion angle propensity normalization applied to local protein structure evaluation.

Authors:  Silvio C E Tosatto; Roberto Battistutta
Journal:  BMC Bioinformatics       Date:  2007-05-15       Impact factor: 3.169

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  6 in total

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Authors:  Antonija Kuzmanic; Bojan Zagrovic
Journal:  Biophys J       Date:  2010-03-03       Impact factor: 4.033

2.  A protocol for the refinement of NMR structures using simultaneously pseudocontact shift restraints from multiple lanthanide ions.

Authors:  Davide Sala; Andrea Giachetti; Claudio Luchinat; Antonio Rosato
Journal:  J Biomol NMR       Date:  2016-10-22       Impact factor: 2.835

3.  Blind testing of routine, fully automated determination of protein structures from NMR data.

Authors:  Antonio Rosato; James M Aramini; Cheryl Arrowsmith; Anurag Bagaria; David Baker; Andrea Cavalli; Jurgen F Doreleijers; Alexander Eletsky; Andrea Giachetti; Paul Guerry; Aleksandras Gutmanas; Peter Güntert; Yunfen He; Torsten Herrmann; Yuanpeng J Huang; Victor Jaravine; Hendrik R A Jonker; Michael A Kennedy; Oliver F Lange; Gaohua Liu; Thérèse E Malliavin; Rajeswari Mani; Binchen Mao; Gaetano T Montelione; Michael Nilges; Paolo Rossi; Gijs van der Schot; Harald Schwalbe; Thomas A Szyperski; Michele Vendruscolo; Robert Vernon; Wim F Vranken; Sjoerd de Vries; Geerten W Vuister; Bin Wu; Yunhuang Yang; Alexandre M J J Bonvin
Journal:  Structure       Date:  2012-02-08       Impact factor: 5.006

4.  A quality metric for homology modeling: the H-factor.

Authors:  Eric di Luccio; Patrice Koehl
Journal:  BMC Bioinformatics       Date:  2011-02-04       Impact factor: 3.169

5.  A method for validating the accuracy of NMR protein structures.

Authors:  Nicholas J Fowler; Adnan Sljoka; Mike P Williamson
Journal:  Nat Commun       Date:  2020-12-18       Impact factor: 14.919

6.  The NMR restraints grid at BMRB for 5,266 protein and nucleic acid PDB entries.

Authors:  Jurgen F Doreleijers; Wim F Vranken; Christopher Schulte; Jundong Lin; Jonathan R Wedell; Christopher J Penkett; Geerten W Vuister; Gert Vriend; John L Markley; Eldon L Ulrich
Journal:  J Biomol NMR       Date:  2009-10-07       Impact factor: 2.835

  6 in total

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