Literature DB >> 24623815

The use of interatomic contact areas to quantify discrepancies between RNA 3D models and reference structures.

Kliment Olechnovič1, Ceslovas Venclovas2.   

Abstract

Growing interest in computational prediction of ribonucleic acid (RNA) three-dimensional structure has highlighted the need for reliable and meaningful methods to compare models and experimental structures. We present a structure superposition-free method to quantify both the local and global accuracy of RNA structural models with respect to the reference structure. The method, initially developed for proteins and here extended to RNA, closely reflects physical interactions, has a simple definition, a fixed range of values and no arbitrary parameters. It is based on the correspondence of respective contact areas between nucleotides or their components (base or backbone). The better is the agreement between respective contact areas in a model and the reference structure, the more accurate the model is considered to be. Since RNA bases account for the largest contact areas, we further distinguish stacking and non-stacking contacts. We have extensively tested the contact area-based evaluation method and found it effective in both revealing local discrepancies and ranking models by their overall quality. Compared to other reference-based RNA model evaluation methods, the new method shows a stronger emphasis on stereochemical quality of models. In addition, it takes into account model completeness, enabling a meaningful evaluation of full models and those missing some residues.
© The Author(s) 2014. Published by Oxford University Press.

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Year:  2014        PMID: 24623815      PMCID: PMC4027170          DOI: 10.1093/nar/gku191

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  14 in total

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3.  RNA canonical and non-canonical base pairing types: a recognition method and complete repertoire.

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Journal:  Nucleic Acids Res       Date:  2002-10-01       Impact factor: 16.971

4.  On the significance of an RNA tertiary structure prediction.

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Journal:  RNA       Date:  2010-05-24       Impact factor: 4.942

5.  All-atom knowledge-based potential for RNA structure prediction and assessment.

Authors:  Emidio Capriotti; Tomas Norambuena; Marc A Marti-Renom; Francisco Melo
Journal:  Bioinformatics       Date:  2011-02-23       Impact factor: 6.937

6.  Contact area difference (CAD): a robust measure to evaluate accuracy of protein models.

Authors:  R A Abagyan; M M Totrov
Journal:  J Mol Biol       Date:  1997-05-09       Impact factor: 5.469

7.  Voronota: A fast and reliable tool for computing the vertices of the Voronoi diagram of atomic balls.

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Journal:  J Comput Chem       Date:  2014-02-12       Impact factor: 3.376

8.  Processing and analysis of CASP3 protein structure predictions.

Authors:  A Zemla; C Venclovas; J Moult; K Fidelis
Journal:  Proteins       Date:  1999

9.  Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters.

Authors:  Magdalena A Jonikas; Randall J Radmer; Alain Laederach; Rhiju Das; Samuel Pearlman; Daniel Herschlag; Russ B Altman
Journal:  RNA       Date:  2009-02       Impact factor: 4.942

10.  MolProbity: all-atom structure validation for macromolecular crystallography.

Authors:  Vincent B Chen; W Bryan Arendall; Jeffrey J Headd; Daniel A Keedy; Robert M Immormino; Gary J Kapral; Laura W Murray; Jane S Richardson; David C Richardson
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  5 in total

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Journal:  Nucleic Acids Res       Date:  2015-02-24       Impact factor: 16.971

4.  A unified statistical potential reveals that amino acid stickiness governs nonspecific recruitment of client proteins into condensates.

Authors:  José A Villegas; Emmanuel D Levy
Journal:  Protein Sci       Date:  2022-07       Impact factor: 6.993

5.  The CAD-score web server: contact area-based comparison of structures and interfaces of proteins, nucleic acids and their complexes.

Authors:  Kliment Olechnovič; Ceslovas Venclovas
Journal:  Nucleic Acids Res       Date:  2014-05-16       Impact factor: 16.971

  5 in total

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