Literature DB >> 7680379

Modeling the three-dimensional structure of RNA using discrete nucleotide conformational sets.

D Gautheret1, F Major, R Cedergren.   

Abstract

The flexibility about seven torsion angles in nucleotides constitutes a severe obstacle to computer modeling of RNA. The computational feasibility of RNA conformational searches can be enhanced by assigning to each nucleotide a set of discrete conformations. In this work, four types of discrete conformational sets for the atomic representation of nucleotide structures were defined and evaluated. These sets, comprising between 10 and 30 conformations, were tested for their ability to reproduce known RNA structures and to generate structures responding to new specifications. Conformational searches were performed with the MC-SYM program, which allows for the generation of all structures satisfying a predetermined set of three-dimensional constraints in a given discrete space. Results with known hairpin loop structures show that root-mean-square deviations of about 1.5 A for backbone atoms and about 2.0 A for all atoms between the modeled and X-ray crystal structures can be expected. The conformational set that gives the most faithful representation of test structures is based on the classification of nucleotide conformations derived from a structural database. Representative conformations are selected from each class that adequately sample variations in backbone direction, sugar pucker and base orientation. With this conformational set, most of the important features of test hairpin structures are reproduced with fidelity, indicating that biologically useful models can be constructed from the combination of discrete nucleotide conformations and an algorithm that rapidly and systematically scans the pre-defined conformational space.

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Year:  1993        PMID: 7680379     DOI: 10.1006/jmbi.1993.1104

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


  22 in total

1.  Conformational analysis of DNA-trinucleotide-hairpin-loop structures using a continuum solvent model.

Authors:  M Zacharias
Journal:  Biophys J       Date:  2001-05       Impact factor: 4.033

2.  Structure of the yeast U2/U6 snRNA complex.

Authors:  Jordan E Burke; Dipali G Sashital; Xiaobing Zuo; Yun-Xing Wang; Samuel E Butcher
Journal:  RNA       Date:  2012-02-10       Impact factor: 4.942

3.  Turning limited experimental information into 3D models of RNA.

Authors:  Samuel Coulbourn Flores; Russ B Altman
Journal:  RNA       Date:  2010-07-22       Impact factor: 4.942

4.  Elucidating the higher-order structure of biopolymers by structural probing and mass spectrometry: MS3D.

Authors:  Daniele Fabris; Eizadora T Yu
Journal:  J Mass Spectrom       Date:  2010-08       Impact factor: 1.982

5.  Describing RNA structure by libraries of clustered nucleotide doublets.

Authors:  Michael T Sykes; Michael Levitt
Journal:  J Mol Biol       Date:  2005-08-05       Impact factor: 5.469

Review 6.  RNA nanotechnology: engineering, assembly and applications in detection, gene delivery and therapy.

Authors:  Peixuan Guo
Journal:  J Nanosci Nanotechnol       Date:  2005-12

7.  The RNA Ontology Consortium: an open invitation to the RNA community.

Authors:  Neocles B Leontis; Russ B Altman; Helen M Berman; Steven E Brenner; James W Brown; David R Engelke; Stephen C Harvey; Stephen R Holbrook; Fabrice Jossinet; Suzanna E Lewis; François Major; David H Mathews; Jane S Richardson; James R Williamson; Eric Westhof
Journal:  RNA       Date:  2006-02-16       Impact factor: 4.942

8.  Conformationally restricted nucleotides as a probe of structure-function relationships in RNA.

Authors:  Kristine R Julien; Minako Sumita; Po-Han Chen; Ite A Laird-Offringa; Charles G Hoogstraten
Journal:  RNA       Date:  2008-07-02       Impact factor: 4.942

9.  RNA2D3D: a program for generating, viewing, and comparing 3-dimensional models of RNA.

Authors:  Hugo M Martinez; Jacob V Maizel; Bruce A Shapiro
Journal:  J Biomol Struct Dyn       Date:  2008-06

10.  A genetic algorithm based molecular modeling technique for RNA stem-loop structures.

Authors:  H Ogata; Y Akiyama; M Kanehisa
Journal:  Nucleic Acids Res       Date:  1995-02-11       Impact factor: 16.971

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