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Proc Natl Acad Sci U S A. 2010 May 4;107(18):8177-82. doi: 10.1073/pnas.0911888107. Epub 2010 Apr 19.

Semiautomated model building for RNA crystallography using a directed rotameric approach.

Author information

1
Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.

Abstract

Structured RNA molecules play essential roles in a variety of cellular processes; however, crystallographic studies of such RNA molecules present a large number of challenges. One notable complication arises from the low resolutions typical of RNA crystallography, which results in electron density maps that are imprecise and difficult to interpret. This problem is exacerbated by the lack of computational tools for RNA modeling, as many of the techniques commonly used in protein crystallography have no equivalents for RNA structure. This leads to difficulty and errors in the model building process, particularly in modeling of the RNA backbone, which is highly error prone due to the large number of variable torsion angles per nucleotide. To address this, we have developed a method for accurately building the RNA backbone into maps of intermediate or low resolution. This method is semiautomated, as it requires a crystallographer to first locate phosphates and bases in the electron density map. After this initial trace of the molecule, however, an accurate backbone structure can be built without further user intervention. To accomplish this, backbone conformers are first predicted using RNA pseudotorsions and the base-phosphate perpendicular distance. Detailed backbone coordinates are then calculated to conform both to the predicted conformer and to the previously located phosphates and bases. This technique is shown to produce accurate backbone structure even when starting from imprecise phosphate and base coordinates. A program implementing this methodology is currently available, and a plugin for the Coot model building program is under development.

PMID:
20404211
PMCID:
PMC2889552
DOI:
10.1073/pnas.0911888107
[Indexed for MEDLINE]
Free PMC Article

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