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PMID: 23202432 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Correcting pervasive errors in RNA crystallography through enumerative structure prediction.

Nature methods ·Vol. 10 ·No. 1 ·2013-01-00 ·Pages 74-6

Chou FC, Sripakdeevong P, Dibrov SM, Hermann T, Das R

Abstract

Three-dimensional RNA models fitted into crystallographic density maps exhibit pervasive conformational ambiguities, geometric errors and steric clashes. To address these problems, we present enumerative real-space refinement assisted by electron density under Rosetta (ERRASER), coupled to Python-based hierarchical environment for integrated 'xtallography' (PHENIX) diffraction-based refinement. On 24 data sets, ERRASER automatically corrects the majority of MolProbity-assessed errors, improves the average R(free) factor, resolves functionally important discrepancies in noncanonical structure and refines low-resolution models to better match higher-resolution models.

MeSH Terms
Computational Biology Crystallography, X-Ray Humans Models, Molecular Nucleic Acid Conformation RNA/chemistry Software
Chemicals
RNA
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Chou Fang-Chieh
Department of Biochemistry, Stanford University, Stanford, California, USA.
Sripakdeevong Parin
Dibrov Sergey M
Hermann Thomas
Das Rhiju
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Article Info
Journal
Nature methods
Abbr.
Nat Methods
ISSN
1548-7105
DOI
10.1038/nmeth.2262
Published
2013-01-00
Epub
2012-00-02
Pages
74-6
Language
English
Region
United States
NLM ID
101215604
PMCID
PMC3531565
Subset
IM
Grants
NIAID NIH HHS · R01 AI072012 · United States
NIGMS NIH HHS · R21 GM102716 · United States
Howard Hughes Medical Institute · United States
NIAID NIH HHS · R01 AI72012 · United States
External Links
PubMed source DOI: 10.1038/nmeth.2262 PMC Full Text View journal details
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