%0 Journal Article
%T Correcting pervasive errors in RNA crystallography through enumerative structure prediction
%A Fang-Chieh Chou
%A Parin Sripakdeevong
%A Sergey M. Dibrov
%A Thomas Hermann
%A Rhiju Das
%J Quantitative Biology
%D 2011
%I arXiv
%R 10.1038/nmeth.2262
%X 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 Rfree factor, resolves functionally important discrepancies in noncanonical structure and refines low-resolution models to better match higher-resolution models.
%U http://arxiv.org/abs/1110.0276v3