  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.
