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  • Title: Correcting pervasive errors in RNA crystallography through enumerative structure prediction.
    Author: Chou FC, Sripakdeevong P, Dibrov SM, Hermann T, Das R.
    Journal: Nat Methods; 2013 Jan; 10(1):74-6. PubMed ID: 23202432.
    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.
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