Biology – Quantitative Biology – Biomolecules
Scientific paper
2011-10-03
Biology
Quantitative Biology
Biomolecules
Scientific paper
RNA crystallographic models, our richest sources of RNA structural information, contain pervasive errors due to ambiguities in manually fitting RNA backbones into experimental density maps. To resolve these ambiguities, we have developed a new Rosetta structure prediction tool (ERRASER: Enumerative Real-space Refinement ASsisted by Electron density under Rosetta) and coupled it to MolProbity validation and PHENIX diffraction-based refinement. On 15 crystallographic datasets for ribozymes, riboswitches, and other RNA domains, ERRASER/PHENIX corrects the majority of identifiable sugar pucker errors, steric clashes, suspicious backbone rotamers, and incorrect bond lengths/angles, while, on average, improving Rfree correlation to set-aside diffraction data by 0.010. As further confirmation of improved accuracy, the refinement enhances agreement between crystals solved by independent groups and between domains related by non-crystallographic symmetry (NCS). Finally, we demonstrate successful application of ERRASER on coordinates for an entire 30S ribosomal subunit. By rapidly and systematically disambiguating RNA model fitting, ERRASER enables RNA crystallography with significantly fewer errors.
Chou Fang-Chieh
Das Rhiju
Sripakdeevong Parin
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