Abstract
We present fragment assembly of RNA with full-atom refinement (FARFAR), a Rosetta framework for predicting and designing noncanonical motifs that define RNA tertiary structure. In a test set of thirty-two 6–20-nucleotide motifs, FARFAR recapitulated 50% of the experimental structures at near-atomic accuracy. Sequence redesign calculations recovered native bases at 65% of residues engaged in noncanonical interactions, and we experimentally validated mutations predicted to stabilize a signal recognition particle domain.
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Acknowledgements
We thank contributors to the current Rosetta codebase, local computer administrators D. Alonso and K. Laidig, the BioX2 cluster (US National Science Foundation award CNS-0619926) and TeraGrid computing resources for enabling rapid development of macromolecular modeling methods; and K. Sjölander for suggesting the acronym FARFAR. This work was supported by the Jane Coffin Childs and Burroughs-Wellcome Foundations (R.D.), the Damon Runyon Cancer Research Foundation (J.K.) and the Howard Hughes Medical Institute (D.B.).
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R.D. designed research, implemented the method, analyzed data and prepared the manuscript; J.K. designed research and implemented the method; and D.B. designed research.
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Das, R., Karanicolas, J. & Baker, D. Atomic accuracy in predicting and designing noncanonical RNA structure. Nat Methods 7, 291–294 (2010). https://doi.org/10.1038/nmeth.1433
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DOI: https://doi.org/10.1038/nmeth.1433
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