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• W2805578964 abstract "Abstract RNA-protein complexes underlie numerous cellular processes including translation, splicing, and posttranscriptional regulation of gene expression. The structures of these complexes are crucial to their functions but often elude high-resolution structure determination. Computational methods are needed that can integrate low-resolution data for RNA-protein complexes while modeling de novo the large conformational changes of RNA components upon complex formation. To address this challenge, we describe a Rosetta method called RNP-denovo to simultaneously fold and dock RNA to a protein surface. On a benchmark set of structurally diverse RNA-protein complexes that are not solvable with prior strategies, this fold-and-dock method consistently sampled native-like structures with better than nucleotide resolution. We revisited three past blind modeling challenges in which previous methods gave poor results: human telomerase, an RNA methyltransferase with a ribosomal RNA domain, and the spliceosome. When coupled with the same sparse FRET, cross-linking, and functional data used in previous work, RNP-denovo gave models with significantly improved accuracy. These results open a route to computationally modeling global folds of RNA-protein complexes from low-resolution data." @default.
• W2805578964 created "2018-06-13" @default.
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• W2805578964 date "2018-06-05" @default.
• W2805578964 modified "2023-10-17" @default.
• W2805578964 title "Sampling native-like structures of RNA-protein complexes through Rosetta folding and docking" @default.
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• W2805578964 doi "https://doi.org/10.1101/339374" @default.
• W2805578964 hasPublicationYear "2018" @default.
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