9syf | pdb_00009syf

Beyond single-state RNA structural biology: MD/NMR description of temperature-sensitive dynamic RNA ensembles - GCAA MD conformational ensemble

spinqualitylabelsall models 9syf Show:Asymmetric Unit Biological Assembly Drag the structure with the mouse to rotate   Export Animated Image   Print3D Structural highlights 9syf is a 1 chain structure with sequence from Synthetic RNA. Full experimental information is available from OCA. For a guided tour on the structure components use FirstGlance. Method: Solution NMR, models Resources: FirstGlance, OCA, PDBe, RCSB, PDBsum, ProSAT Publication Abstract from PubMed While the GNRA tetraloops are an extensively studied and common RNA motif, their dynamic NMR structures in solution integrating state-of-the-art NMR parameters such as residual dipolar couplings (RDC) and cross correlated relaxation rates (CCR) have previously not been determined. Given their dominant occurrence among tetraloops in the PDB and the advance of experimentally reweighted MD simulations, the present work aims at investigating the entire conformational space of two known GNRA tetraloops sequences by an extensive NMR investigation of NOEs, J-couplings constants, RDCs and CCRs. As classical structure calculation proved insufficient for the more dynamic tetraloop we turned to Bayesian/maximum entropy reweighting of molecular simulations using our rich set of experiments. The resulting ensembles were clustered and compared to classically restrained structure calculations, structures from the PDB and models predicted by the prediction algorithms FarFar and Alphafold 3. Our results show that GNRA tetraloops can vary in dynamic sampling of conformational space. They highlight the importance of individual experimental validation of computationally obtained dynamic ensembles and model predictions. Integrated NMR/MD investigation reveals differences after reweighting in conformational ensembles of GAAG and GCAA tetraloops.,Leopold D, Oxenfarth A, Thomasen FE, Kummerer F, Schnieders R, Pinter G, Wacker A, Jonker HRA, Furtig B, Richter C, Lindorff-Larsen K, Schwalbe H RNA. 2026 May 29:rna.081067.126. doi: 10.1261/rna.081067.126. PMID:42215280 From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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