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Title(s)
| Title | Language |
Integrated NMR/MD investigation reveals differences after reweighting in conformational ensembles of the GAAG and GCAA tetraloops | en |
Author(s)
| Name | ORCID | GND | Affiliation |
David Leopold | |||
Oxenfarth, Andreas | |||
Thomasen, F. Emil | University of Copenhagen | ||
Kümmerer, Felix | University of Copenhagen | ||
Schnieders, Robbin | |||
Pinter, György | |||
Wacker, Anna | Max Planck Institute for Terrestrial Microbiology | ||
Jonker, Hendrik R. A. | |||
Fürtig, Boris | |||
Lindorff-Larsen, Kresten | University of Copenhagen | ||
Goethe-Universität Frankfurt am Main, Goethe-Universität Frankfurt am Main Fachbereich 14 Biochemie Chemie und Pharmazie, Instruct-ERIC, Massachusetts Institute of Technology, University of Oxford |
Faculty
14 Biochemistry, Chemistry and Pharmacy
DFG-Subject
201-01 Biochemistry
Date Issued
08 May 2026
Publisher(s)
Goethe-Universität Frankfurt
Type(s) of data
Dataset
Software
Language(s)
en
Abstract(s)
| Abstract | Language |
While the GNRA tetraloops are an extensively studied and common folding 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 literature known GNRA tetraloops sequences by an extensive NMR investigation of NOEs, J-couplings constants, RDCs and CCRs as rich experimental base for MD Bayesian/maximum entropy reweighting, as classical structure calculation proofed insufficient for the more dynamic tetraloop. 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. |
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Acquisition Date
May 22, 2026
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May 22, 2026