Literature DB >> 26306428

Modulating RNA Alignment Using Directional Dynamic Kinks: Application in Determining an Atomic-Resolution Ensemble for a Hairpin using NMR Residual Dipolar Couplings.

Loïc Salmon1, George M Giambaşu2, Evgenia N Nikolova3, Katja Petzold4, Akash Bhattacharya5, David A Case2, Hashim M Al-Hashimi6.   

Abstract

Approaches that combine experimental data and computational molecular dynamics (MD) to determine atomic resolution ensembles of biomolecules require the measurement of abundant experimental data. NMR residual dipolar couplings (RDCs) carry rich dynamics information, however, difficulties in modulating overall alignment of nucleic acids have limited the ability to fully extract this information. We present a strategy for modulating RNA alignment that is based on introducing variable dynamic kinks in terminal helices. With this strategy, we measured seven sets of RDCs in a cUUCGg apical loop and used this rich data set to test the accuracy of an 0.8 μs MD simulation computed using the Amber ff10 force field as well as to determine an atomic resolution ensemble. The MD-generated ensemble quantitatively reproduces the measured RDCs, but selection of a sub-ensemble was required to satisfy the RDCs within error. The largest discrepancies between the RDC-selected and MD-generated ensembles are observed for the most flexible loop residues and backbone angles connecting the loop to the helix, with the RDC-selected ensemble resulting in more uniform dynamics. Comparison of the RDC-selected ensemble with NMR spin relaxation data suggests that the dynamics occurs on the ps-ns time scales as verified by measurements of R(1ρ) relaxation-dispersion data. The RDC-satisfying ensemble samples many conformations adopted by the hairpin in crystal structures indicating that intrinsic plasticity may play important roles in conformational adaptation. The approach presented here can be applied to test nucleic acid force fields and to characterize dynamics in diverse RNA motifs at atomic resolution.

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Year:  2015        PMID: 26306428      PMCID: PMC4748170          DOI: 10.1021/jacs.5b07229

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  82 in total

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  10 in total

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Journal:  J Biomol NMR       Date:  2019-05-02       Impact factor: 2.835

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8.  Rapid and accurate determination of atomistic RNA dynamic ensemble models using NMR and structure prediction.

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9.  High-performance virtual screening by targeting a high-resolution RNA dynamic ensemble.

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10.  High-resolution small RNA structures from exact nuclear Overhauser enhancement measurements without additional restraints.

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  10 in total

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