ArticleNucleic acids research2012
Unraveling the structural complexity in a single-stranded RNA tail: implications for efficient ligand binding in the prequeuosine riboswitch.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Perspective - RNA Dynamics Today and Tomorrow.Journal of molecular biology · 2026Review
- RNA folding kinetics control riboswitch sensitivity in vivo.Nature communications · 2025Article
- Supercomputing in the biological sciences: Toward Zettascale and Yottascale simulations.Current opinion in structural biology · 2024Review
- Nanosecond chain dynamics of single-stranded nucleic acids.Nature communications · 2024Article
- RNA folding kinetics control riboswitch sensitivity in vivo.bioRxiv : the preprint server for biology · 2024Article
- Hierarchical Assembly of Single-Stranded RNA.Journal of chemical theory and computation · 2024Article
- The translational repressor Glorund uses interchangeable RNA recognition domains to recognize Drosophila nanos.Nucleic acids research · 2023Article
- Anomalous Reverse Transcription through Chemical Modifications in Polyadenosine Stretches.Biochemistry · 2020Article
- Global analysis of protein synthesis in Flavobacterium johnsoniae reveals the use of Kozak-like sequences in diverse bacteria.Nucleic acids research · 2019Article
- RNA Dynamics by NMR Spectroscopy.Chembiochem : a European journal of chemical biology · 2019Review
- Structural Studies of the 3',3'-cGAMP Riboswitch Induced by Cognate and Noncognate Ligands Using Molecular Dynamics Simulation.International journal of molecular sciences · 2018Article
- Increasing the length of poly-pyrimidine bulges broadens RNA conformational ensembles with minimal impact on stacking energetics.RNA (New York, N.Y.) · 2018Article
- RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview.Chemical reviews · 2018Review
- Structure of RNA Stem Loop B from the Picornavirus Replication Platform.Biochemistry · 2017Article
- Direct NOE simulation from long MD trajectories.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2016Article
- Conformational Rearrangements of Individual Nucleotides during RNA-Ligand Binding Are Rate-Differentiated.Journal of the American Chemical Society · 2016Article
- Tuning RNA Flexibility with Helix Length and Junction Sequence.Biophysical journal · 2015Article
- Molecular mechanism for preQ1-II riboswitch function revealed by molecular dynamics.RNA (New York, N.Y.) · 2015Article
- NMR studies of dynamic biomolecular conformational ensembles.Progress in nuclear magnetic resonance spectroscopy · 2015Review
- Ligand-detected relaxation dispersion NMR spectroscopy: dynamics of preQ1-RNA binding.Angewandte Chemie (International ed. in English) · 2015Article
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6 authors.
Funding
Abstract
Single-stranded RNAs (ssRNAs) are ubiquitous RNA elements that serve diverse functional roles. Much of our understanding of ssRNA conformational behavior is limited to structures in which ssRNA directly engages in tertiary interactions or is recognized by proteins. Little is known about the structural and dynamic behavior of free ssRNAs at atomic resolution. Here, we report the collaborative application of nuclear magnetic resonance (NMR) and replica exchange molecular dynamics (REMD) simulations to characterize the 12 nt ssRNA tail derived from the prequeuosine riboswitch. NMR carbon spin relaxation data and residual dipolar coupling measurements reveal a flexible yet stacked core adopting an A-form-like conformation, with the level of order decreasing toward the terminal ends. An A-to-C mutation within the polyadenine tract alters the observed dynamics consistent with the introduction of a dynamic kink. Pre-ordering of the tail may increase the efficacy of ligand binding above that achieved by a random-coil ssRNA. The REMD simulations recapitulate important trends in the NMR data, but suggest more internal motions than inferred from the NMR analysis. Our study unmasks a previously unappreciated level of complexity in ssRNA, which we believe will also serve as an excellent model system for testing and developing computational force fields.
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