Dataset Information

Characterizing RNA ensembles from NMR data with kinematic models.

ABSTRACT: Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem-loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention.

SUBMITTER: Fonseca R

PROVIDER: S-EPMC4150802 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Characterizing RNA ensembles from NMR data with kinematic models.

Fonseca Rasmus R Pachov Dimitar V DV Bernauer Julie J van den Bedem Henry H

Nucleic acids research 20140811 15

Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently ...[more]

PMID: 25114056

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Dataset Information

Characterizing RNA ensembles from NMR data with kinematic models.

Publications

Characterizing RNA ensembles from NMR data with kinematic models.

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