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.
Highlights
IntroductionNon-coding ribonucleic acids (ncRNAs) mediate important cellular processes. Transfer RNA and ribosomal RNA are essential functional components in protein synthesis [1]
Non-coding ribonucleic acids mediate important cellular processes
For each RNA molecule, we created a set of 1000 samples starting from the first model of the nuclear magnetic resonance (NMR) bundle
Summary
Non-coding ribonucleic acids (ncRNAs) mediate important cellular processes. Transfer RNA and ribosomal RNA are essential functional components in protein synthesis [1]. Short interfering RNAs (siRNAs) and microRNAs (miRNAs) are the effector molecules in RNA interference, the process of silencing expression of specific genes in cells, and hold great promise as therapeutics [2,3]. RNA molecules are highly dynamic, sampling a wide range of conformational rearrangements to interact with binding partners and perform their function [6,7]. Solution-state nuclear magnetic resonance (NMR) spectroscopy can probe the RNA conformational landscape at timescales ranging from picosecond to seconds or longer, often providing detailed evidence of dynamically interchanging, sparsely populated substates [8,9]. Characterizing conformational substates would offer tremendous potential for uncovering functional mechanisms [10], for riboswitches [11], or predicting molecular interactions of RNA sub-units, such as in nanostructures [12]. Resolving motionally averaged NMR measurements into constituent, structural contributions that represent key features of the data remains extremely challenging [13]
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