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

Biomolecules form dynamic ensembles of many inter-converting conformations which are key for understanding how they fold and function. However, determining ensembles is challenging because the information required to specify atomic structures for thousands of conformations far exceeds that of experimental measurements. We addressed this data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a conformation library. Refinement of this library with NMR residual dipolar couplings provided an atomistic ensemble model for HIV-1 TAR, and the model accuracy was independently supported by comparisons to quantum-mechanical calculations of NMR chemical shifts, comparison to a crystal structure of a substate, and through designed ensemble redistribution via atomic mutagenesis. Applications to TAR bulge variants and more complex tertiary RNAs support the generality of this approach and the potential to make the determination of atomic-resolution RNA ensembles routine.

An RNA dynamic ensemble at atomic resolution

Biomolecules do not fold into a single 3D structure but rather form dynamic ensembles of many inter-converting conformations1. Knowledge of dynamic ensembles is key for understanding how biomolecules fold and function, and for rationally manipulating their activities in drug discovery and synthetic biology2–4. However, solving dynamic ensembles of biomolecules at atomic resolution is a major challenge in structural biology because the information required to specify the position of all atoms in thousands of conformations in an ensemble far exceeds the information content of experimental measurements. Here we addressed the data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a conformational library. Library refinement with NMR residual dipolar couplings enabled determination of an atomic-resolution ensemble for HIV-1 TAR as confirmed by quantum-mechanical calculations of NMR chemical shifts, comparison to a crystal structure of a substate, and through the successful redistribution of the ensemble by design using atomic mutagenesis. The ensemble provides an unprecedented view of how bulge residues cooperatively flip out and undergo sugar repuckering to allow the adjoining helices to stack. The generality of this approach will make determination of atomic-resolution RNA ensembles routine.

Structure of a low-population binding intermediate in protein-RNA recognition

The interaction of the HIV-1 protein transactivator of transcription (Tat) and its cognate transactivation response element (TAR) RNA transactivates viral transcription and represents a paradigm for the widespread occurrence of conformational rearrangements in protein-RNA recognition. Although the structures of free and bound forms of TAR are well characterized, the conformations of the intermediates in the binding process are still unknown. By determining the free energy landscape of the complex using NMR residual dipolar couplings in replica-averaged metadynamics simulations, we observe two low-population intermediates. We then rationally design two mutants, one in the protein and another in the RNA, that weaken specific nonnative interactions that stabilize one of the intermediates. By using surface plasmon resonance, we show that these mutations lower the release rate of Tat, as predicted. These results identify the structure of an intermediate for RNA-protein binding and illustrate a general strategy to achieve this goal with high resolution.