RNA 3D Motif Dynamics Guide Assembly of the Replication Initiation Complex in Flaviviruses
Streit, L. V.; Onikubo, T.; Astore, M. A.; Cioppa, E. A.; Olinares, P. D. B.; Urnavicius, L.; Incarnato, D.; Bonilla, S. L.
Show abstract
Viral RNA genomes contain structured elements that recruit the machinery necessary for their replication. However, these mechanisms remain poorly understood because of RNA structures dynamic nature. Using cryo-EM and single-molecule Forster resonance energy transfer, we show that the flaviviral stem-loop A (SLA)--which recruits the viral polymerase NS5 to initiate negative-strand synthesis--populates a conserved, multi-state conformational ensemble governed by a dynamic three-dimensional (3D) motif. Structures of Zika and dengue SLA-NS5 complexes reveal that NS5 engages a preorganized SLA conformation. Notably, destabilizing this conformation impairs negative-strand synthesis without affecting NS5 binding. Thus, the conserved SLA 3D ensemble guides a post-binding conformational search that converts an initial encounter complex into a productive replication-initiation complex--revealing how RNA conformational ensembles, rather than static structures, dictate function. SUMMARYViral genomes encode dynamic RNA structures that are specifically recognized by proteins to regulate critical steps of the viral life cycle. Although these RNAs exist as multi-state conformational ensembles, structural studies have largely captured single conformations, limiting our mechanistic understanding of RNA-protein recognition and function. Here, using single-particle cryo-electron microscopy (cryo-EM), single-molecule Forster resonance energy transfer, and biochemical assays, we show how flaviviral genomes use structural dynamics encoded in their stem-loop A (SLA) to guide a conserved, multi-step mechanism of negative-strand synthesis initiation by non-structural protein 5 (NS5). Cryo-EM ensembles of SLAs from dengue, Zika, West Nile, and yellow fever viruses reveal a conserved conformational landscape dictated by alternative stacking configurations of a central three-way junction (3WJ). Cryo-EM structures of SLA-NS5 complexes from dengue and Zika show that NS5 engages a specific state within SLA 3D ensemble, one in which the 3WJ adopts a GRR/A tetraloop-like motif that we identify across diverse structural RNAs. Strikingly, mutations that substantially destabilize this state impair negative-strand synthesis without affecting NS5 binding--decoupling binding from function and ruling out a simple conformational-capture mechanism. Instead, the SLAs intrinsic structural dynamics direct a post-binding conformational search that converts an initial, conformationally heterogeneous encounter complex into a productive replication-initiation complex. These results demonstrate a mechanism of RNA-protein recognition in which the 3D conformational ensemble of an RNA guides formation of the functional state downstream of binding, and identify a ubiquitous, intrinsically dynamic 3D motif within the SLAs 3WJ as a critical determinant of flavivirus negative-strand synthesis.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Conformational Landscapes of a Class I Ribonucleotide Reductase Complex during Turnover Reveal Intrinsic Dynamics and Asymmetry 97%
- CRYO-EM STRUCTURE OF THE DELTA-RETROVIRAL INTASOME IN COMPLEX WITH THE PP2A REGULATORY SUBUNIT B56gamma 97%
- Sm-like protein Rof inhibits transcription termination factor Rho by binding site obstruction and conformational insulation 97%
Similar papers in this journal
Similar papers in this journal
- Structures of vertebrate R2 retrotransposon complexes during target-primed reverse transcription and after second strand nicking 97%
- A conserved rRNA switch is central to decoding site maturation on the small ribosomal subunit 97%
- Structural basis of bacteriophage T5 infection trigger and E. coli cell wall perforation 97%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.