An integrative NMR-SAXS approach for structural determination of large RNAs defines the substrate-free state of a <i>trans</i> -cleaving <i>Neurospora</i> Varkud Satellite ribozyme
Bibliographic record
Abstract
The divide-and-conquer strategy is commonly used for protein structure determination, but its applications to high-resolution structure determination of RNAs have been limited. Here, we introduce an integrative approach based on the divide-and-conquer strategy that was undertaken to determine the solution structure of an RNA model system, the Neurospora VS ribozyme. NMR and SAXS studies were conducted on a minimal trans VS ribozyme as well as several isolated subdomains. A multi-step procedure was used for structure determination that first involved pairing refined NMR structures with SAXS data to obtain structural subensembles of the various subdomains. These subdomain structures were then assembled to build a large set of structural models of the ribozyme, which was subsequently filtered using SAXS data. The resulting NMR-SAXS structural ensemble shares several similarities with the reported crystal structures of the VS ribozyme. However, a local structural difference is observed that affects the global fold by shifting the relative orientation of the two three-way junctions. Thus, this finding highlights a global conformational change associated with substrate binding in the VS ribozyme that is likely critical for its enzymatic activity. Structural studies of other large RNAs should benefit from similar integrative approaches that allow conformational sampling of assembled fragments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".