Structural Insights Into Substrate Recognition by the <i>Neurospora</i> Varkud Satellite Ribozyme: Importance of U-Turns at the Kissing-Loop Junction
Bibliographic record
Abstract
Substrate recognition by the Neurospora Varkud satellite ribozyme depends on the formation of a magnesium-dependent kissing-loop interaction between the stem-loop I (SLI) substrate and stem-loop V (SLV) of the catalytic domain. From mutagenesis studies, it has been established that this I/V kissing-loop interaction involves three Watson-Crick base pairs and is associated with a structural rearrangement of the SLI substrate that facilitates catalysis. Here, we report the NMR structural characterization of this I/V kissing-loop using isolated stem-loops. NMR studies were performed on different SLI/SLV complexes containing a common SLV and shiftable, preshifted, or double-stranded SLI variants. These studies confirm the presence of three Watson-Crick base pairs at the kissing-loop junction and provide evidence for the structural rearrangement of shiftable SLI variants upon SLV binding. NMR structure determination of an SLI/SLV complex demonstrates that both the SLI and SLV loops adopt U-turn structures, which facilitates intermolecular Watson-Crick base pairing. Several other interactions at the I/V interface, including base triples and base stacking, help create a continuously stacked structure. These NMR studies provide a structural basis to understand the stability of the I/V kissing-loop interaction and lead us to propose a kinetic model for substrate activation in the VS ribozyme.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".