Role of SLV in SLI substrate recognition by the <i>Neurospora</i> VS ribozyme
Bibliographic record
Abstract
Substrate recognition by the VS ribozyme involves a magnesium-dependent loop/loop interaction between the SLI substrate and the SLV hairpin from the catalytic domain. Recent NMR studies of SLV demonstrated that magnesium ions stabilize a U-turn loop structure and trigger a conformational change for the extruded loop residue U700, suggesting a role for U700 in SLI recognition. Here, we kinetically characterized VS ribozyme mutants to evaluate the contribution of U700 and other SLV loop residues to SLI recognition. To help interpret the kinetic data, we structurally characterized the SLV mutants by NMR spectroscopy and generated a three-dimensional model of the SLI/SLV complex by homology modeling with MC-Sym. We demonstrated that the mutation of U700 by A, C, or G does not significantly affect ribozyme activity, whereas deletion of U700 dramatically impairs this activity. The U700 backbone is likely important for SLI recognition, but does not appear to be required for either the structural integrity of the SLV loop or for direct interactions with SLI. Thus, deletion of U700 may affect other aspects of SLI recognition, such as magnesium ion binding and SLV loop dynamics. As part of our NMR studies, we developed a convenient assay based on detection of unusual (31)P and (15)N N7 chemical shifts to probe the formation of U-turn structures in RNAs. Our model of the SLI/SLV complex, which is compatible with biochemical data, leads us to propose novel interactions at the loop I/loop V interface.
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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".