Solution Structure Determination and Biophysical Studies of 7SK RNP and 7SL SRP RNAs
Bibliographic record
Abstract
Small noncoding RNAs perform integral roles in eukaryotic lifecycles, particularly the 7SK snRNA, which is responsible for RNA Polymerase II transcription modulation and progression when interacting with P-TEFb, and the 7SL RNA involved in Signal Recognition Particle mediation of co-translational activities of endoplasmic reticulum-bound proteins. These RNAs retain important secondary structures that interact with proteins involved in regulating transcription and translation. RNA-protein interactions involving the RNA stem-loops have been previously characterised using chemical probing techniques, Cryo-Electron Microscopy, and Nuclear Magnetic Resonance. However, complete three-dimensional structures of the full-length 7SK and 7SL have not been resolved, limiting our understanding of these RNAs’ tertiary landscapes and mechanisms. Our study bridges this gap in knowledge by using Small-Angle X-ray Scattering and coarse-grained computational modelling of previously determined secondary structures through SimRNA to produce full-sequence, three-dimensional atomistic models of both 7SK and 7SL RNAs. We employed size exclusion chromatography coupled with light scattering and Circular Dichroism Spectroscopy to verify RNA size and compare previously identified secondary structures in solution. We additionally employed all-atom, structure-based potential simulations to generate optimised models within our calculated SAXS envelopes. 7SK’s total morphology is thus presented as a highly versatile structure whose well-defined stem-loops interact with each other in three-dimensional space. 7SL RNA is presented as a tightly wound and somewhat rigid structure, with significant base-pairing features in its Alu domain, whereupon it forms likely scaffolds for signal recognition peptide formation.
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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".