Sequence-dependent conformational preferences of disordered single-stranded RNA
Bibliographic record
Abstract
Disordered single-stranded RNA (ssRNA) molecules, like their well-folded counterparts, have crucial functions that depend on their structures. However, since native ssRNAs constitute a highly heterogeneous conformer population, their structural characterization poses challenges. One important question regards the role of sequence in influencing ssRNA structure. Here, we adopt an integrated approach that combines solution-based measurements, including small-angle X-ray scattering (SAXS) and Förster resonance energy transfer (FRET), with experimentally guided all-atom molecular dynamics (MD) simulations, to construct structural ensembles of a 30-nucleotide RNA homopolymer (rU30) and a 30-nucleotide RNA heteropolymer with an A-/C-rich sequence. We compare the size, shape, and flexibility of the two different ssRNAs. While the average properties align with polymer-physics descriptions of flexible polymers, we discern distinct, sequence-dependent conformations at the molecular level that demand a more detailed representation than provided by polymer models. These findings emphasize the role of sequence in shaping the overall properties of ssRNA.
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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 | 0.000 |
| 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 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".