Single-molecule force spectroscopy of the add adenine riboswitch relates folding to regulatory mechanism
Bibliographic record
Abstract
Riboswitches regulate gene expression via ligand binding to an aptamer domain which induces conformational changes in a regulatory expression platform. By unfolding and refolding single add adenine riboswitch molecules in an optical trap, an integrated picture of the folding was developed and related to the regulatory mechanism. Force-extension curves (FECs) and constant-force folding trajectories measured on the aptamer alone revealed multiple partially-folded states, including several misfolded states not on the native folding pathway. All states were correlated to key structural components and interactions within hierarchical folding pathways. FECs of the full-length riboswitch revealed that the thermodynamically stable conformation switches upon ligand binding from a structure repressing translation to one permitting it. Along with rapid equilibration of the two structures in the absence of adenine, these results support a thermodynamically-controlled regulatory mechanism, in contrast with the kinetic control of the closely-related pbuE adenine riboswitch. Comparison of the folding of these riboswitches revealed many similarities arising from shared structural features but also essential differences related to their different regulatory mechanisms.
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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) | 0.001 | 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".