Faculty Opinions recommendation of Time-resolved NMR methods resolving ligand-induced RNA folding at atomic resolution.
Bibliographic record
Abstract
Structural transitions of RNA between alternate conformations with similar stabilities are associated with important aspects of cellular function. Few techniques presently exist that are capable of monitoring such transitions and thereby provide insight into RNA dynamics and function at atomic resolution. Riboswitches are found in the 5'-UTR of mRNA and control gene expression through structural transitions after ligand recognition. A time-resolved NMR strategy was established in conjunction with laser-triggered release of the ligand from a photocaged derivative in situ to monitor the hypoxanthine-induced folding of the guanine-sensing riboswitch aptamer domain of the Bacillus subtilis xpt-pbuX operon at atomic resolution. Combining selective isotope labeling of the RNA with NMR filter techniques resulted in significant spectral resolution and allowed kinetic analysis of the buildup rates for individual nucleotides in real time. Three distinct kinetic steps associated with the ligand-induced folding were delineated. After initial complex encounter the ligand-binding pocket is formed and results in subsequent stabilization of a remote long-range loop-loop interaction. Incorporation of NMR data into experimentally restrained molecular dynamics simulations provided insight into the RNA structural ensembles involved during the conformational transition. PMID: 17895388
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.035 |
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".