Recurrent RNA motifs as probes for studying RNA-protein interactions in the ribosome
Bibliographic record
Abstract
To understand how the nucleotide sequence of ribosomal RNA determines its tertiary structure, we developed a new approach for identification of those features of rRNA sequence that are responsible for formation of different short- and long-range interactions. The approach is based on the co-analysis of several examples of a particular recurrent RNA motif. For different cases of the motif, we design combinatorial gene libraries in which equivalent nucleotide positions are randomized. Through in vivo expression of the designed libraries we select those variants that provide for functional ribosomes. Then, analysis of the nucleotide sequences of the selected clones would allow us to determine the sequence constraints imposed on each case of the motif. The constraints shared by all cases are interpreted as providing for the integrity of the motif, while those ones specific for individual cases would enable the motif to fit into the particular structural context. Here we demonstrate the validity of this approach for three examples of the so-called along-groove packing motif found in different parts of ribosomal RNA.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".