Systematic analysis of the interactions driving small molecule–RNA recognition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RNA molecules are becoming an important target class in drug discovery. However, the principles for designing RNA-binding small molecules are yet to be fully uncovered. In this study, we examined the Protein Data Bank (PDB) to highlight privileged interactions underlying small molecule-RNA recognition. By comparing this analysis with previously determined small molecule-protein interactions, we find that RNA recognition is driven mostly by stacking and hydrogen bonding interactions, while protein recognition is instead driven by hydrophobic effects. Furthermore, we analyze patterns of interactions to highlight potential strategies to tune RNA recognition, such as stacking and cation-π interactions that favor purine and guanine recognition, and note an unexpected paucity of backbone interactions, even for cationic ligands. Collectively, this work provides further understanding of RNA-small molecule interactions that may inform the design of small molecules targeting RNA.
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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 | 0.001 |
| 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 it