Influence of the Number, Nature and Position of Methyl Posttranscriptional Modifications on Nucleobase Stacking in RNA
Bibliographic record
Abstract
Abstract DFT calculations are employed to quantify the influence of the presence, number, nature, and position of posttranscriptional methylation on stacking strength of RNA bases. We carry out detailed potential energy scans of the variation in stacking energies with characteristic geometrical parameters in three categories of forty stacked dimers – canonical base homodimers (N||N), methylated base homodimers (mN||mN) and heterodimers of canonical bases and methylated counterparts (N||mN). Our analysis reveals that neutral methylation invariably enhances the stacking of bases. Further, N||mN stacking is stronger than mN||mN stacking and charged N||mN exhibit strongest stacking among all dimers. This indicates that methylations greatly enhance stacking when dispersed in RNA sequences containing identical bases. Comparison of stacks involving singly‐ and doubly‐methylated purines reveal that incremental methylation enhances the stacking in neutral dimers. Although methylation at the carbon position of neutral pyrimidine dimers greatly enhances the stacking, methylation on the 5‐membered ring imparts better stacking compared to methylation on the 6‐membered ring in adenine dimers. However, methylation at the ring nitrogen (N 1 ) provides better stacking than the amino group (N 2 ) in guanine dimers. Our results thus highlight subtle structural effects of methylation on RNA base stacking and will enhance our understanding of the physicochemical principles of RNA structure and dynamics.
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".