Enzymatic Synthesis of RNAs Capped with Nucleotide Analogues Reveals the Molecular Basis for Substrate Selectivity of RNA Capping Enzyme: Impacts on RNA Metabolism
Bibliographic record
Abstract
RNA cap binding proteins have evolved to specifically bind to the N7-methyl guanosine cap structure found at the 5' ends of eukaryotic mRNAs. The specificity of RNA capping enzymes towards GTP for the synthesis of this structure is therefore crucial for mRNA metabolism. The fact that ribavirin triphosphate was described as a substrate of a viral RNA capping enzyme, raised the possibility that RNAs capped with nucleotide analogues could be generated in cellulo. Owing to the fact that this prospect potentially has wide pharmacological implications, we decided to investigate whether the active site of the model Paramecium bursaria Chlorella virus-1 RNA capping enzyme was flexible enough to accommodate various purine analogues. Using this approach, we identified several key structural determinants at each step of the RNA capping reaction and generated RNAs harboring various different cap analogues. Moreover, we monitored the binding affinity of these novel capped RNAs to the eIF4E protein and evaluated their translational properties in cellulo. Overall, this study establishes a molecular rationale for the specific selection of GTP over other NTPs by RNA capping enzyme It also demonstrates that RNAs can be enzymatically capped with certain purine nucleotide analogs, and it also describes the impacts of modified RNA caps on specific steps involved in mRNA metabolism. For instance, our results indicate that the N7-methyl group of the classical N7-methyl guanosine cap is not always indispensable for binding to eIF4E and subsequently for translation when compensatory modifications are present on the capped residue. Overall, these findings have important implications for our understanding of the molecular determinants involved in both RNA capping and RNA metabolism.
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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".