4′-<i>C</i>-Methoxy-2′-deoxy-2′-fluoro Modified Ribonucleotides Improve Metabolic Stability and Elicit Efficient RNAi-Mediated Gene Silencing
Bibliographic record
Abstract
We designed novel 4′-modified 2′-deoxy-2′-fluorouridine (2′-F U) analogues with the aim to improve nuclease resistance and potency of therapeutic siRNAs by introducing 4′- C -methoxy (4′-OMe) as the alpha (C4′α) or beta (C4′β) epimers. The C4′α epimer was synthesized by a stereoselective route in six steps; however, both α and β epimers could be obtained by a nonstereoselective approach starting from 2′-F U. 1 H NMR analysis and computational investigation of the α-epimer revealed that the 4′-OMe imparts a conformational bias toward the North - East sugar pucker, due to intramolecular hydrogen bonding and hyperconjugation effects. The α-epimer generally conceded similar thermal stability as unmodified nucleotides, whereas the β-epimer led to significant destabilization. Both 4′-OMe epimers conferred increased nuclease resistance, which can be explained by the close proximity between 4′-OMe substituent and the vicinal 5′- and 3′-phosphate group, as seen in the X-ray crystal structure of modified RNA. siRNAs containing several C4′α-epimer monomers in the sense or antisense strands triggered RNAi-mediated gene silencing with efficiencies comparable to that of 2′-F U.
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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".