Differential stability of 2′F-ANA•RNA and ANA•RNA hybrid duplexes: roles of structure, pseudohydrogen bonding, hydration, ion uptake and flexibility
Bibliographic record
Abstract
Hybrids of RNA with arabinonucleic acids 2'F-ANA and ANA have very similar structures but strikingly different thermal stabilities. We now present a thorough study combining NMR and other biophysical methods together with state-of-the-art theoretical calculations on a fully modified 10-mer hybrid duplex. Comparison between the solution structure of 2'F-ANA*RNA and ANA*RNA hybrids indicates that the increased binding affinity of 2'F-ANA is related to several subtle differences, most importantly a favorable pseudohydrogen bond (2'F-purine H8) which contrasts with unfavorable 2'-OH-nucleobase steric interactions in the case of ANA. While both 2'F-ANA and ANA strands maintained conformations in the southern/eastern sugar pucker range, the 2'F-ANA strand's structure was more compatible with the A-like structure of a hybrid duplex. No dramatic differences are found in terms of relative hydration for the two hybrids, but the ANA*RNA duplex showed lower uptake of counterions than its 2'F-ANA*RNA counterpart. Finally, while the two hybrid duplexes are of similar rigidities, 2'F-ANA single strands may be more suitably preorganized for duplex formation. Thus the dramatically increased stability of 2'F-ANA*RNA and ANA*RNA duplexes is caused by differences in at least four areas, of which structure and pseudohydrogen bonding are the most important.
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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".