Revisiting the Effects of Sequence and Structure on the Hydrogen Bonding and π-Stacking Interactions in Nucleic Acids
Bibliographic record
Abstract
Calculated electron densities from PBE0/6-31+G(d,p) were analyzed with respect to the hydrogen bonding within a nucleic acid base pair and the π-stacking between sets of base pairs. From published X-ray crystallographic data, base pairs were isolated from a total of 11 DNA and RNA duplexes, and their experimental geometry was maintained throughout the analyses. Focusing solely on Watson-Crick base pairs, from the values of the electron density between interacting nuclei (at the bond critical points), we provide quantitative data on individual weak interactions. For hydrogen bonding, in addition to quantifying the scissoring effect in GC base pairs, the origin of the controversy around the relative stability of AT and AU base pairs is identified and resolved. Thus, it is illustrated how the conclusion as to their relative stability rests on the specific choice of oligonucleotides compared. For π-stacking, sequence effects for tandem AT base pairs are captured, quantified, and explained, and the greater sensitivity of GC, over AT, sequences to the rise parameter is established. The results presented here show that, from experimental geometries and their electron densities, previously determined effects of the sequence and structure of a duplex on the stabilizing interactions can be captured, quantified, and traced back to the geometry of the base pairs.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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".