Extended Weak Bonding Interactions in DNA: π-Stacking (Base−Base), Base−Backbone, and Backbone−Backbone Interactions
Bibliographic record
Abstract
We report on several weak interactions in nucleic acids, which, collectively, can make a nonnegligible contribution to the structure and stability of these molecules. Fragments of DNA were obtained from previously determined accurate experimental geometries and their electron density distributions calculated using density functional theory (DFT). The electron densities were analyzed topologically according to the quantum theory of atoms in molecules (AIM). A web of closed-shell bonding interactions is shown to connect neighboring base pairs in base-pair duplexes and in dinuleotide steps. This bonding underlies the well-known pi-stacking interaction between adjacent nucleic acid bases and is characterized topologically for the first time. Two less widely appreciated modes of weak closed-shell interactions in nucleic acids are also described: (i) interactions between atoms in the bases and atoms belonging to the backbone (base-backbone) and (ii) interactions among atoms within the backbone itself (backbone-backbone). These interactions include hydrogen bonding, dihydrogen bonding, hydrogen-hydrogen bonding, and several other weak closed-shell X-Y interactions (X, Y = O, N, C). While each individual interaction is very weak and typically accompanied by perhaps 0.5-3 kcal/mol, the sum total of these interactions is postulated to play a role in stabilizing the structure of nucleic acids. The Watson-and-Crick hydrogen bonding is also characterized in detail at the experimental geometries as a prelude to the discussion of the modes of interactions listed in the title.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".