Effects of Extending the Computational Model on DNA–Protein T-shaped Interactions: The Case of Adenine–Histidine Dimers
Bibliographic record
Abstract
The MP2/6-31G*(0.25) π-π or π(+)-π T-shaped (edge-to-face) interactions between neutral or protonated histidine and adenine were considered using computational models of varying size to determine the effects of the protein and DNA backbones on the preferred dimer structure and binding strength. The overall consequences of the backbones are reasonably subtle for the neutral adenine-histidine T-shaped dimers. Furthermore, the minor changes in the binding strengths of these dimers upon model extension arise from additional (attractive) backbone-π (bb-π) contacts and changes in the preferred π-π orientations, which is verified by the quantum theory of atoms in molecules (QTAIM). Since the binding strength of the extended dimer equals the sum of the individual backbone-π and π-π contributions, the π-π component is not appreciably affected by polarization of the ring upon inclusion of the biological backbone. In contrast, the larger effect of the backbone on the protonated histidine dimers cannot simply be predicted as the sum of changes in the π-π and bb-π components regardless of the dimer type or model. This suggests, and QTAIM qualitatively supports, that the magnitude of the π(+)-π contribution changes, which is likely due to alterations in the electrostatic landscape of the monomer rings upon inclusion of the biological backbone that largely affect T-shaped dimers. These findings differ from those previously reported for (neutral) π-π stacked and (metallic) cation-π interactions, which highlights the distinct properties of each (π-π, π(+)-π, and cation-π) classification of noncovalent interaction. Furthermore, these results emphasize the importance of considering backbone-π interactions when analyzing contacts that appear in experimental crystal structures and cautions the use of truncated models when evaluating the magnitude of the π(+)-π contribution present in large biological complexes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".