Effects of the biological backbone on DNA–protein stacking interactions
Bibliographic record
Abstract
The pi-pi stacking (face-to-face) interactions between the five natural DNA or RNA nucleobases and the four aromatic amino acids were compared using three different types of dimers: (1) a truncated nucleoside (nucleobase) stacked with a truncated amino acid; (2) a truncated nucleoside (nucleobase) stacked with an extended amino acid; and (3) a nucleoside (extended nucleobase) stacked with a truncated amino acid. Systematic (MP2/6-31G*(0.25)) potential energy surface scans reveal important information about the effects of the deoxyribose sugar and protein backbone on the structure and binding energy between truncated nucleobase and amino acid models that are typically implemented in the literature. Most notably, electrostatic and steric interactions arising from the bulkiness of the biological backbones can change the preferred relative orientations of DNA and protein pi-systems. More importantly, the protein backbone can strengthen the stacking energy (by up to 10 kJ mol(-1)), while the deoxyribose moiety can strengthen or weaken the stacking interaction depending on the positioning of the amino acid relative to the sugar residue. These effects are likely due to additional interactions between the amino acid or nucleobase ring and the backbone in the extended monomer rather than significant changes in the properties of the biological pi-systems upon model extension. Since the present work reveals that all calculated DNA-protein stacking interactions are significant and approach the strength of other noncovalent interactions between biomolecules, both pi-pi and backbone-pi interactions must be considered when attempting to gain a complete picture of DNA-protein binding.
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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 | 0.000 |
| 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".