Effects of Hydrogen Bonding on the Acidity of Adenine, Guanine, and Their 8-Oxo Derivatives
Bibliographic record
Abstract
Complexes between ammonia, water, or hydrogen fluoride and adenine, guanine, or their 8-oxo derivatives are investigated using density-functional theory. The binding strengths of the neutral and (N9) anionic complexes are considered for a variety of purine binding sites. The effects of hydrogen-bonding interactions on the (N9) acidity of the purine derivatives are considered as a function of the molecule bound and the binding site. It is found that hydrogen-bonding interactions with one molecule can increase the acidity of purine derivatives by up to 60 kJ mol(-1). The (calculated) simultaneous effects of up to four molecules on the acidity of the purine derivatives are also considered. Our data suggest that the effects of more than one molecule on the acidity of the purines are generally less than the sum of the individual (additive) effects, where the magnitude of the deviation from additivity increases with the number, as well as the acidity, of molecules bound. Nevertheless, the increase in the acidity due to additional hydrogen-bonding interactions is significant, where the effect of two, three, or four hydrogen-bonding interactions can be as large as approximately 95, 115, and 130 kJ mol(-1), respectively. The present study provides a greater fundamental understanding of hydrogen-bonding interactions involving the natural purines, as well as those generated through oxidative DNA damage, which may aid the understanding of important biological processes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".