The Hydrogen Bonding Properties of Cytosine: A Computational Study of Cytosine Complexed with Hydrogen Fluoride, Water, and Ammonia
Bibliographic record
Abstract
Density functional theory is used to study the hydrogen bonding pattern in cytosine, which does not contain alternating proton donor and acceptor sites and therefore is unique compared with the other pyrimidines. Complexes between various small molecules (HF, H(2)O, and NH(3)) and four main binding sites in (neutral and (N1) anionic) cytosine are considered. Two complexes (O2(N1) and N3(N4)) involve neighboring cytosine proton acceptor and donor sites, which leads to cooperative interactions and bidendate hydrogen bonds. The third (less stable) complex (N4) involves a single cytosine donor. The final (O2-N3) complex involves two cytosine proton acceptors, which leads to an anticooperative hydrogen bonding pattern for H(2)O and NH(3). On the neutral surface, the anticooperative O2-N3 complex is less stable than those involving bidentate hydrogen bonds, and the H(2)O complex cannot be characterized when diffuse functions are included in the (6-31G(d,p)) basis set. On the contrary, the anionic O2-N3 structure is the most stable complex, while the HF and H(2)O N3(N4) complexes cannot be characterized with diffuse functions. B3LYP and MP2 potential energy surface scans are used to consider the relationship between the water N3(N4) and O2-N3 complexes. These calculations reveal that diffuse functions reduce the conversion barrier between the two complexes on both the neutral and anionic surfaces, where the reduction leads to a (O2-N3) energy plateau on the neutral surface and complete (N3(N4)) complex destabilization on the anionic surface. From these complexes, the effects of hydrogen bonds on the (N1) acidity of cytosine are determined, and it is found that the trends in the effects of hydrogen bonds on the (N1) acidity are similar for all pyrimidines.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".