Hydrogen-Bond Mediated Catalysis: The Aminolysis of 6-Chloropyrimidine as Catalyzed by Derivatives of Uracil
Bibliographic record
Abstract
The aminolysis of 6-chloropyrimidine and 2-amino-6-chloropyrimidine has been examined by using density functional theory. Relative to the aminolysis of 6-chloropyrimidine, the addition of an electron-donating NH(2) group to C(2) increases the barrier to aminolysis, indicating that the third hydrogen bond does not play a catalytic role but introduces additional rigidity into the system. However, the computations suggest that there is an interesting correlation between the barrier to aminolysis and the proton affinity of the species that interacts with the incoming NH(3). To extend the range of proton affinities, the aminolysis of 6-chloropyrimidine was examined by using fluoro, imine, and thioketo derivatives of the uracil-derived bases. The proton affinity of the moiety that hydrogen bonds with NH(3) is decreased by fluoro substitution, and thus the aminolysis barriers are increased. Similarly, imine substitution enhances the PA of the moiety, which is reflected in a decrease in the aminolysis barriers. The same correlation exists for the thioketo-derived bases, whose PAs are intermediate between the fluoro and imine derivatives. Thus, the aminolysis of 6-chloropryimidine and 2-amino-6-chloropyrimidine demonstrates the importance of a well-chosen proton acceptor and the catalytic possibilities associated with the formation of multiple hydrogen bonds.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".