Conformation/Tautomerization effect on the pK<sub>a</sub> values of lumazine and 6‐thienyllumazine
Bibliographic record
Abstract
Density functional theory [B3LYP/6‐311+G(d,p)] was used in combination with the conductor‐like polarizable continuum model (CPCM) solvation model to investigate the relative stability and site‐specific values of neutral and ionized tautomers of lumazine (LM) and 6‐thienylLM (TLM). Two types of populations should be taken into consideration when calculating the , tautomers, and conformers. The major tautomer of neutral LM in aqueous solution is 13‐LM (the 13 notation refers to the acidic protons being in positions 1 and 3 of LM) TLM has decreased acidity at N8 relative to LM. Further, the trans conformer of TLM is more acidic than cis. Similar to the case of LM, for TLM, N1 is more acidic than N3 in the uracil part. However, N8 is predicted to be a stronger acid than N1 for TLM. This acidity enhancement is essentially because of a specific stabilization of the anion when the thienyl group replaces H. Two factors are responsible for the acidity strength of N8: The thienyl ring upon deprotonation acts inductively as an electron‐withdrawing group, and the excess electron density is dispersed better when the system is trans and contains second‐row atoms. Accurate pKa calculation requires that all conformers/tautomers be included into the calculation. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".