Density Functional Theory Analysis of Stereoelectronic Properties of Cobalamins
Bibliographic record
Abstract
Density functional theory (DFT) is applied to the calculation of the steric and electronic factors which might affect the Co−C R bond activation in coenzyme B 12 . The six-coordinate cobalamins (B−[Co III (corrin)]−R, models of coenzyme B 12 ) include the actual corrin macroring as the equatorial ligand and imidazole (Im), dimethylbenzimidazole (DBI) or water (H 2 O), as the α-trans ligand (B). The β axial ligand (R) represents a series of alkyl groups with different steric bulkiness ranging from −C⋮N, −C⋮CH through methyl, ethyl, isopropyl, tert -butyl to 5‘-deoxy-5‘-adenosyl. Each trans ligand (Im, DBI or H 2 O) produces a positive correlation of the Co−C R and Co−N B bond lengths. The increasing complexity of the R group leads to two major structural correlations: a positive correlation between the Co−C R and Co−N B bond lengths and an inverse correlation between the Co−C R bond length and the flatness of the corrin ring. It is shown that stereoelectronic properties of cobalamins can only be explained on the basis of electronic considerations. Moreover, electron donation from axial ligands to the cobalt atom either by electron donating substituents or by a properly oriented external electric field caused by external electric charges is argued to be the main trigger for the activation of the Co−C R bond.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".