A Multi-Scale Computational Study on the Mechanism of Streptococcus pneumoniae Nicotinamidase (SpNic)
Bibliographic record
Abstract
Nicotinamidase (Nic) is a key zinc-dependent enzyme in NAD metabolism that catalyzes the hydrolysis of nicotinamide to give nicotinic acid. A multi-scale computational approach has been used to investigate the catalytic mechanism, substrate binding and roles of active site residues of Nic from Streptococcus pneumoniae (SpNic). In particular, density functional theory (DFT), molecular dynamics (MD) and ONIOM quantum mechanics/molecular mechanics (QM/MM) methods have been employed. The overall mechanism occurs in two stages: (i) formation of a thioester enzyme-intermediate (IC2) and (ii) hydrolysis of the thioester bond to give the products. The polar protein environment has a significant effect in stabilizing reaction intermediates and in particular transition states. As a result, both stages effectively occur in one step with Stage 1, formation of IC2, being rate limiting barrier with a cost of 53.5 kJ·mol-1 with respect to the reactant complex, RC. The effects of dispersion interactions on the overall mechanism were also considered but were generally calculated to have less significant effects with the overall mechanism being unchanged. In addition, the active site lysyl (Lys103) is concluded to likely play a role in stabilizing the thiolate of Cys136 during the reaction.
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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 | 0.000 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".