Insights into the Catalytic Mechanism of Coral Allene Oxide Synthase: A Dispersion Corrected Density Functional Theory Study
Bibliographic record
Abstract
In this present work the mechanism by which cAOS catalyzes the formation of allene oxide from its hydroperoxy substrate was computationally investigated by using a DFT-chemical cluster approach. In particular, the effects of dispersion interactions and DFT functional choice (M06, B3LYP, B3LYP*, and BP86), as well as the roles of multistate reactivity and the tyrosyl proximal ligand, were examined. It is observed that the computed relative free energies of stationary points along the overall pathway are sensitive to the choice of DFT functional, while the mechanism obtained is generally not. Large reductions in relative free energies for stationary points along the pathway (compared to the initial reactant complex) of on average 46.3 and 97.3 kJ mol(-1) for the doublet and quartet states, respectively, are observed upon going from the M06 to BP86 functional. From results obtained by using the B3LYP* method, well-tested previously on heme-containing systems, the mechanism of cAOS appears to occur with considerably higher Gibbs free energies than that for the analogous pathway in pAOS, possibly due to the presence of a ligating tyrosyl residue in cAOS. Furthermore, at the IEFPCM-B3LYP*/6-311+G(2df,p)//B3LYP/BS1 level of theory the inclusion of dispersion effects leads to the suggestion that the overall mechanism of cAOS could occur without the need for spin inversion.
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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) | 0.001 | 0.001 |
| 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) | 0.002 | 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".