Incorporation of Manganese Complexes into Xylanase: New Artificial Metalloenzymes for Enantioselective Epoxidation
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Bibliographic record
Abstract
Here we report the best artificial metalloenzyme to date for the selective oxidation of aromatic alkenes; it was obtained by noncovalent insertion of Mn(III)-meso-tetrakis(p-carboxyphenyl)porphyrin [Mn(TpCPP), 1-Mn] into a host protein, xylanase 10A from Streptomyces lividans (Xln10A). Two metallic complexes-N,N'-ethylene bis(2-hydroxybenzylimine)-5,5'-dicarboxylic acid Mn(III) [(Mn-salen), 2-Mn] and 1-Mn-were associated with Xln10A, and the two hybrid biocatalysts were characterised by UV-visible spectroscopy, circular dichroism and molecular modelling. Only the artificial metalloenzyme based on 1-Mn and Xln10A was studied for its catalytic properties in the oxidation of various substituted styrene derivatives by KHSO(5): after optimisation, the 1-Mn-Xln10A artificial metalloenzyme was able to catalyse the oxidation of para-methoxystyrene by KHSO(5) with a 16 % yield and the best enantioselectivity (80 % in favour of the R isomer) ever reported for an artificial metalloenzyme.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it