Direct Spectrophotometric Assay of Laccase Using Diazo Derivatives of Guaiacol
Bibliographic record
Abstract
Laccase (EC 1.10.3.2) is a widespread cuproenzyme able to oxidize various types of phenols and similar aromatic compounds through a one-electron transfer mechanism. The enzyme has already found its way into the market as a biocatalyst. Because of its ability to be paired by electron mediators, the expectation for employing laccases in versatile processes is very high. There are a few spectrophotometric methods for assaying the laccase activity; however, all of them are based on the formation of product(s) resulting from the enzymatic and inevitable succeeding chemical reactions. Use of diazo derivatives of guaiacol (DdG) was developed as a new spectrophotometric method based on substrate depletion allowing direct assessment of enzyme activity has been introduced. This method allows accurate comprehensive kinetic studies of laccases and provides reliable information about the quality of docking of different substrates or one substrate to the active sites of different laccases. Using this method, the kinetic parameters of various DdG carrying different electron donating and withdrawing substituents were used to assay laccase from Neurospora crassa. 2-Methoxy-4-[(4-phenyl)azo]-phenol (K(m) = 93.5 μM and V = 1.98 μM/min) was identified as an appropriate substrate for the accurate and routine spectrophotometric based assay of laccases.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".