Functional screening pipeline to uncover laccase-like multicopper oxidase enzymes that transform industrial lignins
Bibliographic record
Abstract
Laccase-like multicopper oxidases are recognized for their potential to alter the reactivity of lignins for application in value-added products. Typically, model compounds are employed to discover such enzymes; however, they do not represent the complexity of industrial lignin substrates. In this work, a screening pipeline was developed to test enzymes simultaneously on model compounds and industrial lignins. A total of 12 lignin-active fungal multicopper oxidases were discovered, including 9 enzymes active under alkaline conditions (pH 11.0). Principal component analysis revealed the poor ability of model compounds to predict enzyme performance on industrial lignins. Additionally, sequence similarity analyses grouped these enzymes with Auxiliary Activity-1 sub-families with few previously characterized members, underscoring their taxonomic novelty. Correlation between the lignin-activity of these enzymes and their taxonomic origin, however, was not observed. These are critical insights to bridge the gap between enzyme discovery and application for industrial lignin valorization.
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How this classification was reachedexpand
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".