Enhanced Polysaccharide Binding and Activity on Linear β-Glucans through Addition of Carbohydrate-Binding Modules to Either Terminus of a Glucooligosaccharide Oxidase
Bibliographic record
Abstract
The gluco-oligosaccharide oxidase from Sarocladium strictum CBS 346.70 (GOOX) is a single domain flavoenzyme that favourably oxidizes gluco- and xylo- oligosaccharides. In the present study, GOOX was shown to also oxidize plant polysaccharides, including cellulose, glucomannan, β-(1→3,1→4)-glucan, and xyloglucan, albeit to a lesser extent than oligomeric substrates. To improve GOOX activity on polymeric substrates, three carbohydrate binding modules (CBMs) from Clostridium thermocellum, namely CtCBM3 (type A), CtCBM11 (type B), and CtCBM44 (type B), were separately appended to the amino and carboxy termini of the enzyme, generating six fusion proteins. With the exception of GOOX-CtCBM3 and GOOX-CtCBM44, fusion of the selected CBMs increased the catalytic activity of the enzyme (kcat) on cellotetraose by up to 50%. All CBM fusions selectively enhanced GOOX binding to soluble and insoluble polysaccharides, and the immobilized enzyme on a solid cellulose surface remained stable and active. In addition, the CBM fusions increased the activity of GOOX on soluble glucomannan by up to 30% and on insoluble crystalline as well as amorphous cellulose by over 50%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.001 | 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".