Analysis of the galactomannan binding ability of β-mannosidases, BtMan2A and CmMan5A, regarding their activity and synergism with a β-mannanase
Bibliographic record
Abstract
Both β-mannanases and β-mannosidases are required for mannan-backbone degradation into mannose. In this study, two β-mannosidases of glycoside hydrolase (GH) families 2 (BtMan2A) and 5 (CmMan5A) were evaluated for their substrate specificities and galactomannan binding ability. BtMan2A preferred short manno-oligomers, while CmMan5A preferred longer ones; DP >2, and galactomannans. BtMan2A displayed irreversible galactomannan binding, which was pH-dependent, with higher binding observed at low pH, while CmMan5A had limited binding. Docking and molecular dynamics (MD) simulations showed that BtMan2A galactomannan binding was stronger under acidic conditions (-8.4 kcal/mol) than in a neutral environment (-7.6 kcal/mol), and the galactomannan ligand was more unstable under neutral conditions than acidic conditions. Qualitative surface plasmon resonance (SPR) experimentally confirmed the reduced binding capacity of BtMan2A at pH 7. Finally, synergistic β-mannanase to β-mannosidase (BtMan2A or CmMan5A) ratios required for maximal galactomannan hydrolysis were determined. All CcManA to CmMan5A combinations were synergistic (≈1.2-fold), while combinations of CcManA with BtMan2A (≈1.0-fold) yielded no hydrolysis improvement. In conclusion, the low specific activity of BtMan2A towards long and galactose-containing oligomers and its non-catalytic galactomannan binding ability led to no synergy with the mannanase, making GH2 mannosidases ineffective for use in cocktails for mannan degradation.
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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) | 0.000 | 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".