Orthogonal Active-Site Labels for Mixed-Linkage endo-β-Glucanases
Bibliographic record
Abstract
Small molecule irreversible inhibitors are valuable tools for determining catalytically important active-site residues and revealing key details of the specificity, structure, and function of glycoside hydrolases (GHs). β-glucans that contain backbone β(1,3) linkages are widespread in nature, e.g., mixed-linkage β(1,3)/β(1,4)-glucans in the cell walls of higher plants and β(1,3)glucans in yeasts and algae. Commensurate with this ubiquity, a large diversity of mixed-linkage endoglucanases (MLGases, EC 3.2.1.73) and endo-β(1,3)-glucanases (laminarinases, EC 3.2.1.39 and EC 3.2.1.6) have evolved to specifically hydrolyze these polysaccharides, respectively, in environmental niches including the human gut. To facilitate biochemical and structural analysis of these GHs, with a focus on MLGases, we present here the facile chemo-enzymatic synthesis of a library of active-site-directed enzyme inhibitors based on mixed-linkage oligosaccharide scaffolds and N -bromoacetylglycosylamine or 2-fluoro-2-deoxyglycoside warheads. The effectiveness and irreversibility of these inhibitors were tested with exemplar MLGases and an endo-β(1,3)-glucanase. Notably, determination of inhibitor-bound crystal structures of a human-gut microbial MLGase from Glycoside Hydrolase Family 16 revealed the orthogonal labeling of the nucleophile and catalytic acid/base residues with homologous 2-fluoro-2-deoxyglycoside and N -bromoacetylglycosylamine inhibitors, respectively. We anticipate that the selectivity of these inhibitors will continue to enable the structural and mechanistic analyses of β-glucanases from diverse sources and protein families.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".