Glycosidases: Functions, Families and Folds
Bibliographic record
Abstract
Abstract Glycosidases catalyse the hydrolysis of glycosidic linkages, thereby degrading oligosaccharides and glycoconjugates, the structurally most diverse class of biopolymers. These efficient and highly specific catalysts play important roles in biological processes thus a detailed knowledge of glycosidase function is invaluable for understanding and controlling diseases and for industrial applications. The classification of this huge class of enzymes into families on the basis of amino acid sequence has provided a highly valuable tool for the analysis of structure–function relationships. Furthermore, the steady increase in three‐dimensional structural information is revealing further evolutionary relationships between glycosidase families. In addition to the majority of glycosidases that act via the classical Koshland mechanisms, a growing number of such enzymes that use unusual mechanisms are being uncovered. This confluence of bioinformatics, structural and mechanistic studies has greatly advanced glycosidase engineering and the development of specific glycosidase inhibitors. Key Concepts: Classification of glycosidases by sequence similarity in a comprehensive database CAZy has proven to be an invaluable tool to analyse their structures and functions. Glycosidases adopt a variety of folds. The vast majority of glycosidases act via Koshland mechanisms with either retention or inversion of the anomeric configuration. Some glycosidases use unusual mechanisms employing hydration, elimination and/or redox steps. Detailed mechanistic understanding of glycosidase mechanism has allowed the engineering of glycosynthases and the development of specific inhibitors.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".