A subfamily roadmap of the evolutionarily diverse glycoside hydrolase family 16 (GH16)
Bibliographic record
Abstract
Glycoside hydrolase family (GH) 16 comprises a large and taxonomically diverse family of glycosidases and transglycosidases that adopt a common -jelly-roll fold and are active on a range of terrestrial and marine polysaccharides. Presently, broadly insightful sequence-function correlations in GH16 are hindered by a lack of a systematic subfamily structure. To fill this gap, we have used a highly scalable protein sequence similarity network analysis to delineate nearly 23,000 GH16 sequences into 23 robust subfamilies, which are strongly supported by hidden Markov model and maximum likelihood molecular phylogenetic analyses. Subsequent evaluation of over 40 experimental three-dimensional structures has highlighted key tertiary structural differences, predominantly manifested in active-site loops, that dictate substrate specificity across the GH16 evolutionary landscape. As for other large GH families (i.e. GH5, GH13, and GH43), this new subfamily classification provides a roadmap for functional glycogenomics that will guide future bioinformatics and experimental structurefunction analyses. The GH16 subfamily classification is publicly available in the CAZy database. The sequence similarity network workflow used here, SSNpipe, is freely available from GitHub.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.017 |
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".