The Evolution and Functional Diversification of the Deubiquitinating Enzyme Superfamily
Bibliographic record
Abstract
Ubiquitin and ubiquitin-like molecules are attached to and removed from cellular proteins in a dynamic and highly regulated manner. Deubiquitinating enzymes are critical to this process, and the genetic catalogue of deubiquitinating enzymes expanded greatly over the course of evolution. Extensive functional redundancy has been noted among the 93 members of the human deubiquitinating enzyme (DUB) superfamily. This is especially true of genes that were generated by duplication (termed paralogs) as they often retain considerable sequence similarity. Because complete redundancy in systems should be eliminated by selective pressure, we theorized that many overlapping DUBs must have significant and unique spatiotemporal roles that can be evaluated in an evolutionary context. We have determined the evolutionary history of the entire class of deubiquitinating enzymes, including the sequence and means of duplication for all paralogous pairs. To establish their uniqueness, we have investigated cell-type specificity in developmental and adult contexts, and have investigated the coemergence of substrates from the same duplication events. Our analysis has revealed examples of DUB gene subfunctionalization, neofunctionalization, and nonfunctionalization.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".