An improved SUMmOn‐based methodology for the identification of ubiquitin and ubiquitin‐like protein conjugation sites identifies novel ubiquitin‐like protein chain linkages
Bibliographic record
Abstract
Ubiquitin (Ub) and the ubiquitin-like proteins (Ubls) comprise a remarkable assortment of polypeptides that are covalently conjugated to target proteins (or other biomolecules) to modulate their intracellular localization, half-life, and/or activity. Identification of Ub/Ubl conjugation sites on a protein of interest can thus be extremely important for understanding how it is regulated. While MS has become a powerful tool for the study of many classes of PTMs, the identification of Ub/Ubl conjugation sites presents a number of unique challenges. Here, we present an improved Ub/Ubl conjugation site identification strategy, utilizing SUMmOn analysis and an additional protease (lysyl endopeptidase C), as a complement to standard approaches. As compared with standard trypsin proteolysis-database search protocols alone, the addition of SUMmOn analysis can (i) identify Ubl conjugation sites that are not detected by standard database searching methods, (ii) better preserve Ub/Ubl conjugate identity, and (iii) increase the number of identifications of Ub/Ubl modifications in lysine-rich protein regions. Using this methodology, we characterize for the first time a number of novel Ubl linkages and conjugation sites, including alternative yeast (K54) and mammalian small ubiquitin-related modifier (SUMO) chain (SUMO-2 K42, SUMO-3 K41) assemblies, as well as previously unreported NEDD8 chain (K27, K33, and K54) topologies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".