“ChopNSpice,” a Mass Spectrometric Approach That Allows Identification of Endogenous Small Ubiquitin-like Modifier-conjugated Peptides
Bibliographic record
Abstract
Conjugation of small ubiquitin-like modifier (SUMO) to substrates is involved in a large number of cellular processes. Typically, SUMO is conjugated to lysine residues within a SUMO consensus site; however, an increasing number of proteins are sumoylated on non-consensus sites. To appreciate the functional consequences of sumoylation, the identification of SUMO attachment sites is of critical importance. Discovery of SUMO acceptor sites is usually performed by a laborious mutagenesis approach or using MS. In MS, identification of SUMO acceptor sites in higher eukaryotes is hampered by the large tryptic fragments of SUMO1 and SUMO2/3. MS search engines in combination with known databases lack the possibility to search MSMS spectra for larger modifications, such as sumoylation. Therefore, we developed a simple and straightforward database search tool ("ChopNSpice") that successfully allows identification of SUMO acceptor sites from proteins sumoylated in vivo and in vitro. By applying this approach we identified SUMO acceptor sites in, among others, endogenous SUMO1, SUMO2, RanBP2, and Ubc9.
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 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 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.004 | 0.003 |
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".