Solution NMR structure and NMR-based molecular backbone dynamics of Ub <sup>KEKS</sup> : a ubiquitin variant encoded in the UBB4 pseudogene with emerging specific and new functions
Bibliographic record
Abstract
Recently, proteomics analyses using databases of unannotated ORFs revealed that ubiquitin (Ub) variants can be encoded and expressed from pseudogenes. One such pseudogene, UBBP4, produces Ub KEKS , which contains four substitutions (Q2K, K33E, Q49K, and N60S) relative to canonical Ub. Unlike Ub, Ub KEKS does not promote proteasomal degradation through K48 linkages and instead modifies a distinct set of proteins. To elucidate the structural basis of this divergence, we solved the NMR solution structure of Ub KEKS and characterized its backbone dynamics by 15N-relaxation. While Ub KEKS retains the overall helix-grip fold, we observed significant rearrangements and amplified motions in residues governing the Ub pincer mode, a conformational switch that determines whether UIMs engage the canonical I44 interface or the α1–β3 edge. Specifically, Q2K and K33E cooperate to enhance motions on both fast (ps–ns) and slow (µs–ms) timescales within α1, the β1–β2 loop, and β5—regions central to pincer mode regulation. In addition, Q49K, adjacent to I44, perturbs UIM recognition and likely interferes with K48 chain formation and binding to the proteasomal receptor S5a. Collectively, our findings identify structural and dynamical determinants that explain Ub KEKS's distinct substrate profile and inability to target proteins for degradation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".