Structure and Interactions of the Ubiquitin-Conjugating Enzyme Variant Human Uev1a: Implications for Enzymatic Synthesis of Polyubiquitin Chains<sup>,</sup>
Bibliographic record
Abstract
Lys(63)-linked polyubiquitination of TRAF2 or TRAF6 is an essential step within the signal transduction cascade responsible for activation of p38, c-Jun N-terminal kinase, and the transcription factor NF-kappaB. Attachment of ubiquitin (Ub) to a TRAF, and conjugation of Ub molecules to form a polyUb chain, is catalyzed by a heterodimer composed of a catalytically active E2 (hUbc13), involved in covalent bond transfer, and hUev1a, an E2-like protein involved in substrate Ub binding. Given the key biochemical processes in which hUev1a is involved, it is important to determine the molecular basis of the catalytic mechanism for Lys(63)-linked protein ubiquitination. Nuclear magnetic resonance (NMR) spectroscopy was used to determine the structure of hUev1a and its interactions with Ub and hUbc13. A structural model for the Ub-hUev1a-hUbc13-Ub tetramer was developed to gain chemical insight into the synthesis of Lys(63)-linked Ub chains. We propose that a network of hydrogen bonds involving hUbc13-Asp(81) and Ub-Glu(64) positions Ub-Lys(63) proximal to the active site. Interestingly, restrained molecular dynamics simulations in implicit solvent indicate that deprotonation of Ub-Lys(63) does not involve a general Asp or Glu base and may occur when the amino group approaches the thioester carbonyl carbon near the Bürgi-Dunitz trajectory.
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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 | 0.001 | 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".