Structural and functional characterization of ubiquitin variant inhibitors for the JAMM-family deubiquitinases STAMBP and STAMBPL1
Bibliographic record
Abstract
Abstract Ubiquitination is one of the most crucial post-translational protein modifications involved in a myriad of biological pathways. This process is reversed by deubiquitinases (DUBs) that deconjugate the ubiquitin (Ub) moiety or poly-Ub chains from substrates. In the past decade, tremendous efforts have been focused on targeting DUBs for drug discovery. However, most chemical compounds with inhibitory activity for DUBs suffer from mild potency and low selectivity. To overcome these obstacles, we developed a phage display-based protein engineering strategy for generating Ub variant (UbV) inhibitors and have previously successfully applied it to the Ub-specific protease (USP) family of cysteine proteases. In this work, we leveraged the UbV platform to target STAMBP, a member of the JAB1/MPN/MOV34 (JAMM) metalloprotease family of DUB enzymes. We identified two UbVs (UbV SP.1 and UbV SP.3 ) that bind to STAMBP with high affinity but differ in their selectivity for the closely related paralog STAMBPL1. We determined the STAMBPL1-UbV SP.1 complex structure by X-ray crystallography, revealing hotspots of the tight JAMM-UbV interaction. Finally, we show that UbV SP.1 and UbV SP.3 are potent inhibitors of the STAMBP isopeptidase activity, far exceeding the reported small-molecule inhibitor BC-1471. This work demonstrates that UbV technology is suitable to develop tool molecules for metalloproteases. These tools can be used to understand the cellular function of JAMM family DUBs.
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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".