A novel method for site-specific chemical SUMOylation: SUMOylation of Hsp90 modulates co-chaperone binding <i>in vitro</i>
Bibliographic record
Abstract
SUMO is covalently attached to lysine side chains in target proteins by the action of a cascade of E1, E2, and E3 ligases. Unlike ubiquitin, SUMO does not target proteins for degradation but rather plays a regulatory role in activating target proteins or directing them to multiprotein complexes. Isolating SUMOylated proteins from native sources is challenging because of the low stoichiometry of SUMOylation that occurs for any given target protein in cells. Here we report a novel strategy to couple SUMO to the site of a target lysine for the purpose of in vitro study. Introduction of a single cysteine after the C terminal diglycine motif and a cysteine in place of a target lysine in a substrate protein allows for efficient and specific crosslinking of SUMO using a homo-bifunctional maleimide crosslinker. We demonstrate that SUMO can be crosslinked in this manner to amino acid position 178 in the dimeric molecular chaperone, Hsp90. Chemically SUMOylated Hsp90 has very similar ATPase activity compared to unmodified Hsp90 but displays preferential co-chaperone binding in vivo. Our novel strategy can easily be applied to other SUMOylated or ubiquitinated target protein in vitro.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".