System-wide Analysis Reveals Intrinsically Disordered Proteins Are Prone to Ubiquitylation after Misfolding Stress
Bibliographic record
Abstract
Damaged and misfolded proteins that are no longer functional in the cell need to be eliminated. Failure to do so might lead to their accumulation and aggregation, a hallmark of many neurodegenerative diseases. Protein quality control pathways play a major role in the degradation of these proteins, which is mediated mainly by the ubiquitin proteasome system. Despite significant focus on identifying ubiquitin ligases involved in these pathways, along with their substrates, a systems-level understanding of these pathways has been lacking. For instance, as misfolded proteins are rapidly ubiquitylated, unconjugated ubiquitin is rapidly depleted from the cell upon misfolding stress; yet it is unknown whether certain targets compete more efficiently to be ubiquitylated. Using a system-wide approach, we applied statistical and computational methods to identify characteristics enriched among proteins that are further ubiquitylated after heat shock. We discovered that distinct populations of structured and, surprisingly, intrinsically disordered proteins are prone to ubiquitylation. Proteomic analysis revealed that abundant and highly structured proteins constitute the bulk of proteins in the low-solubility fraction after heat shock, but only a portion is ubiquitylated. In contrast, ubiquitylated, intrinsically disordered proteins are enriched in the low-solubility fraction after heat shock. These proteins have a very low abundance in the cell, are rarely encoded by essential genes, and are enriched in binding motifs. In additional experiments, we confirmed that several of the identified intrinsically disordered proteins were ubiquitylated after heat shock and demonstrated for two of them that their disordered regions are important for ubiquitylation after heat shock. We propose that intrinsically disordered regions may be recognized by the protein quality control machinery and thereby facilitate the ubiquitylation of proteins after heat shock.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".