Structural basis of aggregate binding by the AAA+ disaggregase ClpG
Bibliographic record
Abstract
Severe heat stress causes massive loss of essential proteins by aggregation, necessitating a cellular activity that rescues aggregated proteins. This activity is executed by ATP-dependent, ring-forming, hexameric AAA+ disaggregases. Little is known about the recognition principles of stress-induced protein aggregates. How can disaggregases specifically target aggregated proteins, while avoiding binding to soluble non-native proteins? Here, we determined by NMR spectroscopy the core structure of the aggregate-targeting N1 domain of the bacterial AAA+ disaggregase ClpG, which confers extreme heat resistance to bacteria. N1 harbors a Zn 2+ -coordination site that is crucial for structural integrity and disaggregase functionality. We found that conserved hydrophobic N1 residues located on a β-strand are crucial for aggregate targeting and disaggregation activity. Analysis of mixed hexamers consisting of full-length and N1-truncated subunits revealed that a minimal number of four N1 domains must be present in a AAA+ ring for high-disaggregation activity. We suggest that multiple N1 domains increase substrate affinity through avidity effects. These findings define the recognition principle of a protein aggregate by a disaggregase, involving simultaneous contacts with multiple hydrophobic substrate patches located in close vicinity on an aggregate surface. This binding mode ensures selectivity for aggregated proteins while sparing soluble, non-native protein structures from disaggregase activity.
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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) | 0.000 | 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".