Pre-N and C-terminal extension regions of Arabidopsis HSP90.7 regulate the chaperone activity and ER stress response
Bibliographic record
Abstract
The endoplasmic reticulum (ER)-localized molecular chaperone heat shock protein 90.7 (HSP90.7) plays a critical role in maintaining protein homeostasis in plants, particularly under stress conditions. However, the functional roles of its pre-N-terminal region (pre-N) and C-terminal extension (CTE) regions remain poorly understood. In this study, we integrated molecular dynamics simulations, in vitro biochemical assays, and in vivo mutant analysis to investigate the roles of these regions. Deletion of either region did not affect normal seedling development but conferred pronounced hypersensitivity to ER stress. Molecular dynamics simulations revealed that both the pre-N and CTE form regulatory contacts with HSP90.7's N-terminal, middle, and C-terminal domains, likely modulating the chaperone's global stability and interdomain communication. Consistent with these findings, removing the pre-N region increased ATPase activity and altered ATP-binding kinetics, consistent with prior reports for mammalian glucose response protein 94, whereas deleting the CTE diminished ATP-independent holdase function. Thus, our findings highlight a conserved regulatory role of the pre-N across ER-localized HSP90s. Together, our results underscore the significance of the pre-N and CTE regions for HSP90.7's functional cycle and establish their specialized roles in ER homeostasis and plant stress resilience.
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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".