Mutational Analysis of Glycogen Synthase Kinase 3β Protein Kinase Together with Kinome-Wide Binding and Stability Studies Suggests Context-Dependent Recognition of Kinases by the Chaperone Heat Shock Protein 90
Bibliographic record
Abstract
The heat shock protein 90 (HSP90) and cell division cycle 37 (CDC37) chaperones are key regulators of protein kinase folding and maturation. Recent evidence suggests that thermodynamic properties of kinases, rather than primary sequences, are recognized by the chaperones. In concordance, we observed a striking difference in HSP90 binding between wild-type (WT) and kinase-dead (KD) glycogen synthase kinase 3β (GSK3β) forms. Using model cell lines stably expressing these two GSK3β forms, we observed no interaction between WT GSK3β and HSP90, in stark contrast to KD GSK3β forming a stable complex with HSP90 at a 1:1 ratio. In a survey of 91 ectopically expressed kinases in DLD-1 cells, we compared two parameters to measure HSP90 dependency: static binding and kinase stability following HSP90 inhibition. We observed no correlation between HSP90 binding and reduced stability of a kinase after pharmacological inhibition of HSP90. We expanded our stability study to >50 endogenous kinases across four cell lines and demonstrated that HSP90 dependency is context dependent. These observations suggest that HSP90 binds to its kinase client in a particular conformation that we hypothesize to be associated with the nucleotide-processing cycle. Lastly, we performed proteomics profiling of kinases and phosphopeptides in DLD-1 cells to globally define the impact of HSP90 inhibition on the kinome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".