Binding of Human Nucleotide Exchange Factors to Heat Shock Protein 70 (Hsp70) Generates Functionally Distinct Complexes in Vitro
Bibliographic record
Abstract
Proteins with Bcl2-associated anthanogene (BAG) domains act as nucleotide exchange factors (NEFs) for the molecular chaperone heat shock protein 70 (Hsp70). There are six BAG family NEFs in humans, and each is thought to link Hsp70 to a distinct cellular pathway. However, little is known about how the NEFs compete for binding to Hsp70 or how they might differentially shape its biochemical activities. Toward these questions, we measured the binding of human Hsp72 (HSPA1A) to BAG1, BAG2, BAG3, and the unrelated NEF Hsp105. These studies revealed a clear hierarchy of affinities: BAG3 > BAG1 > Hsp105 ≫ BAG2. All of the NEFs competed for binding to Hsp70, and their relative affinity values predicted their potency in nucleotide and peptide release assays. Finally, we combined the Hsp70-NEF pairs with cochaperones of the J protein family (DnaJA1, DnaJA2, DnaJB1, and DnaJB4) to generate 16 permutations. The activity of the combinations in ATPase and luciferase refolding assays were dependent on the identity and stoichiometry of both the J protein and NEF so that some combinations were potent chaperones, whereas others were inactive. Given the number and diversity of cochaperones in mammals, it is likely that combinatorial assembly could generate a large number of distinct permutations.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".