PKD autoinhibition in <i>trans</i> regulates activation loop autophosphorylation in <i>cis</i>
Bibliographic record
Abstract
Phosphorylation is a ubiquitous mechanism by which signals are transduced in cells. Protein kinases, enzymes that catalyze the phosphotransfer reaction are, themselves, often regulated by phosphorylation. Paradoxically, however, a substantial fraction of more than 500 human protein kinases are capable of catalyzing their own activation loop phosphorylation. Commonly, these kinases perform this autophosphorylation reaction in trans , whereby transient dimerization leads to the mutual phosphorylation of the activation loop of the opposing protomer. In this study, we demonstrate that protein kinase D (PKD) is regulated by the inverse mechanism of dimerization-mediated trans -autoinhibition, followed by activation loop autophosphorylation in cis . We show that PKD forms a stable face-to-face homodimer that is incapable of either autophosphorylation or substrate phosphorylation. Dissociation of this trans -autoinhibited dimer results in activation loop autophosphorylation, which occurs exclusively in cis . Phosphorylation serves to increase PKD activity and prevent trans -autoinhibition, thereby switching PKD on. Our findings not only reveal the mechanism of PKD regulation but also have profound implications for the regulation of many other eukaryotic kinases.
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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 | 0.001 |
| 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".