Allosteric linkers in cAMP signalling
Bibliographic record
Abstract
Weak interactions mediated by dynamic linkers are key determinants of allosteric regulation in multidomain signalling proteins. However, the mechanisms of linker-dependent control have remained largely elusive. In the present article, we review an allosteric model introduced recently to explain how signalling proteins effectively sense and respond to weak interactions, such as those elicited by flexible linkers flanking globular domains. Central to this model is the idea that near degeneracy within the free energy landscape of conformational selection maximally amplifies the response to weak (~2RT), but conformation-selective interactions. The model was tested as proof of principle using the prototypical regulatory subunit (R) of protein kinase A and led to the unanticipated finding that dynamic linkers control kinase activation and inhibition by tuning the inhibitory pre-equilibrium of a minimally populated intermediate (apo R). A practical implication of the proposed model is a new strategy to design kinase inhibitors with enhanced potency through frustration-relieving mutations.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".