Allosteric regulation of cyclic nucleotide-dependent protein kinases
Bibliographic record
Abstract
Kinases include a wide variety of valuable drug targets, but full therapeutic exploitation requires a high degree of selectivity. A promising avenue to engineer the desired kinase selectivity relies on allosteric sites. Here, we provide a focused minireview of recent progress in allosteric modulation of cyclic nucleotide-dependent kinases, including protein kinases A and G. We show how apparently diverse emerging concepts, such as allosteric pluripotency, allosteric nonadditive binding, and uncompetitive allosteric inhibition, are all manifestations of complex conformational ensembles. Such ensembles include not only the typical apo-inactive and effector-bound-active states, but also mixed intermediates that feature attributes of the former states within a single molecule. We also discuss how allosteric responses are amplified by aggregation processes, thus establishing a novel interface between the signaling and amyloid fields. Finally, we critically evaluate the challenges and opportunities for clinical translation opened by these emerging allosteric concepts.
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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 | 0.001 |
| 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".