Evolution and Engineering of Allosteric Regulation in Protein Kinases
Bibliographic record
Abstract
ABSTRACT Allosteric regulation – the control of protein function by sites far from the active site – is a common feature of proteins that enables dynamic cellular responses. Reversible modifications such as phosphorylation are well suited to mediate such regulatory dynamics, yet the evolution of new allosteric regulation demands explanation. To understand this, we mutationally scanned the surface of a prototypical kinase to identify readily evolvable phosphorylation sites. The data reveal a set of spatially distributed “hotspots” that coevolve with the active site and preferentially modulate kinase activity. By engineering simple consensus phosphorylation sites at these hotspots we successfully rewired in vivo cell signaling. Beyond synthetic biology, the hotspots are frequently used by the diversity of natural allosteric regulatory mechanisms in the kinase family and exploited in human disease. ONE SENTENCE SUMMARY Cell signaling is easily rewired by introducing new phosphoregulation at latent allosteric surface sites.
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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 | 0.001 |
| 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".