Evolution of Characterized Phosphorylation Sites in Budding Yeast
Bibliographic record
Abstract
Phosphorylation is one of the most studied and important regulatory mechanisms that modulate protein function in eukaryotic cells. Recently, several studies have investigated the evolution of phosphorylation sites identified by high-throughput methods. These studies have revealed varying degrees of evidence for constraint and plasticity, and therefore, there is currently no consensus as to the evolutionary properties of this important regulatory mechanism. Here, we present a study of high-confidence annotated sites from budding yeast and show that these sites are significantly constrained compared with their flanking region in closely related species. We show that this property does not change in structured or unstructured regions. We investigate the birth, death and compensation rates of the phosphorylation sites and test if sites are more likely to be gained or lost in proteins with greater numbers of sites. Finally, we also show that this evolutionary conservation can yield significant improvement for kinase target predictions when the kinase recognition motif is known, and can be used to infer the recognition motif when a set of targets is known. Our analysis indicates that phosphorylation sites are under selective constraint, consistent with their functional importance. We also find that a small fraction of phosphorylation sites turnover during evolution, which may be an important process underlying the evolution of regulatory networks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".