Phosphorylation as a candidate regulatory mechanism for effector recruitment to tankyrase
Bibliographic record
Abstract
The ADP-ribosyltransferase tankyrase (with two paralogues, TNKS and TNKS2) plays pivotal roles in diverse cellular processes that encompass signal transduction, including Wnt/β-catenin, Hippo and toll-like receptor (TLR) signalling, mitotic spindle assembly, glucose homeostasis and telomere maintenance, among many other functions. Tankyrase recruits its effectors (substrates and binders) via a degenerate tankyrase-binding motif (TBM) and exerts its activities by subsequent substrate ADP-ribosylation and/or scaffolding. Variants of the TBM, found in diverse proteins, engage the ankyrin repeat cluster (ARC) domains of tankyrase. Yet, whether effector recruitment to tankyrase can be regulated has remained unknown. In this study, we propose that phosphorylation at position eight of the TBM enhances the affinity of effectors for the ARC domains of tankyrase. Using isolated TBM peptides, we demonstrate that phosphorylation of serine, but not tyrosine, strengthens ARC binding by up to an order of magnitude. Interrogation of proteome-wide phosphorylation data reveals that phosphorylation at position eight in the TBM is enriched in proteins that support centrosome function/localization. Our findings suggest that TBM phosphorylation may serve as an effector-specific mechanism for tankyrase recruitment/retention, providing an additional layer of regulation to control tankyrase.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".