‘AND’ logic gates at work: Crystal structure of Rad53 bound to Dbf4 and Cdc7
Bibliographic record
Abstract
Forkhead-associated (FHA) domains are phosphopeptide recognition modules found in many signaling proteins. The Saccharomyces cerevisiae protein kinase Rad53 is a key regulator of the DNA damage checkpoint and uses its two FHA domains to interact with multiple binding partners during the checkpoint response. One of these binding partners is the Dbf4-dependent kinase (DDK), a heterodimer composed of the Cdc7 kinase and its regulatory subunit Dbf4. Binding of Rad53 to DDK, through its N-terminal FHA (FHA1) domain, ultimately inhibits DDK kinase activity, thereby preventing firing of late origins. We have previously found that the FHA1 domain of Rad53 binds simultaneously to Dbf4 and a phosphoepitope, suggesting that this domain functions as an 'AND' logic gate. Here, we present the crystal structures of the FHA1 domain of Rad53 bound to Dbf4, in the presence and absence of a Cdc7 phosphorylated peptide. Our results reveal how the FHA1 uses a canonical binding interface to recognize the Cdc7 phosphopeptide and a non-canonical interface to bind Dbf4. Based on these data we propose a mechanism to explain how Rad53 enhances the specificity of FHA1-mediated transient interactions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".