The Human PDZome: A Gateway to PSD95-Disc Large-Zonula Occludens (PDZ)-mediated Functions
Bibliographic record
Abstract
Protein-protein interactions organize the localization, clustering, signal transduction, and degradation of cellular proteins and are therefore implicated in numerous biological functions. These interactions are mediated by specialized domains able to bind to modified or unmodified peptides present in binding partners. Among the most broadly distributed protein interaction domains, PSD95-disc large-zonula occludens (PDZ) domains are usually able to bind carboxy-terminal sequences of their partners. In an effort to accelerate the discovery of PDZ domain interactions, we have constructed an array displaying 96% of the human PDZ domains that is amenable to rapid two-hybrid screens in yeast. We have demonstrated that this array can efficiently identify interactions using carboxy-terminal sequences of PDZ domain binders such as the E6 oncoviral protein and protein kinases (PDGFRβ, BRSK2, PCTK1, ACVR2B, and HER4); this has been validated via mass spectrometry analysis. Taking advantage of this array, we show that PDZ domains of Scrib and SNX27 bind to the carboxy-terminal region of the planar cell polarity receptor Vangl2. We also have demonstrated the requirement of Scrib for the promigratory function of Vangl2 and described the morphogenetic function of SNX27 in the early Xenopus embryo. The resource presented here is thus adapted for the screen of PDZ interactors and, furthermore, should facilitate the understanding of PDZ-mediated functions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".