Structural basis for protein–protein interactions in the 14-3-3 protein family
Bibliographic record
Abstract
The seven members of the human 14-3-3 protein family regulate a diverse range of cell signaling pathways by formation of protein-protein complexes with signaling proteins that contain phosphorylated Ser/Thr residues within specific sequence motifs. Previously, crystal structures of three 14-3-3 isoforms (zeta, sigma, and tau) have been reported, with structural data for two isoforms deposited in the Protein Data Bank (zeta and sigma). In this study, we provide structural detail for five 14-3-3 isoforms bound to ligands, providing structural coverage for all isoforms of a human protein family. A comparative structural analysis of the seven 14-3-3 proteins revealed specificity determinants for binding of phosphopeptides in a specific orientation, target domain interaction surfaces and flexible adaptation of 14-3-3 proteins through domain movements. Specifically, the structures of the beta isoform in its apo and peptide bound forms showed that its binding site can exhibit structural flexibility to facilitate binding of its protein and peptide partners. In addition, the complex of 14-3-3 beta with the exoenzyme S peptide displayed a secondary structural element in the 14-3-3 peptide binding groove. These results show that the 14-3-3 proteins are adaptable structures in which internal flexibility is likely to facilitate recognition and binding of their interaction partners.
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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) | 0.000 | 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) | 0.001 | 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".