Characterization of 14-3-3 Proteins from Cryptosporidium parvum
Bibliographic record
Abstract
UNLABELLED: The parasite Cryptosporidium parvum has three 14-3-3 proteins: Cp14ε, Cp14a and Cp14b, with only Cp14ε similar to human 14-3-3 proteins in sequence, peptide-binding properties and structure. Structurally, Cp14a features the classical 14-3-3 dimer but with a uniquely wide pocket and a disoriented RRY triad potentially incapable of binding phosphopeptides. The Cp14b protein deviates from the norm significantly: (i) In one subunit, the phosphorylated C-terminal tail is bound in the binding groove like a phosphopeptide. This supports our binding study indicating this protein was stabilized by a peptide mimicking its last six residues. (ii) The other subunit has eight helices instead of nine, with αA and αB forming a single helix and occluding the peptide-binding cleft. (iii) The protein forms a degenerate dimer with the two binding grooves divided and facing opposite directions. These features conspire to block and disrupt the bicameral substrate-binding pocket, suggesting a possible tripartite auto-regulation mechanism that has not been observed previously. ENHANCED VERSION: This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".