Structure and function of the Fgd family of divergent FYVE domain proteins
Bibliographic record
Abstract
FYVE domains are highly conserved protein modules that typically bind phosphatidylinositol 3-phosphate (PI3P) on the surface of early endosomes. Along with pleckstrin homology (PH) and phox homology (PX) domains, FYVE domains are the principal readers of the phosphoinositide (PI) code that mediate specific recognition of eukaryotic organelles. Of all the human FYVE domain containing proteins, those within the faciogenital dysplasia (Fgd) subfamily are particularly divergent and couple with GTPases to exert unique cellular functions. The subcellular distributions and functions of these evolutionarily conserved signal transducers, which also include Dbl homology (DH) and two PH domains, are discussed here to better understand the biological range of processes that such multidomain proteins engage in. Determinants of their various functions include specific multidomain architectures, posttranslational modifications including PIP stops that have been discovered in sorting nexins, PI recognition motifs, and phospholipid-binding surfaces as defined by the Membrane Optimal Docking Area (MODA) program. How these orchestrate Fgd function remains unclear but has implications for developmental diseases including Aarskog-Scott syndrome, which is also known as faciogenital dysplasia, and forms of cancer that are associated with mutations and amplifications of Fgd genes.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".