Ligand Specificity in the CRAL-TRIO Protein Family
Bibliographic record
Abstract
Intracellular trafficking of hydrophobic ligands is often mediated by specific binding proteins. The CRAL-TRIO motif is common to several lipid binding proteins including the cellular retinaldehyde binding protein (CRALBP), the alpha-tocopherol transfer protein (alpha-TTP), yeast phosphatidylinositol transfer protein (Sec14p), and supernatant protein factor (SPF). To examine the ligand specificity of these proteins, we measured their affinity toward a variety of hydrophobic ligands using a competitive [(3)H]-RRR-alpha-tocopherol binding assay. Alpha-TTP preferentially bound RRR-alpha-tocopherol over all other tocols assayed, exhibiting a K(d) of 25 nM. Binding affinities of other tocols for alphaTTP closely paralleled their ability to inhibit in vitro intermembrane transfer and their potency in biological assays. All other homologous proteins studied bound alpha-tocopherol but with pronouncedly weaker (> 10-fold) affinities than alpha-TTP. Sec14p demonstrated a K(d) of 373 nM for alpha-tocopherol, similar to that for its native ligand, phosphatidylinositol (381 nM). Human SPF had the highest affinity for phosphatidylinositol (216 nM) and gamma-tocopherol (268 nM) and significantly weaker affinity for alpha-tocopherol (K(d) 615 nM). SPF bound [(3)H]-squalene more weakly (879 nM) than the other ligands. Our data suggest that of all known CRAL-TRIO proteins, only alphaTTP is likely to serve as the physiological mediator of alpha-tocopherol's biological activity. Further, ligand promiscuity observed within this family suggests that caution should be exercised when suggesting protein function(s) from measurements utilizing a single ligand.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".