The prion protein binds thiamine
Bibliographic record
Abstract
Although highly conserved throughout evolution, the exact biological function of the prion protein is still unclear. In an effort to identify the potential biological functions of the prion protein we conducted a small-molecule screening assay using the Syrian hamster prion protein [shPrP(90-232)]. The screen was performed using a library of 149 water-soluble metabolites that are known to pass through the blood-brain barrier. Using a combination of 1D NMR, fluorescence quenching and surface plasmon resonance we identified thiamine (vitamin B1) as a specific prion ligand with a binding constant of ~60 μM. Subsequent studies showed that this interaction is evolutionarily conserved, with similar binding constants being seen for mouse, hamster and human prions. Various protein construct lengths, both with and without the unstructured N-terminal region in the presence and absence of copper, were examined. This indicates that the N-terminus has no influence on the protein's ability to interact with thiamine. In addition to thiamine, the more biologically abundant forms of vitamin B1 (thiamine monophosphate and thiamine diphosphate) were also found to bind the prion protein with similar affinity. Heteronuclear NMR experiments were used to determine thiamine's interaction site, which is located between helix 1 and the preceding loop. These data, in conjunction with computer-aided docking and molecular dynamics, were used to model the thiamine-binding pharmacophore and a comparison with other thiamine binding proteins was performed to reveal the common features of interaction.
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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".