Recovery of PEX1-Gly843Asp peroxisome dysfunction by small-molecule compounds
Bibliographic record
Abstract
Zellweger spectrum disorder (ZSD) is a heterogeneous group of diseases with high morbidity and mortality caused by failure to assemble normal peroxisomes. There is no therapy for ZSD, but management is supportive. Nevertheless, one-half of the patients have a phenotype milder than classic Zellweger syndrome and exhibit a progressive disease course. Thus, patients would benefit if therapies became available and were instituted early. Recent reports indicate several interventions that result in partial peroxisome recovery in ZSD fibroblasts. To identify drugs that recover peroxisome functions, we expressed a GFP-peroxisome targeting signal 1 reporter in fibroblasts containing the common disease allele, PEX1-p.Gly843Asp. The GFP reporter remained cytosolic at baseline, and improvement in peroxisome functions was detected by the redistribution of the GFP reporter from the cytosol to the peroxisome. We established a high-content screening assay based on this phenotype assay and evaluated 2,080 small molecules. The cells were cultured in chemical for 2 days and then, were fixed and imaged by epifluorescent microscopy on a high-content imaging platform. We identified four compounds that partially recover matrix protein import, and we confirmed three using independent assays. Our results suggest that PEX1-p.G843D is a misfolded protein amenable to chaperone therapy.
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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 | 0.000 |
| 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".