High Throughput Assay Identifies Glafenine as a Corrector for the Folding Defect in Corneal Dystrophy–Causing Mutants of SLC4A11
Bibliographic record
Abstract
PURPOSE: Protein misfolding, causing retention of nascent protein in the endoplasmic reticulum (ER), is the most common molecular phenotype for disease alleles of membrane proteins. Strategies are needed to identify therapeutics able to correct such folding/trafficking defects. Mutations of SLC4A11, a plasma membrane transport protein of the human corneal endothelial cell layer, cause cases of congenital hereditary endothelial dystrophy, Harboyan syndrome, and Fuchs' endothelial corneal dystrophy. Most SLC4A11 mutations induce SLC4A11 misfolding and retention in the ER. METHODS: An assay amenable to high-throughput screening was developed to quantify SLC4A11 at the plasma membrane, enabling a search for potential traffic-correcting small molecules. The assay was validated by comparing cell surface abundance of SLC4A11 mutants measured in the assay to observations from confocal immunofluorescence and values from cell surface biotinylation. Functionality of mutant proteins was assessed, using a confocal microscopic green fluorescent protein (GFP) water flux assay where relative rates of cell swelling are compared. RESULTS: A small-scale screen revealed that the nonsteroidal anti-inflammatory drugs (NSAIDs), glafenine, ibuprofen, and acetylsalicylic acid dissolved in 0.2% dimethyl sulfoxide (DMSO), partially rescued the trafficking defect in some SLC4A11 mutants, expressed in HEK293 cells. These SLC4A11 mutants retained functional activity when rescued to the plasma membrane by glafenine treatment. Glafenine was effective with an EC50 of 1.5 ± 0.7 μM. CONCLUSIONS: These data suggest that glafenine, and perhaps other NSAIDs, hold potential as therapeutics for misfolded membrane proteins, like SLC4A11. The high throughput approach described here can be modified to identify correctors of other misfolded plasma membrane proteins that cause eye disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".