Quercitrin and quercetin 3-β-d-glucoside as chemical chaperones for the A4V SOD1 ALS-causing mutant
Bibliographic record
Abstract
In many cases of familial amyotrophic lateral sclerosis (ALS), mutant forms of the Cu,Zn superoxide dismutase protein (SOD1) misfold and aggregate in motor neurons. Monomers of the normally homodimeric SOD1 have been found in patient tissue, presymptomatic mouse models of ALS, and in vitro misfolding assays which suggests that monomerization might be an early step in the pathological SOD1 misfolding pathway. In this study, we targeted the dimer interface with small molecules that might act as chemical chaperones to stabilize the native dimer and prevent downstream misfolding and aggregation. We performed a computational screen with a library of ~4400 drugs and natural compounds that were docked to two pockets around the SOD1 dimer interface. Of the resultant hits, seven were tested for misfolding and aggregation inhibition activity with A4V mutant SOD1. Quercitrin, quercetin-3-β-d-glucoside (Q3BDG), and, to a markedly lesser extent, epigallocatechin gallate (EGCG) were found to combat misfolding and aggregation induced by hydrogen peroxide, a physiologically relevant stress, as assessed by a gel-based assay and 8-anilinonaphthalene-1-suflonic acid (ANS) fluorescence. Isothermal titration calorimetry (ITC) and a colourimetric assay determined that these molecules directly bind A4V SOD1. Based on these findings, we speculate that quercitrin and Q3BDG may be potential therapeutic inhibitors of misfolding and aggregation in SOD1-associated ALS.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".