Glycosylated tetrahydrosalens as multifunctional molecules for Alzheimer's therapy
Bibliographic record
Abstract
The tetrahydrosalens N,N'-bis(2-hydroxybenzyl)-ethane-1,2-diamine ((2)(1)), N,N'-bis(2-hydroxybenzyl)-(-)-1,2-cyclohexane-(1R,2R)-diamine ((2)(2)), N,N'-bis(2-hydroxybenzyl)-N,N'-dimethyl-ethane-1,2-diamine ((2)(3)), N,N'-bis(2-hydroxybenzyl)-N,N'-dibenzyl-ethane-1,2-diamine ((2)(4)), and N,N'-bis(2-(4-tert-butyl)hydroxybenzyl)-ethane-1,2-diamine ((2)(5)), as well as their prodrug glycosylated forms, (1-5), have been prepared and evaluated in vitro for their potential use as Alzheimer's disease (AD) therapeutics. Dysfunctional interactions of metal ions, especially those of Cu, Zn, and Fe, with the amyloid-beta (Abeta) peptide are hypothesised to play an important role in the aetiology of AD, and disruption of these aberrant metal-peptide interactions via chelation therapy holds considerable promise as a therapeutic strategy. Tetrahydrosalens such as (2)(1-5) have a significant affinity for metal ions, and thus should be able to compete with the Abeta peptide for Cu, Zn, and Fe in the brain. This activity was assayed in vitrovia a turbidity assay; (2)(1) and (2)(3) were found to attenuate Abeta(1-40) aggregation after exposure to Cu(2+) and Zn(2+). In addition, (2)(1-5) were determined to be potent antioxidants on the basis of an in vitro antioxidant assay. (1-5) were prepared as metal binding prodrugs; glycosylation is intended to prevent systemic metal binding, improve solubility, and enhance brain uptake. Enzymatic (beta-glucosidase) deprotection of the carbohydrate moieties was facile, with the exception of (4), demonstrating the general feasibility of this prodrug approach. Finally, a representative prodrug, (3), was determined to be non-toxic over a large concentration range in a cell viability assay.
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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 | 0.000 | 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 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".