Novel Dimer Compounds That Bind α-Synuclein Can Rescue Cell Growth in a Yeast Model Overexpressing α-Synuclein. A Possible Prevention Strategy for Parkinson’s Disease
Bibliographic record
Abstract
The misfolding of α-synuclein is a critical event in the death of dopaminergic neurons and the progression of Parkinson’s disease. Previously, it was suggested that drugs, which bind to α-synuclein and form a loop structure between the N- and C-termini, tend to be neuroprotective, whereas others, which cause a more compact structure, tend to be neurotoxic. To improve the binding to α-synuclein, eight novel compounds were synthesized from a caffeine scaffold attached to ( R, S )-1-aminoindan, ( R, S )-nicotine, and metformin, and their binding to α-synuclein determined through nanopore analysis and isothermal titration calorimetry. The ability of the dimers to interact with α-synuclein in a cell system was assayed in a yeast model of PD which expresses an AS-GFP (α-synuclein-Green Fluorescent Protein) construct under the control of a galactose promoter. In 5 mM galactose this yeast strain will not grow and large cytoplasmic foci are observed by fluorescent microscopy. Two of the dimers, C 8 -6-I and C 8 -6-N, at a concentration of 0.1 μM allowed the yeast to grow normally in 5 mM galactose and the AS-GFP became localized to the periphery of the cell. Both dimers were superior when compared to the monomeric compounds. The presence of the dimers also caused the disappearance of preformed cytoplasmic foci. Nanopore analysis of C 8 -6-I and C 8 -6-N were consistent with simultaneous binding to both the N- and C-terminus of α-synuclein but the binding constants were only 10 5 M –1 .
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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".