The Binding of BF-227-Like Benzoxazoles to Human α-Synuclein and Amyloid β Peptide Fibrils
Bibliographic record
Abstract
Development of an α-synuclein (α-Syn) positron emission tomography agent for the diagnosis and evaluation of Parkinson disease therapy is a key goal of neurodegenerative disease research. BF-227 has been described as an α-Syn binder and hence was employed as a lead to generate a library of α-Syn-binding compounds. [ 3 H]BF-227 bound to α-Syn and amyloid β peptide (Aβ) fibrils with affinities (K D ) of 46.0 nM and 15.7 nM, respectively. Affinities of BF-227-like compounds (expressed as K i ) for α-Syn and Aβ fibrils were determined, along with 5 reference compounds (flutafuranol, flutemetamol, florbetapir, BF-227, and PiB). Selectivity for α-Syn binding, defined as the K i (Aβ)/K i (α-Syn) ratio, was 0.23 for BF-227. A similar or lower ratio was measured for analogues decorated with alkyl or oxyethylene chains attached to the oxygen at the 6 position of BF-227, suggesting a lack of involvement of the side chain in fibril binding. BF-227-like iodobenzoxazoles had lower affinities and poor α-Syn selectivity. However, BF-227-like fluorobenzoxazoles had improved α-Syn selectively having K i (Aβ)/K i (α-Syn) ranging from 2.2 to 5.1 with appreciable fibril affinity, although not sufficient to warrant further investigation. Compounds based on fluorobenzoxazoles might offer an approach to obtaining an α-Syn imaging agent with an appropriate affinity and selectivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".