<i>In Silico</i> Discovery and Subsequent Characterization of Potent 4R-Tauopathy Positron Emission Tomography Radiotracers
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide A chemical fingerprint search identified Z3777013540 (1-(5-(6-fluoro-1 H -indol-2-yl)pyrimidin-2-yl)piperidin-4-ol; 1 ) as a potential 4R-tau binding ligand. Binding assays in post-mortem Alzheimer’s disease (AD), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD) brain with [ 3 H] 1 provided K D (nM) values in AD = 4.0, PSP = 5.1, and CBD = 4.5. In vivo positron emission tomography (PET) imaging in rats with [ 18 F] 1 demonstrated good brain penetration and rapid clearance from normal brain tissues. A subsequent molecular similarity search using 1 as the query revealed an additional promising compound, Z4169252340 (4-(5-(6-fluoro-1 H -indol-2-yl)pyrimidin-2-yl)morpholine; 21 ). Binding assays with [ 3 H] 21 provided K D (nM) values in AD = 1.2, PSP = 1.6, and CBD = 1.7 and lower affinities for binding aggregated α-synuclein and amyloid-beta. PET imaging in rats with [ 18 F] 21 demonstrated a higher brain penetration than [ 18 F] 1 and rapid clearance from normal brain tissues. We anticipate that 1 and 21 will be useful for the identification of other potent novel 4R-tau radiotracers.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".