High-Throughput Scintillation Proximity Assay for Stearoyl-CoA Desaturase-1
Bibliographic record
Abstract
Stearoyl-CoA desaturase (SCD) catalyzes the synthesis of monounsaturated fatty acids and has been implicated in a number of disease states, including obesity and diabetes. To find small-molecule inhibitor leads, a high-throughput scintillation proximity assay (SPA) was developed using the hydrophobic binding characteristics of a glass microsphere scintillant bead to capture SCD1 from a crude lysate of recombinant SCD1 in Sf9 lysate coupled with the strong binding characteristics of an azetidine compound ([(3)H]AZE). The SPA assay was stable over 24 h and could detect compounds with micromolar to nanomolar potencies. A robust 1536-well high-throughput screening assay was developed with good signal-to-noise ratio (10:1) and excellent Z' factor (0.8). A screening collection of 1.6 million compounds was screened at 11 µM, and approximately 7700 compounds were identified as initial hits, exhibiting at least 35% inhibition of [(3)H]AZE binding. Further screening and confirmation with an SCD enzyme activity assay led to a number of new structural leads for inhibition of the enzyme. The SPA assay complements the enzyme activity assay for SCD1 as a tool for the discovery of novel leads in drug discovery.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".