Functionally active modulators targeting the LRRK2 WD40 repeat domain identified by FRASE-bot in CACHE Challenge #1
Bibliographic record
Abstract
Critical Assessment of Computational Hit-Finding Experiments (CACHE) Challenges emerged as real-life stress tests for computational hit-finding strategies. In CACHE Challenge #1, 23 participants contributed their original workflows to identify small-molecule ligands for the WD40 repeat (WDR) of LRRK2, a promising Parkinson's target. We applied the FRASE-based hit-finding robot (FRASE-bot), a platform for interaction-based screening allowing a drastic reduction of the explorable chemical space and a concurrent detection of putative ligand-binding sites. In two screening rounds, 84 compounds were procured for experimental testing and 8 were confirmed to bind LRRK2-WDR with dissociation constants (Kd) ranging from 3 to 41 μM. To investigate the functional effect of WDR ligands, they were tested for their ability to modify the LRRK2 activity markers in HEK293T cells. Two compounds showed statistically significant increases in the kinase activity of WT LRRK2, and two compounds affected the conformation and kinase activity of major LRRK2 mutants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".