Series of (([1,1′-Biphenyl]-2-yl)methyl)sulfinylalkyl Alicyclic Amines as Novel and High Affinity Atypical Dopamine Transporter Inhibitors with Reduced hERG Activity
Bibliographic record
Abstract
Currently, there are no FDA-approved medications for the treatment of psychostimulant use disorders (PSUD). We have previously discovered “atypical” dopamine transporter (DAT) inhibitors that do not display psychostimulant-like behaviors and may be useful as medications to treat PSUD. Lead candidates (e.g., JJC8-091, 1 ) have shown promising in vivo profiles in rodents; however, reducing hERG (human ether-à-go-go -related gene) activity, a predictor of cardiotoxicity, has remained a challenge. Herein, a series of 30 (([1,1′-biphenyl]-2-yl)methyl)sulfinylalkyl alicyclic amines was synthesized and evaluated for DAT and serotonin transporter (SERT) binding affinities. A subset of analogues was tested for hERG activity, and the IC 50 values were compared to those predicted by our hERG QSAR models, which showed robust predictive power. Multiparameter optimization scores (MPO > 3) indicated central nervous system (CNS) penetrability. Finally, comparison of affinities in human DAT and its Y156F and Y335A mutants suggested that several compounds prefer an inward facing conformation indicating an atypical DAT inhibitor profile.
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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) | 0.001 | 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) | 0.003 | 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".