Identification of Selective Acyl Sulfonamide–Cycloalkylether Inhibitors of the Voltage-Gated Sodium Channel (Na <sub>V</sub> ) 1.7 with Potent Analgesic Activity
Bibliographic record
Abstract
Herein, we report the discovery and optimization of a series of orally bioavailable acyl sulfonamide Na V 1.7 inhibitors that are selective for Na V 1.7 over Na V 1.5 and highly efficacious in in vivo models of pain and hNa V 1.7 target engagement. An analysis of the physicochemical properties of literature Na V 1.7 inhibitors suggested that acyl sulfonamides with high f sp3 could overcome some of the pharmacokinetic (PK) and efficacy challenges seen with existing series. Parallel library syntheses lead to the identification of analogue 7, which exhibited moderate potency against Na V 1.7 and an acceptable PK profile in rodents, but relatively poor stability in human liver microsomes. Further, design strategy then focused on the optimization of potency against hNa V 1.7 and improvement of human metabolic stability, utilizing induced fit docking in our previously disclosed X-ray cocrystal of the Na V 1.7 voltage sensing domain. These investigations culminated in the discovery of tool compound 33, one of the most potent and efficacious Na V 1.7 inhibitors reported to date.
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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) | 0.000 | 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 | 0.001 |
| 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".