Structure-Based Design of PROTACS for the Degradation of Soluble Epoxide Hydrolase
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The bifunctional soluble epoxide hydrolase (sEH) represents a promising target for inflammation-related diseases. Although potent inhibitors targeting each domain are available, sEH-PROTACs offer the unique ability to simultaneously block both enzymatic functions, mimicking the sEH knockout phenotype, which has been associated with reducing inflammation, including neuroinflammation, and delaying the progression of Alzheimer’s disease. Herein, we report the structure-based development of a potent sEH-PROTAC as a useful pharmacological tool. In order to facilitate a rapid testing of the PROTACs, a cell-based sEH degradation assay was developed utilizing HiBiT technology. We designed and synthesized 24 PROTACs. Furthermore, cocrystallization of sEH with two selected PROTACs allowed us to explore the binding mode and rationalize the most optimal linker length. After comprehensive biological and physicochemical characterization of this series, the most optimal PROTAC 23 was identified in primary human and murine cells, highlighting the potential of using 23 in disease-relevant cell and tissue models.
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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 | 0.001 |
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".