Development of Highly Potent and Selective FGFR4 Inhibitors Based on SNAr Electrophiles
Bibliographic record
Abstract
Fibroblast Growth Factor Receptor 4 (FGFR4) is thought to be a driver in several cancer types, most notably in hepatocellular carcinoma. One way to achieve high potency and isoform-selectivity for FGFR4 is to covalently target a rare cysteine (C552) in the hinge region of its kinase domain that is not present in other FGFR family members (FGFR1-3). Typically, this cysteine is addressed via classical acrylamide electrophiles. Here, we demonstrate that non-canonical covalent “warheads” based on nucleophilic aromatic substitution (SNAr) chemistry can be employed in a rational manner to generate highly potent and (isoform )selective FGFR4 inhibitors with a low intrinsic reactivity. Our key compounds showed low- to subnanomolar potency, efficient covalent inactivation, and excellent selectivity over other FGFRs as well as kinases with an equivalent cysteine and a representative subset of the kinome. Moreover, these compounds achieved low nanomolar potencies in cellular assays and demonstrated good microsomal stability highlighting the potential of SNAr-based approaches in covalent inhibitor design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".