Development of Novel, Highly Potent Inhibitors of V-RAF Murine Sarcoma Viral Oncogene Homologue B1 (BRAF): Increasing Cellular Potency through Optimization of a Distal Heteroaromatic Group
Bibliographic record
Abstract
We describe the design, synthesis, and optimization of a series of new inhibitors of V-RAF murine sarcoma viral oncogene homologue B1 (BRAF), a kinase whose mutant form (V600E) is implicated in several types of cancer, with a particularly high frequency in melanoma. Our previously described inhibitors with a tripartite A-B-C system (where A is a hinge binding pyrido[4,5-b]imidazolone system, B is an aryl spacer group, and C is a heteroaromatic group) were potent against purified (V600E)BRAF in vitro but were less potent in accompanying cellular assays. Substitution of different aromatic heterocycles for the phenyl based C-ring is evaluated herein as a potential means of improving the cellular potencies of these inhibitors. Substituted pyrazoles, particularly 3-tert-butyl-1-aryl-1H-pyrazoles, increase the cellular potencies without detrimental effects on the potency on isolated (V600E)BRAF. Thus, compounds have been synthesized that inhibit, with low nanomolar concentrations, (V600E)BRAF, its downstream signaling in cells [as measured by the reduction of the phosphorylation of extracellular regulated kinase (ERK)], and the proliferation of mutant BRAF-dependent cells. Concomitant benefits are good oral bioavailability and high plasma concentrations in vivo.
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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 | 0.000 |
| 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".