Design, Synthesis, and Bioactivity Assessment of Modified Vemurafenib Analog
Bibliographic record
Abstract
Background: Metastatic melanoma is a highly aggressive malignancy with poor prognoses and frequent resistance to conventional chemotherapy. Approximately 40% of melanoma cases carry the BRAFV600E mutation, for which vemurafenib, a selective BRAFV600E inhibitor, is approved. Despite initial clinical benefits, vemurafenib often leads to drug resistance and relapse, highlighting the need for improved therapeutic strategies. Objectives, methods: In this study, we designed, synthesized, and characterized five novel vemurafenib analogs—RF-86A, RF-87A, RF-94A, RF-94B, and RF-96B—with the aim of enhancing anti-proliferative and anti-metastatic effects against human melanoma cells. Results: All compounds induced apoptosis in BRAFV600E-mutated A375 cells, with RF-86A displaying the lowest IC50 value among the series, comparable to that of vemurafenib. Moreover, RF-86A exhibited the highest selectivity index, as determined using HEK293T cells as a non-tumorigenic control. Additionally, migration assays and gelatin zymography demonstrated that the analogs, unlike vemurafenib, significantly inhibited matrix metalloproteinases MMP-2 and MMP-9, key enzymes involved in tumor invasion and metastasis. Conclusions: These findings suggest that structural modifications to the vemurafenib scaffold may improve therapeutic efficacy and offer a promising strategy to overcome acquired resistance.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".