Discovery of Novel Flavonoid Dimers To Reverse Multidrug Resistance Protein 1 (MRP1, ABCC1) Mediated Drug Resistance in Cancers Using a High Throughput Platform with “Click Chemistry”
Bibliographic record
Abstract
A 300-member flavonoid dimer library of multidrug resistance-associated protein 1 (MRP1, ABCC1) modulators was rapidly assembled using “click chemistry”. Subsequent high-throughput screening has led to the discovery of highly potent (EC 50 ranging from 53 to 298 nM) and safe (selective indexes ranging from >190 to >1887) MRP1 modulators. Some dimers have potency about 6.5- to 36-fold and 64- to 358-fold higher than the well-known MRP1 inhibitors, verapamil, and MK571, respectively. They inhibited DOX efflux and restored intracellular DOX concentration. The most potent modulator, Ac3Az11, was predicted to bind to the bipartite substrate-binding site of MRP1 in a competitive manner. Moreover, it provided sufficient concentration to maintain its plasma level above its in vitro EC 50 (53 nM for DOX) for about 90 min. Overall, we demonstrate that “click chemistry” coupled with high throughput screening is a rapid, reliable, and efficient tool in the discovery of compounds having potent MRP1-modualting activity.
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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".