Computationally Driven Discovery of a BCR-ABL1 Kinase Inhibitor with Activity in Multidrug-Resistant Chronic Myeloid Leukemia
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The permeability glycoprotein, encoded by the ABCB1 gene, is widely implicated in multidrug resistance (MDR), as it has been shown to reduce the intracellular concentration of most small molecule therapeutics, including the majority of the breakpoint cluster region Abelson proto-oncogene 1 (BCR-ABL1) kinase inhibitors used in the treatment of Philadelphia chromosome positive (Ph+) leukemias. With this in mind, we describe an integrated theoretical and experimental approach to shed light on substituent effects in the pendant anilino moiety of 4-anilinoquinazolines and 4-anilinoquinoline-3-carbonitrile-based kinase inhibitors and their influence on P-gp-mediated efflux. This analysis culminated in the identification of a hydroxylamine-bearing, dual cSRC/BCR-ABL1 kinase inhibitor 16a that exhibits a marked reduction in P-gp-mediated efflux ratio and potent activity in a Ph+ patient-derived cell line (K562) and an MDR-Ph+ patient-derived cell line (K562/Dox) overexpressing P-gp. Overall, we demonstrate that the P-gp-mediated efflux ratio can be minimized by computationally driven optimization of the molecular dipole and/or cp K a without recourse to intramolecular hydrogen bonds.
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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) | 0.004 | 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".