From a drug repositioning to a structure-based drug design approach to tackle acute lymphoblastic leukemia
Bibliographic record
Abstract
Cancer cells utilize the main de novo pathway and the alternative salvage pathway for deoxyribonucleotide biosynthesis to achieve adequate nucleotide pools. Deoxycytidine kinase is the rate-limiting enzyme of the salvage pathway and it has recently emerged as a target for anti-proliferative therapies for cancers where it is essential. Here, we present the development of a potent inhibitor applying an iterative multidisciplinary approach, which relies on computational design coupled with experimental evaluations. This strategy allows an acceleration of the hit-to-lead process by gradually implementing key chemical modifications to increase affinity and activity. Our lead compound, OR0642, is more than 1000 times more potent than its initial parent compound, masitinib, previously identified from a drug repositioning approach. OR0642 in combination with a physiological inhibitor of the de novo pathway doubled the survival rate in a human T-cell acute lymphoblastic leukemia patient-derived xenograft mouse model, demonstrating the proof-of-concept of this drug design strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".