Design, Synthesis, and Biological Evaluation of 3-(Imidazo[1,2-<i>a</i>]pyrazin-3-ylethynyl)-4-isopropyl-<i>N</i>-(3-((4-methylpiperazin-1-yl)methyl)-5-(trifluoromethyl)phenyl)benzamide as a Dual Inhibitor of Discoidin Domain Receptors 1 and 2
Bibliographic record
Abstract
Abstract Discoidin-domain receptors 1 and 2 (DDR1 and DDR2) are new potential targets for anti-inflammatory-drug discovery. A series of heterocycloalkynylbenzimides were designed and optimized to coinhibit DDR1 and DDR2. One of the most promising compounds, 5n, tightly bound to DDR1 and DDR2 proteins with Kd values of 7.9 and 8.0 nM; potently inhibited the kinases with IC50 values of 9.4 and 20.4 nM, respectively; and was significantly less potent for a panel of 403 wild-type kinases at 1.0 μM. DDR1- and DDR2-kinase inhibition by 5n was validated by Western-blotting analysis in primary human lung fibroblasts. The compound also dose-dependently inhibited lipopolysaccharide (LPS)-induced interleukin 6 (IL-6) release in vitro and exhibited promising in vivo anti-inflammatory effects in an LPS-induced-acute-lung-injury (ALI) mouse model. Compound 5n may serve as a lead compound for new anti-inflammatory drug discovery.
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 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) | 0.002 | 0.001 |
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".