Synthesis and Biological Evaluation of Small Molecule Inhibitors of Immune Cytopenias
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Immune cytopenias are a group of autoimmune disorders where patients develop autoantibodies against certain types of blood cells such as red blood cells (RBCs) or thrombocytes. We investigated small molecules as potential inhibitors of phagocytosis of blood cells that are prevalent in immune thrombocytopenia (ITP) and warm autoantibody immune hemolytic anemia (wAIHA). Upon screening a chemical library of over 13,000 compounds in silico, followed by evaluating 80 compounds in vitro as inhibitors of phagocytosis of opsonized RBCs by monocytes, we identified four hit molecules. These compounds contain a pyrazole moiety as a key structural feature. Here, we reveal the independent synthesis and re-evaluation of these hits, as well as revalidate the biological activities and the synthesis of their analogs to understand the structure–activity relationships. Two of the resynthesized compounds showed up to a 9-fold difference in their inhibitory activities between the commercial and synthesized batches, and the analogs exhibited either equal or weaker potency than the parent compounds targeting phagocytosis of RBCs. The role of regioisomers and the importance of an ester moiety are revealed as important structural features through these analogs. The pharmacokinetics of the promising compound 33 suggested that this compound shows significant efficacy in restoring platelet counts in the mouse model of ITP, despite the rapid hydrolysis of its methyl ester moiety.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".