Small Molecule Drugs That Inhibit Phagocytosis
Bibliographic record
Abstract
In our initial publication on the in vitro testing of more than 200 compounds, we demonstrated that small molecules can inhibit phagocytosis. We therefore theorized that a small molecule drug discovery-based approach to the treatment of immune cytopenias (ITP, AIHA, HTR, DHTR) is feasible. Those earlier studies showed that small molecules with anti-phagocytic groups, such as the pyrazole core, are good models for producing efficacious phagocytosis inhibitors with low toxicity. We recently screened a chemical library of 80 compounds containing pyrazole/isoxazole/pyrrole core structures and found four hit molecules for further follow-up, all having the pyrazole core structure. Subsequent evaluation via MTT viability, LDH release, and apoptosis, led to the selection of two lead compounds with negligible toxicity and high efficacy. In an in vitro assay for inhibition of phagocytosis, their IC50 values were 2–4 µM. The rational development of these discoveries from hit to lead molecule stage, viz. independent synthesis/scale up of hit molecules, and in vivo activities in mouse models of autoimmune disease, will result in the selection of a lead compound(s) for further pre-clinical evaluation.
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 | 0.000 |
| 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) | 0.000 | 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 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".