Automated in vivo compound screening with zebrafish and the discovery and validation of PD 81,723 as a novel angiogenesis inhibitor
Bibliographic record
Abstract
Angiogenesis is a critical process in tumor progression. Inhibition of angiogenesis by blocking VEGF signaling can impair existing tumor vessels and halt tumor progression. However, the benefits are transient, and most patients who initially respond to these therapies develop resistance. Accordingly, there is a need for new anti-angiogenesis therapeutics to delay the processes of resistance or eliminate the resistive effects entirely. This manuscript presents the results of a screen of the National Institutes of Health Clinical Collections Libraries I & II (NIHCCLI&II) for novel angiogenesis inhibitors. The 727 compounds of the NIHCCLI&II library were screened with a high-throughput drug discovery platform (HTP) developed previously with angiogenesis-specific protocols utilizing zebrafish. The screen resulted in 14 hit compounds that were subsequently narrowed down to one, with PD 81,723 chosen as the lead compound. PD 81,723 was validated as an inhibitor of angiogenesis in vivo in zebrafish and in vitro in human umbilical vein endothelial cells (HUVECs). Zebrafish exposed to PD 81,723 exhibited several signs of a diminished endothelial network due to the inhibition of angiogenesis. Immunochemical analysis did not reveal any significant apoptotic or mitotic activity in the zebrafish. Assays with cultured HUVECs elucidated the ability of PD 81,723 to inhibit capillary tube formation, migration, and proliferation of endothelial cells. In addition, PD 81,723 did not induce apoptosis while significantly down regulating p21, AKT, VEGFR-2, p-VEGFR-2, eNOS, and p-eNOS, with no notable change in endogenous VEGF-A in cultured HUVECs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".