A Mammalian Genetic System To Screen for Small Molecules Capable of Disrupting Protein−Protein Interactions
Bibliographic record
Abstract
A mammalian two-hybrid system was developed for high-throughput screening of compounds that disrupt specific protein-protein interactions. The existing mammalian systems are unsatisfactory for drug screening due to nonregulated expression of interacting proteins. To construct a tightly regulated system, the tetracycline repressor was fused with the inhibitory KRAB domain as a suppressor. The binding of the suppressor to the tet operator entirely blocked expression of two interacting proteins. When both the inducer doxycycline and drugs were added to the culture, the reporter gene was either activated by interaction of the paired proteins with ineffective drugs or remained silent due to disruption of the protein interactions by the effective drugs. We demonstrate that interactions of the type I receptor for TGFbeta with FKBP12 and the epidermal growth factor receptor (EGFR) with p85 are effectively disrupted by FK506 and EGFR kinase inhibitor AG1478, respectively. The power of this system for drug screening was further demonstrated by rapid identification of inhibitors from a druglike library for the receptor kinases.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".