Targeting AGAT gene expression – a drug screening approach for the treatment of GAMT deficiency
Bibliographic record
Abstract
BACKGROUND: Targeting the enzyme L-Arginine:glycine amidinotransferase (AGAT) to reduce the formation of guanidinoacetate (GAA) in patients with guanidinoacetate methyltransferase (GAMT) deficiency, we attempted to identify drugs for repurposing that reduce the expression of AGAT via transcriptional inhibition. RESEARCH DESIGN AND METHODS: The authors applied a HeLa cell line stably expressing AGAT promoter and firefly luciferase reporter for high-content screening and secondary screening. For further assessment, the authors integrated Nanoluc luciferase as a reporter into the endogenous AGAT gene in HAP1 cell lines and used the human immortalized cell line RH30 as model of GAMT deficiency. RESULTS: Screening 6,000 drugs and drug-like compounds, the authors identified 43 and 34 high-score candidates as inhibitors and inducers of AGAT promoter-reporter expression, respectively. After further deselection considering dose response, drug toxicity, topical formulations, price, and accessibility, the authors assessed seven candidates and found none of them demonstrating efficacy in HAP1 and RH30 cells and warranting further assessment. CONCLUSION: The selection of the test models is crucial for screening of gene repressor drugs. Almost all drugs with an impact on gene expression had off-target effects. It is unlikely to find drugs that are selective inhibitors of AGAT expression, rendering pharmacological AGAT gene repression a risky approach for the treatment of GAMT deficiency.
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 | 0.000 |
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".