Development of a genetically encoded and potent PDE6D inhibitor
Bibliographic record
Abstract
Abstract PDE6D is a trafficking chaperone of prenylated proteins, such as small GTPases. Several small molecule inhibitors have been developed against it, given that the oncogene K-Ras is one of the cargo proteins. Inhibitor development suffered from the fact that inhibitors against the hydrophobic pocket of PDE6D were typically poorly water-soluble. Here we describe the development of genetically encoded inhibitors that are inspired by high-affinity natural cargo of PDE6D. Our most potent inhibitor, SNAP-STI, encodes merely a farnesylated tetra-peptide, which efficiently blocks PDE6D binding of farnesylated cargo. Direct comparison with small molecule PDE6D inhibitors suggests its higher potency. We show that inhibition of K-Ras membrane anchorage and K-RasG12C-dependent MAPK-signaling by SNAP-STI is weak, consistent with what is observed after PDE6D knockdown. Our data therefore further support that PDE6D is not a suitable surrogate target for efficient inhibition of K-Ras membrane anchorage and MAPK-activity. Nonetheless, by exploiting contacts at the pocket entry, we established a generalizable strategy to design high-affinity PDE6D inhibitors, providing powerful tools for PDE6D biology and target validation.
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 | 0.001 |
| 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".