A Novel Diacylglycerol-lactone Shows Marked Selectivity in Vitro among C1 Domains of Protein Kinase C (PKC) Isoforms α and δ as Well as Selectivity for RasGRP Compared with PKCα
Bibliographic record
Abstract
Although multiple natural products are potent ligands for the diacylglycerol binding C1 domain of protein kinase C (PKC), RasGRP, and related targets, the high conservation of C1 domains has impeded the development of selective ligands. We characterized here a diacylglycerol-lactone, 130C037, emerging from a combinatorial chemical synthetic strategy, which showed substantial selectivity. 130C037 gave shallow binding curves for PKC isoforms alpha, beta, gamma, delta, and epsilon, with apparent Ki values ranging from 340 nm for PKCalpha to 29 nm for PKCepsilon. When binding to isolated C1 domains of PKCalpha and -delta, 130C037 showed good affinity (Ki= 1.78 nm) only for deltaC1b, whereas phorbol 12,13-dibutyrate showed affinities within 10-fold for all. In LNCaP cells, 130C037 likewise selectively induced membrane translocation of deltaC1b. 130C037 bound intact RasGRP1 and RasGRP3 with Ki values of 3.5 and 3.8 nm, respectively, reflecting 8- and 90-fold selectivity relative to PKCepsilon and PKCalpha. By Western blot of Chinese hamster ovary cells, 130C037 selectively induced loss from the cytosol of RasGRP3 (ED50 = 286 nm), partial reduction of PKCepsilon (ED50 > 10 microm), and no effect on PKCalpha. As determined by confocal microscopy in LNCaP cells, 130C037 caused rapid translocation of RasGRP3, limited slow translocation of PKCepsilon, and no translocation of PKCalpha. Finally, 130C037 induced Erk phosphorylation in HEK-293 cells ectopically expressing RasGRP3 but not in control cells, whereas phorbol ester induced phosphorylation in both. The properties of 130C037 provide strong proof of principle for the feasibility of developing ligands with selectivity among C1 domain-containing therapeutic targets.
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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 | 0.000 | 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) | 0.001 | 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".