The Basis of the Substrate Specificity of the Epsilon Isoform of Human Diacylglycerol Kinase is not a Consequence of Competing Hydrolysis of ATP
Bibliographic record
Abstract
The diacylglycerol kinase from E. coli transfers some of the γ‐phosphate of ATP to water as well as to diacylglycerol. We also demonstrate that glycerol can act as an acceptor for the phosphate of ATP. We have compared this behavior with that of the only mammalian isoform of diacylglycerol kinase that exhibits acyl chain specificity, i.e. DGKε. The purpose of the study was to determine if differences in the competition between ATPase activity and lipid phosphorylation could contribute to the observed acyl chain specificity with different diacylglycerols. Neither with the highly specific substrate of DGKε, 1‐stearoyl‐2‐arachidonoyl glycerol, nor with a less specific substrate, 1‐stearoyl‐2‐linoleoyl glycerol, is there any evidence for ATP hydrolysis accompanying substrate phosphorylation. Thus, at least for this isoform of diacylglycerol kinase, water does not compete with diacylglycerol as an acceptor of the γ‐phosphate of ATP. The results demonstrate that the substrate specificity of mammalian DGKε is not a consequence of different degrees of ATP hydrolysis in the presence of different species of diacylglycerol. This work was supported by a grant from the Natural Sciences and Engineering Council of Canada, 9848.
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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".