Characterization of desnutrin functional domains: critical residues for triacylglycerol hydrolysis in cultured cells
Bibliographic record
Abstract
Murine desnutrin/human ATGL is a triacylglycerol (TAG) hydrolase with a predicted catalytic dyad within an alpha-beta hydrolase fold in the N-terminal region. In humans, mutations resulting in C-terminal truncation cause neutral lipid storage disease with myopathy. To identify critical functional domains, we measured TAG breakdown in cultured cells by mutated or truncated desnutrin. In vitro, C-terminally truncated desnutrin displayed an even higher apparent V(max) than the full-length form without changes in K(m), which may be explained by our finding of an interaction between the C- and N-terminal domains. In live cells, however, C-terminally truncated adenoviral desnutrin had lower TAG hydrolase activity. We investigated a role for the phosphorylation of C-terminal S406 and S430 residues but found that these were not necessary for TAG breakdown or lipid droplet localization in cells. The predicted N-terminal active sites, S47 and D166, were both critical for TAG hydrolysis in live cells and in vitro. We also identified two overlapping N-terminal motifs that predict lipid substrate binding domains, a glycine-rich motif (underlined) and an amphipathic alpha-helix (bold) within amino acid residues 10-24 (ISFAGCGFLGVYHIG). G14, F17, L18, and V20, but not G16 and G19, were important for TAG hydrolysis, suggesting a potential role for the amphipathic alpha-helix in TAG binding. This study identifies for the first time critical sites in the N-terminal region of desnutrin and reveals the requirement of the C-terminal region for TAG hydrolysis in cultured cells.
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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 | 0.000 |
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 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".