Simplified assays of lipolysis enzymes for drug discovery and specificity assessment of known inhibitors
Bibliographic record
Abstract
Lipids are used as cellular building blocks and condensed energy stores and also act as signaling molecules. The glycerolipid/ fatty acid cycle, encompassing lipolysis and lipogenesis, generates many lipid signals. Reliable procedures are not available for measuring activities of several lipolytic enzymes for the purposes of drug screening, and this resulted in questionable selectivity of various known lipase inhibitors. We now describe simple assays for lipolytic enzymes, including adipose triglyceride lipase (ATGL), hormone sensitive lipase (HSL), sn-1-diacylglycerol lipase (DAGL), monoacylglycerol lipase, α/β-hydrolase domain 6, and carboxylesterase 1 (CES1) using recombinant human and mouse enzymes either in cell extracts or using purified enzymes. We observed that many of the reported inhibitors lack specificity. Thus, Cay10499 (HSL inhibitor) and RHC20867 (DAGL inhibitor) also inhibit other lipases. Marked differences in the inhibitor sensitivities of human ATGL and HSL compared with the corresponding mouse enzymes was noticed. Thus, ATGListatin inhibited mouse ATGL but not human ATGL, and the HSL inhibitors WWL11 and Compound 13f were effective against mouse enzyme but much less potent against human enzyme. Many of these lipase inhibitors also inhibited human CES1. Results describe reliable assays for measuring lipase activities that are amenable for drug screening and also caution about the specificity of the many earlier described lipase inhibitors.
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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 | 0.003 | 0.001 |
| 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".