Catalytic Activity Is Not Required for Secreted PCSK9 to Reduce Low Density Lipoprotein Receptors in HepG2 Cells
Bibliographic record
Abstract
Proprotein convertase subtilisin/kexin type 9 (PCSK9), a member of the proteinase K subfamily of subtilases, promotes internalization and degradation of low density lipoprotein receptors (LDLRs) after binding the receptor on the surface of hepatocytes. PCSK9 has autocatalytic activity that releases the prodomain at the N terminus of the protein. The prodomain remains tightly associated with the catalytic domain as the complex transits the secretory pathway. It is not known whether enzymatic activity is required for the LDLR-reducing effects of PCSK9. Here we expressed the prodomain together with a catalytically inactive protease domain in cells and purified the protein from the medium. The ability of the catalytically inactive PCSK9 to bind and degrade LDLRs when added to culture medium of human hepatoma HepG2 cells at physiological concentrations was similar to that seen using wild-type protein. Similarly, a catalytic-dead version of a gain-of-function mutant, PCSK9(D374Y), showed no loss of activity compared with a catalytically active counterpart; both proteins displayed approximately 10-fold increased activity in degradation of cell surface LDLRs compared with wild-type PCSK9. We conclude that the ability of PCSK9 to degrade LDLRs is independent of catalytic activity and suggest that PCSK9 functions as a chaperone to prevent LDLR recycling and/or to target LDLRs for lysosomal degradation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".