PCSK9 Prosegment Chimera as Novel Inhibitors of LDLR Degradation
Bibliographic record
Abstract
The proprotein convertase PCSK9, a target for the treatment of hypercholesterolemia, is a negative regulator of the LDL receptor (LDLR) leading to its degradation in endosomes/lysosomes and up-regulation of plasma LDL-cholesterol levels. The proprotein convertases, a family of nine secretory serine proteases, are first synthesized as inactive zymogens. Except for PCSK9, all other convertases are activated following the autocatalytic excision of their inhibitory N-terminal prosegment. PCSK9 is unique since the mature enzyme exhibits a cleaved prosegment complexed with the catalytic subunit and has no protease activity towards other substrates. Similar to other convertases, we hypothesized that the in trans presence of the PCSK9 prosegment would interfere with PCSK9's activity on the LDLR. Since the prosegment cannot be secreted alone, we engineered a chimeric protein using the Fc-region of human IgG1 fused to the PCSK9 prosegment. The expression of such Fcpro-fusion protein in HEK293 and HepG2 cells resulted in a secreted protein that binds PCSK9 and markedly inhibits its activity on the LDLR. This was observed by either intracellular co-expression of PCSK9 and Fcpro or by an extracellular in vitro co-incubation of Fcpro with PCSK9. Structure-function studies revealed that the inhibitory function of Fcpro does not require the acidic N-terminal stretch (residues 31-58) nor the C-terminal Gln 152 of the prosegment. Fcpro likely interacts with the prosegment and/or catalytic subunit of the prosegment≡PCSK9 complex thereby allosterically modulating its function. Our data suggest a novel strategic approach for the design and isolation of PCSK9 inhibitors.
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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 | 0.001 |
| 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".