A transient amphipathic helix in the prodomain of PCSK9 facilitates binding to low-density lipoprotein particles
Bibliographic record
Abstract
Proprotein convertase subtilisin/kexin type-9 (PCSK9) is a ligand of low-density lipoprotein (LDL) receptor (LDLR) that promotes LDLR degradation in late endosomes/lysosomes. In human plasma, 30–40% of PCSK9 is bound to LDL particles; however, the physiological significance of this interaction remains unknown. LDL binding in vitro requires a disordered N-terminal region in PCSK9's prodomain. Here, we report that peptides corresponding to a predicted amphipathic α-helix in the prodomain N terminus adopt helical structure in a membrane-mimetic environment. This effect was greatly enhanced by an R46L substitution representing an atheroprotective PCSK9 loss-of-function mutation. A helix-disrupting proline substitution within the putative α-helical motif in full-length PCSK9 lowered LDL binding affinity >5-fold. Modeling studies suggested that the transient α-helix aligns multiple polar residues to interact with positively charged residues in the C-terminal domain. Gain-of-function PCSK9 mutations associated with familial hypercholesterolemia (FH) and clustered at the predicted interdomain interface (R469W, R496W, and F515L) inhibited LDL binding, which was completely abolished in the case of the R496W variant. These findings shed light on allosteric conformational changes in PCSK9 required for high-affinity binding to LDL particles. Moreover, the initial identification of FH-associated mutations that diminish PCSK9's ability to bind LDL reported here supports the notion that PCSK9-LDL association in the circulation inhibits PCSK9 activity.
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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) | 0.002 | 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".