Structural Characterization of a Low Density Lipoprotein Receptor-active Apolipoprotein E Peptide, ApoE3-(126–183)
Bibliographic record
Abstract
Apolipoprotein E (apoE) plays a critical role in lipoprotein particle clearance from blood plasma through its interaction with the low density lipoprotein (LDL) receptor and other related receptors. Here, we studied a 58-residue peptide encompassing the receptor binding region of apoE. ApoE3-(126-183) was generated by cyanogen bromide cleavage of recombinant apoE3-(1-183), purified by reversed-phase high pressure liquid chromatography, and characterized by mass spectrometry. Far UV CD spectroscopy of the peptide showed that it is unstructured in aqueous solution. The addition of trifluoroethanol or dodecylphosphocholine induces the peptide to adopt an alpha-helical conformation. ApoE3-(126-183) efficiently transforms dimyristoylphosphatidylglycerol (DMPG) vesicles into peptide-lipid complexes. Analysis of apoE3-(126-183). DMPG complexes by electron microscopy revealed disc-shaped particles with an average diameter of 13 +/- 3 nm. Flotation equilibrium analysis yielded a particle molecular mass of 252 kDa. Far UV CD analysis of apoE3-(126-183).DMPG discs provided evidence that the peptide adopts a helical conformation. Competition binding experiments with (125)I-labeled low density lipoprotein (LDL) were conducted to assess the ability of apoE3-(126-183).DMPG complexes to bind to the LDL receptor. Both N-terminal apoE and the peptide, when complexed with DMPG, competed with (125)I-LDL for binding sites on the surface of cultured human skin fibroblasts. Under the conditions employed, apoE3-(126-183).DMPG complexes were similar to apoE3-(1-183).DMPG discs in their ability to bind to the receptor, demonstrating that the peptide represents a good model to study the interaction between apoE and the LDL receptor. Preliminary NMR results indicated that a high resolution structure of the apoE3-(126-183) peptide is obtainable.
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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) | 0.000 | 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 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".