Binding of an Antibody Mimetic of the Human Low Density Lipoprotein Receptor to Apolipoprotein E Is Governed through Electrostatic Forces
Bibliographic record
Abstract
Monoclonal antibody 2E8 is specific for an epitope that coincides with the binding site of the low density lipoprotein receptor (LDLR) on human apoE. Its reactivity with apoE variants resembles that of the LDLR: it binds well with apoE3 and poorly with apoE2. The heavy chain complementarity-determining region (CDRH) 2 of 2E8 shows homology to the ligand-binding domain of the LDLR. To define better the structural basis of the 2E8/apoE interaction and particularly the role of electrostatic interactions, we generated and characterized a panel of 2E8 variants. Replacement of acidic residues in the 2E8 CDRHs showed that Asp(52), Glu(53), and Asp(56) are essential for high-affinity binding. Although Asp(31) (CDRH1), Glu(58) (CDRH2), and Asp(97) (CDRH3) did not appear to be critical, the Asp(97) --> Ala variant acquired reactivity with apoE2. A Thr(57) --> Glu substitution increased affinity for both apoE3 and apoE2. The affinities of wild-type 2E8 and variants for apoE varied inversely with ionic strength, suggesting that electrostatic forces contribute to both antigen binding and isoform specificity. We propose a model of the 2E8.apoE immune complex that is based on the 2E8 and apoE crystal structures and that is consistent with the apoE-binding properties of wild-type 2E8 and its variants. Given the similarity between the LDLR and 2E8 in terms of specificity, the LDLR/ligand interaction may also have an important electrostatic component.
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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) | 0.001 | 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".