Promotion of the neutralization-competent structure of the HIV-1 gp41 membrane proximal external region when tethered to its native transmembrane domain, and expressed in the context of the plasma membrane: implications for vaccine design (53.24)
Bibliographic record
Abstract
Abstract The limited success of vaccines targeting the MPER, a target of three broadly neutralizing (bNt) monoclonal antibodies (MAbs), we hypothesize, reflects the difficulty of mimicking the neutralization-competent structure (NCS) of the MPER. We determined the contribution of the amino-acid sequence and the transmembrane domain (TM), to the antigenicity of the MPER in the context of the plasma membrane. DNA constructs encoding various gp41 ectodomain fragments, and the TM of either the platelet-derived growth factor receptor (PGDFR), or that of gp41, were produced and transiently expressed in COS-7 cells. Constructs expressing the MPER tethered to the gp41 TM followed by a 27-residue cytoplasmic tail fragment, MPER-TM1, produced optimal binding of MAbs 2F5, 4E10 and Z13e1. A series of 24 single amino-acid substitutions in the MPER-TM1 revealed critical binding residues for the three MAbs; similar substitutions were previously shown to ablate Ab-mediated viral neutralization. Neutralization-incompetent 2F5 Fab and 4E10 IgG mutant Abs failed to bind MPER-TM1, yet retained the ability to bind to peptide epitopes, indicating the plasma-membrane expressed MPER-TM1 closely approaches the NCS of the MPER. Substitution of the TM of gp41 with that from the PGDFR reduced binding by MAb 4E10, but not MAbs 2F5 or Z13e1. Our studies reveal that the gp41 TM appears to play a pivotal role both in orienting the 4E10 epitope, and affecting exposure of the MPER epitopes for all three bNtMAbs.
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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".