Molecular basis for epitope recognition by non-neutralizing anti-gp41 antibody F240
Bibliographic record
Abstract
Antibody-dependent cell-mediated cytotoxicity (ADCC) by non-neutralizing antibodies (nnAbs) specific to the HIV envelope (Env) glycoproteins present at the surface of virus sensitized or infected cells plays a role in the effective adaptive immune response to HIV. Here, we explore the molecular basis for the epitope at the disulfide loop region (DLR) of the principal immunodominant domain of gp41, recognized by the well-known nnAb F240. Our structural studies reveal details of the F240-gp41 interface and describe a structure of DLR that is distinct from known conformations of this region studied in the context of either CD4-unliganded Env trimer or the gp41 peptide in the unbound state. These data coupled with binding and functional analyses indicate that F240 recognizes non-trimeric Env forms which are significantly overexpressed on intact virions but poorly represented at surfaces of cells infected with infectious molecular clones and endogenously-infected CD4 T cells from HIV-1-infected individuals. Furthermore, although we detect ADCC activities of F240 against cells spinoculated with intact virions, our data suggest that these activities result from F240 recognition of gp41 stumps or misfolded Env variants present on virions rather than its ability to recognize functional gp41 transition structures emerging on trimeric Env post CD4 receptor engagement.
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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".