P-C3 Targeting the epitopes in the C1-C2 region of HIV-1 gp120 for effective Fc-mediated effector function
Bibliographic record
Abstract
Accumulating evidence indicates a role for Fc receptor (FcR)-mediated effector functions of antibodies, including antibody-dependent cell- mediated cytotoxicity (ADCC), in prevention of HIV-1 acquisition and in post-infection control of viremia. Consequently, an understanding of the molecular basis for Env epitopes that constitute effective ADCC targets is of fundamental interest for humoral anti-HIV-1 immunity and for HIV-1 vaccine design. A substantial portion of FcR-effector function of potentially protective anti-HIV-1 antibodies is directed toward non-neutralizing, transitional, CD4-induceable (CD4i) epitopes associated with the gp41 reactive region of gp120 (Cluster A epitopes). Our previous studies defined two highly conserved epitope sub-groups within the Cluster A region; the A32-like epitope which maps to the mobile layers 1 and 2 within C1- C2 regions of gp120 and a hybrid A32-C11-like epitope which maps to elements of both the A32-like sub-region and the 7 layered β-sheet of the gp41-interactive region of gp120. Here we elucidate the structural basis for antigen engagement into an effective immune-complex that leads to potent ADCC function to the Cluster A region. We also present the structure based design of an independent inner domain molecule, ID, an immunogen candidate stably expressing the Cluster A epitopes involved in potent FcR-effector function to HIV-1 within a minimal structural unit of gp120.
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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 | 0.000 |
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".