Inducing protective antibody response to HIV-1 with inner domain of gp120
Bibliographic record
Abstract
Recent nonhuman primate studies and clinical trials suggest that antibody-mediated protection against HIV-1 will require anti-envelope (Env) humoral immunity beyond direct neutralization, to include Fc-receptor effector functions such as antibody-dependent cellular cytotoxicity (ADCC).In parallel, strong evidence points toward the transitional and non-neutralizing A32-like epitopes (Cluster A) of HIV-1 Env as major targets for potent ADCC responses.We were first to define these epitope targets at atomic level by describing structures of several A32-like antibodies in complexes with CD4-triggered gp120.Our studies mapped the A32-epitope into mobile layers 1 and 2 of the inner domain (ID) of CD4-triggered gp120.Here, we describe a stable molecule expressing the C1-C2 region epitopes within a minimal structural unit of HIV-1 Env.Through two phases of structure-based design we developed a construct, referred to as ID2, which consists of the inner domain of gp120 expressed independently of the outer domain and stabilized in the CD4-bound conformation by an inter-layer disulfide bond.Each phase of the design process was visualized and validated at the molecular level by structural analysis of ID variants complexed with anti-Cluster A antibodies as well as by functional testing.Our data indicate that ID2 expresses the C1-C2 epitopes involved in potent ADCC within the context of a CD4triggered full-length gp120, but without the complication of other epitope regions.Thus, ID2 represents a novel candidate probe for the analysis and/or selective induction of antibody responses to the A32 epitope sub-region.We also present the crystal structure of ID2 complexed with mAb A32, the canonical antibody of the Cluster A region.This represents the first structural analysis of mAb A32 bound by its Env antigen defining its epitope.
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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".