Conformational Masking and Receptor-Dependent Unmasking of Highly Conserved Env Epitopes Recognized by Non-Neutralizing Antibodies That Mediate Potent ADCC against HIV-1
Bibliographic record
Abstract
The mechanism of antibody-mediated protection is a major focus of HIV-1 vaccine development and a significant issue in the control of viremia. Virus neutralization, Fc-mediated effector function, or both, are major mechanisms of antibody-mediated protection against HIV-1, although other mechanisms, such as virus aggregation, are known. The interplay between virus neutralization and Fc-mediated effector function in protection against HIV-1 is complex and only partially understood. Passive immunization studies using potent broadly neutralizing antibodies (bnAbs) show that both neutralization and Fc-mediated effector function provides the widest dynamic range of protection; however, a vaccine to elicit these responses remains elusive. By contrast, active immunization studies in both humans and non-human primates using HIV-1 vaccine candidates suggest that weakly neutralizing or non-neutralizing antibodies can protect by Fc-mediated effector function, albeit with a much lower dynamic range seen for passive immunization with bnAbs. HIV-1 has evolved mechanisms to evade each type of antibody-mediated protection that must be countered by a successful AIDS vaccine. Overcoming the hurdles required to elicit bnAbs has become a major focus of HIV-1 vaccine development. Here, we discuss a less studied problem, the structural basis of protection (and its evasion) by antibodies that protect only by potent Fc-mediated effector function.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".