HIV-1 neutralization tiers are not relevant for inhibitors targeting the pre-hairpin intermediate
Bibliographic record
Abstract
Abstract HIV-1 strains are categorized into one of three neutralization tiers based on the relative ease by which they are neutralized by plasma from HIV-1 infected donors not on antiretroviral therapy; tier-1 strains are particularly sensitive to neutralization while tier-2 and tier-3 strains are increasingly difficult to neutralize. Most broadly neutralizing antibodies (bnAbs) previously described target the native prefusion conformation of HIV-1 Envelope (Env), but the relevance of the tiered categories for inhibitors targeting another Env conformation, the pre-hairpin intermediate, is not well understood. Here we show that two inhibitors targeting distinct highly-conserved regions of the pre-hairpin intermediate have strikingly consistent neutralization potencies (within ∼100-fold for a given inhibitor) against strains in all three neutralization tiers of HIV-1; in contrast, best-in-class bnAbs targeting diverse Env epitopes vary by more than 10,000-fold in potency against these strains. Our results indicate that antisera-based HIV-1 neutralization tiers are not relevant for inhibitors targeting the pre-hairpin intermediate and highlight the potential for therapies and vaccine efforts targeting this conformation.
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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 | 0.001 |
| 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 | 0.001 | 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".