Anti-V3 Monoclonal Antibodies Display Broad Neutralizing Activities against Multiple HIV-1 Subtypes
Bibliographic record
Abstract
BACKGROUND: The V3 loop of the HIV-1 envelope (Env) glycoprotein gp120 was identified as the "principal neutralizing domain" of HIV-1, but has been considered too variable to serve as a neutralizing antibody (Ab) target. Structural and immunochemical data suggest, however, that V3 contains conserved elements which explain its role in binding to virus co-receptors despite its sequence variability. Despite this evidence of V3 conservation, the ability of anti-V3 Abs to neutralize a significant proportion of HIV-1 isolates from different subtypes (clades) has remained controversial. METHODS: HIV-1 neutralization experiments were conducted in two independent laboratories to test human anti-V3 monoclonal Abs (mAbs) against pseudoviruses (psVs) expressing Envs of diverse HIV-1 subtypes from subjects with acute and chronic infections. Neutralization was defined by 50% inhibitory concentrations (IC(50)), and was statistically assessed based on the area under the neutralization titration curves (AUC). RESULTS: Using AUC analyses, statistically significant neutralization was observed by >or=1 anti-V3 mAbs against 56/98 (57%) psVs expressing Envs of diverse subtypes, including subtypes A, AG, B, C and D. Even when the 10 Tier 1 psVs tested were excluded from the analysis, significant neutralization was detected by >or=1 anti-V3 mAbs against 46/88 (52%) psVs from diverse HIV-1 subtypes. Furthermore, 9/24 (37.5%) Tier 2 viruses from the clade B and C standard reference panels were neutralized by >or=1 anti-V3 mAbs. Each anti-V3 mAb tested was able to neutralize 28-42% of the psVs tested. By IC(50) criteria, 40/98 (41%) psVs were neutralized by >or=1 anti-V3 mAbs. CONCLUSIONS: Using standard and new statistical methods of data analysis, 6/7 anti-V3 human mAbs displayed cross-clade neutralizing activity and revealed that a significant proportion of viruses can be neutralized by anti-V3 Abs. The new statistical method for analysis of neutralization data provides many advantages to previously used analyses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".