Comprehensive Antigenic Map of a Cleaved Soluble HIV-1 Envelope Trimer
Bibliographic record
Abstract
The trimeric envelope (Env) spike is the focus of vaccine design efforts aimed at generating broadly neutralizing antibodies (bNAbs) to protect against HIV-1 infection. Three recent developments have facilitated a thorough investigation of the antigenic structure of the Env trimer: 1) the isolation of many bNAbs against multiple different epitopes; 2) the generation of a soluble trimer mimic, BG505 SOSIP.664 gp140, that expresses most bNAb epitopes; 3) facile binding assays involving the oriented immobilization of tagged trimers. Using these tools, we generated an antigenic map of the trimer by antibody cross-competition. Our analysis delineates three well-defined epitope clusters (CD4 binding site, quaternary V1V2 and Asn332-centered oligomannose patch) and new epitopes at the gp120-gp41 interface. It also identifies the relationships among these clusters. In addition to epitope overlap, we defined three more ways in which antibodies can cross-compete: steric competition from binding to proximal but non-overlapping epitopes (e.g., PGT151 inhibition of 8ANC195 binding); allosteric inhibition (e.g., PGT145 inhibition of 1NC9, 8ANC195, PGT151 and CD4 binding); and competition by reorientation of glycans (e.g., PGT135 inhibition of CD4bs bNAbs, and CD4bs bNAb inhibition of 8ANC195). We further demonstrate that bNAb binding can be complex, often affecting several other areas of the trimer surface beyond the epitope. This extensive analysis of the antigenic structure and the epitope interrelationships of the Env trimer should aid in design of both bNAb-based therapies and vaccines intended to induce bNAbs.
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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 | 0.000 |
| 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".