Human Anti-V3 HIV-1 Monoclonal Antibodies Encoded by the VH5-51/VL Lambda Genes Define a Conserved Antigenic Structure
Bibliographic record
Abstract
Preferential usage of immunoglobulin (Ig) genes that encode antibodies (Abs) against various pathogens is rarely observed and the nature of their dominance is unclear in the context of stochastic recombination of Ig genes. The hypothesis that restricted usage of Ig genes predetermines the antibody specificity was tested in this study of 18 human anti-V3 monoclonal Abs (mAbs) generated from unrelated individuals infected with various subtypes of HIV-1, all of which preferentially used pairing of the VH5-51 and VL lambda genes. Crystallographic analysis of five VH5-51/VL lambda-encoded Fabs complexed with various V3 peptides revealed a common three dimensional (3D) shape of the antigen-binding sites primarily determined by the four complementarity determining regions (CDR) for the heavy (H) and light (L) chains: specifically, the H1, H2, L1 and L2 domains. The CDR H3 domain did not contribute to the shape of the binding pocket, as it had different lengths, sequences and conformations for each mAb. The same shape of the binding site was further confirmed by the identical backbone conformation exhibited by V3 peptides in complex with Fabs which fully adapted to the binding pocket and the same key contact residues, mainly germline-encoded in the heavy and light chains of five Fabs. Finally, the VH5-51 anti-V3 mAbs recognized an epitope with an identical 3D structure which is mimicked by a single mimotope recognized by the majority of VH5-51-derived mAbs but not by other V3 mAbs. These data suggest that the identification of preferentially used Ig genes by neutralizing mAbs may define conserved epitopes in the diverse virus envelopes. This will be useful information for designing vaccine immunogen inducing cross-neutralizing Abs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".