Peptides Designed To Spatially Depict the Epstein-Barr Virus Major Virion Glycoprotein gp350 Neutralization Epitope Elicit Antibodies That Block Virus-Neutralizing Antibody 72A1 Interaction with the Native gp350 Molecule
Bibliographic record
Abstract
UNLABELLED: Epstein-Barr virus (EBV) is the etiologic agent of infectious mononucleosis and the root cause of B-cell lymphoproliferative disease in individuals with a weakened immune system, as well as a principal cofactor in nasopharyngeal carcinoma, various lymphomas, and other cancers. The EBV major virion surface glycoprotein gp350 is viewed as the best vaccine candidate to prevent infectious mononucleosis in healthy EBV-naive persons and EBV-related cancers in at-risk individuals. Previous epitope mapping of gp350 revealed only one dominant neutralizing epitope, which has been shown to be the target of the monoclonal antibody 72A1. Computer modeling of the 72A1 antibody interaction with the gp350 amino terminus was used to identify gp350 amino acids that could form strong ionic, electrostatic, or hydrogen bonds with the 72A1 antibody. Peptide DDRTTLQLAQNPVYIPETYPYIKWDN (designated peptide 2) and peptide GSAKPGNGSYFASVKTEMLGNEID (designated peptide 3) were designed to spatially represent the gp350 amino acids predicted to interact with the 72A1 antibody paratope. Peptide 2 bound to the 72A1 antibody and blocked 72A1 antibody recognition of the native gp350 molecule. Peptide 2 and peptide 3 were recognized by human IgG and shown to elicit murine antibodies that could target gp350 and block its recognition by the 72A1 antibody. This work provides a structural mapping of the interaction between the EBV-neutralizing antibody 72A1 and the major virion surface protein gp350. gp350 mimetic peptides that spatially depict the EBV-neutralizing epitope would be useful as a vaccine to focus the immune system exclusively to this important virus epitope. IMPORTANCE: The production of virus-neutralizing antibodies targeting the Epstein-Barr virus (EBV) major surface glycoprotein gp350 is important for the prevention of infectious mononucleosis and EBV-related cancers. The data presented here provide the first in silico map of the gp350 interaction with a virus-blocking monoclonal antibody. Immunization with gp350 peptides identified by in silico mapping generated antibodies that cross-react with the EBV gp350 molecule and block recognition of the gp350 molecule by a virus-neutralizing antibody. Through its ability to focus the immune system exclusively on the gp350 sequence important for viral entry, these peptides may form the basis of an EBV vaccine candidate. This strategy would sidestep the production of other irrelevant gp350 antibodies that divert the immune system from generating a protective antiviral response or that impede access to the virus-blocking epitope by protective antibodies.
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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) | 0.000 | 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".