Structure guided mimicry of an essential P. falciparum receptor-ligand complex enhances cross neutralizing antibodies
Bibliographic record
Abstract
Abstract Invasion of human erythrocytes by Plasmodium falciparum ( Pf ) merozoites relies on the interaction between two parasite proteins: apical membrane antigen 1 (AMA1) and rhoptry neck protein 2 (RON2). While antibodies to AMA1 provide limited protection against Pf in non-human primate malaria models, clinical trials using recombinant AMA1 alone (apoAMA1) yielded no protection due to insufficient functional antibodies. Immunization with AMA1 bound to RON2L, a 49-amino acid peptide from its ligand RON2, has shown superior protection by increasing the proportion of neutralizing antibodies. However, this approach relies on the formation of a complex in solution between the two vaccine components. To advance vaccine development, here we engineered chimeric antigens by replacing the AMA1 DII loop, displaced upon ligand binding, with RON2L. Structural analysis confirmed that the fusion chimera (Fusion-F D12 ) closely mimics the binary AMA1-RON2L complex. Immunization studies in female rats demonstrated that Fusion-F D12 immune sera, but not purified IgG, neutralized vaccine-type parasites more efficiently compared to apoAMA1, despite lower overall anti-AMA1 titers. Interestingly, Fusion-F D12 immunization enhanced antibodies targeting conserved epitopes on AMA1, leading to increased neutralization of non-vaccine type parasites. Identifying these cross-neutralizing antibody epitopes holds promise for developing an effective, strain-transcending malaria vaccine.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".