The molecular basis of Plasmodium falciparum merozoite invasion inhibition via anti-PfCyRPA antibodies
Bibliographic record
Abstract
Plasmodium falciparum, the pathogen responsible for the deadliest form of malaria, continues to exact an immense human toll, disproportionality shouldered by countries in sub-Saharan Africa. Significant progress has been made this century in reducing global malaria mortality and morbidity, but these gains remain fragile. The development of a malaria vaccine that protects against clinical disease would be an invaluable addition to the malaria control toolkit, but has remained elusive to date. As a result, the search for new, more potent vaccine antigens continues. Emerging from these efforts was the identification of the PfRH5:PfCyRPA:PfRipr complex (RCR), which is essential for merozoite invasion into the host erythrocyte. Here, a new panel of anti-PfCyRPA antibodies are evaluated for their ability to block merozoite invasion, including two new mAbs that are the most potently inhibitory anti-PfCyRPA mAbs described to-date. Structural studies revealed a single critical face of PfCyRPA that elicits neutralizing antibodies, where all four of the newly described inhibitory mAbs bound, opening the door for further studies on synthetic PfCyRPA immunogens that can focus the immune response on this vulnerable region of PfCyRPA. Finally, studies of synergy and antagonism between pairs of anti-PfCyRPA mAbs revealed that non-competing inhibitory anti-PfCyRPA mAbs potently synergize with each other. A novel mechanism of synergy to explain this observation was described, whereby lateral interactions between adjacent antibody Fab arms stabilize and enhance antibody affinity for PfCyRPA. Together, these data can inform the design of the next generation of malaria therapeutics.
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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 | 0.001 |
| 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".