Crystal Structure of the Hendra Virus Attachment G Glycoprotein Bound to a Potent Cross-Reactive Neutralizing Human Monoclonal Antibody
Bibliographic record
Abstract
The henipaviruses, represented by Hendra (HeV) and Nipah (NiV) viruses are highly pathogenic zoonotic paramyxoviruses with uniquely broad host tropisms responsible for repeated outbreaks in Australia, Southeast Asia, India and Bangladesh. The high morbidity and mortality rates associated with infection and lack of licensed antiviral therapies make the henipaviruses a potential biological threat to humans and livestock. Henipavirus entry is initiated by the attachment of the G envelope glycoprotein to host cell membrane receptors. Previously, henipavirus-neutralizing human monoclonal antibodies (hmAb) have been isolated using the HeV-G glycoprotein and a human naïve antibody library. One cross-reactive and receptor-blocking hmAb (m102.4) was recently demonstrated to be an effective post-exposure therapy in two animal models of NiV and HeV infection, has been used in several people on a compassionate use basis, and is currently in development for use in humans. Here, we report the crystal structure of the complex of HeV-G with m102.3, an m102.4 derivative, and describe NiV and HeV escape mutants. This structure provides detailed insight into the mechanism of HeV and NiV neutralization by m102.4, and serves as a blueprint for further optimization of m102.4 as a therapeutic agent and for the development of entry inhibitors and vaccines.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".