Identification and Evaluation of a Highly Effective Fusion Inhibitor for Human Metapneumovirus
Bibliographic record
Abstract
Human metapneumovirus (hMPV) can cause acute upper and lower respiratory tract infections that are particularly severe in young children, elderly subjects, and immunocompromised patients. To date, no treatments or vaccines are available for hMPV infections. Our objective was to assess the inhibitory potential of several peptides derived from the heptad repeat A and B (HRA and HRB) domains of the hMPV fusion protein. Nine candidate peptides were expressed in Escherichia coli or obtained synthetically and tested in vitro and in an animal model. Excellent in vitro inhibition of an hMPV strain of the A1 subgroup was obtained with five peptides, with 50% inhibitory concentrations ranging from 1.4 nM to 3.3 microM. One peptide, HRA2, displayed very potent activity against all four hMPV subgroups. It was also moderately active against human respiratory syncytial virus (strain A2) but displayed no activity against human parainfluenza virus type 3. BALB/c mice that received the HRA2 peptide and a lethal hMPV intranasal challenge simultaneously were completely protected from clinical symptoms and mortality. On day 5 postinfection, HRA2-treated mice had undetectable lung viral loads which were significantly less than those of untreated mice (3 x 10(4) 50% tissue culture infective doses/lung). Pulmonary inflammation, levels of proinflammatory cytokines/chemokines (RANTES, gamma interferon, and monocyte chemoattractant protein 1) and airway obstruction were also significantly decreased in HRA2-treated mice. The results of this study demonstrate that potent antivirals can be derived from the hMPV fusion protein HR domains. Moreover, hMPV, compared to other paramyxoviruses and to the human immunodeficiency virus, seems to be more susceptible to HRA- than HRB-derived peptides.
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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 | 0.001 |
| 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".