ArticleViruses2025
AI-Powered Identification of Human Cell Surface Protein Interactors of the Hemagglutinin Glycoprotein of High-Pandemic-Risk H5N1 Influenza Virus.
Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
2 authors.
Funding
Abstract
H5N1 is a highly pathogenic avian influenza virus of major global concern. Since 2023, it has circulated widely among wild and farmed birds, with increasing spillover into mammals, including minks, seals, and cattle, and sporadic infections in humans in Chile, the UK, and the USA. The risk of a future pandemic is considered high because ongoing viral evolution could enable efficient human-to-human transmission. The hemagglutinin (HA) glycoprotein is the principal determinant of host range, mediating viral attachment and entry through interactions with sialylated glycans and potentially additional host surface proteins. Here, we developed an artificial intelligence (AI)-based pipeline integrating structural modeling, protein-protein interaction prediction, and biological filtering to identify human cell surface proteins with high likelihood of interacting with H5N1 HA. These interactions may contribute to viral entry and tropism and therefore represent promising candidates for experimental validation and therapeutic targeting. Our findings highlight the utility of AI-driven pipelines in accelerating the discovery of host factors relevant to pandemic influenza viruses.
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