Understanding how viruses engage host cell surfaces is fundamental to infection biology and therapeutic development. While vaccines remain central to prevention, recent global crises have emphasized the need for complementary antiviral strategies that can be mobilized rapidly against both known and emerging pathogens. In this context, artificial intelligence (AI) systems for biomolecular structure prediction, culminating in AlphaFold 3, are reshaping what is experimentally and conceptually achievable. Here, we present “Interactys-AI”, a framework designed to exploit AI-based structural modeling to systematically map virus–host protein–protein interactions (PPIs) and connect them to actionable drug repurposing opportunities. Beyond a technical workflow, Interactys-AI reflects a broader transformation toward predictive and anticipatory antiviral discovery. We describe the conceptual foundations of the platform, its implementation, and its application to influenza A H5N1 hemagglutinin. We further discuss how structural AI may redefine preparedness strategies, highlight current limitations, and outline future directions toward real-time therapeutic hypothesis generation.
Poitras et al. (2026) studied this question.