Rapid discovery of antiviral targets through dimensionality reduction of genome-scale metabolic models

The COVID-19 pandemic underscored the urgent need for rapid and broadly applicable strategies to identify antiviral targets against emerging pathogens. Conventional approaches, which rely on detailed viral characterization and large-scale drug screening, are too slow to address this challenge. Here, we introduce a transcriptome-based computational framework that integrates genome-scale metabolic models with dimensionality reduction to uncover host metabolic vulnerabilities that support viral replication. Applying this approach to bulk and single-cell RNA-seq data from HCoV-OC43-infected cells and organoids identified oxidative phosphorylation as a key vulnerability, and pharmacological inhibition of complex I effectively curtailed viral replication. Extending the framework to SARS-CoV-2 and MERS-CoV revealed pyrimidine catabolism as a conserved antiviral pathway, with inhibition of its rate-limiting enzyme DPYD suppressing replication in organoid models. Re-analysis of SARS-CoV-2 patient metabolome data further confirmed elevated DPYD activity, underscoring its clinical relevance. Together, these findings establish a generalizable and rapid strategy for host-directed antiviral discovery, providing a foundation for precision therapeutics and pandemic preparedness. Significance StatementHost-directed antiviral therapies offer several advantages in antiviral research, but identifying key host factors poses a significant challenge. By integrating genome-scale metabolic models with single-gene knockout simulation and dimensionality reduction, we developed a computational framework based on single and bulk RNA-seq data that can systematically pinpoint host pathways whose downregulation is predicted to rewire virus-induced metabolic alterations. Applying this approach to multiple human coronaviruses reveals unique metabolic vulnerabilities, and we experimentally demonstrate that inhibiting these host metabolic pathways reduces viral replication. This framework provides a generalizable antiviral strategy to discern effective targets and can be further extended to investigate virus-host metabolic interactions.