Conserved metabolic vulnerabilities across pathogenic coronaviruses nominate host-directed therapeutic targets

Pathogenic coronaviruses profoundly rewire host cell metabolism to support viral replication, yet whether these metabolic alterations expose shared and actionable vulnerabilities remains unclear. By integrating transcriptomic profiles from cells infected with SARS-CoV, SARS-CoV-2, and MERS-CoV with genome-scale metabolic models, we identify conserved and virus-specific metabolic perturbations affecting mitochondrial transport, nucleotide biosynthesis, fatty acid metabolism, and redox balance. Despite distinct transcriptional responses, all three viruses converge on a limited set of metabolic reactions whose flux ranges deviate strongly from healthy states. Using a network-based predictive framework, we systematically identify gene-pair perturbations that restore perturbed reaction fluxes toward non-infected metabolic states. Predicted rescue mechanisms reveal shared metabolic dependencies across coronaviruses, as well as time-dependent virus-specific vulnerabilities, and nominate druggable host targets. Notably, several top predictions align with independent experimental and clinical evidence, including metabolic interventions shown to reduce viral replication or disease severity in COVID-19 patients. Together, our results define conserved metabolic rescue pathways in coronavirus infection and provide a general strategy for identifying host-directed therapeutic opportunities from transcriptomic data. HighlightsO_LICoronaviruses converge on shared metabolic vulnerabilities in host cells C_LIO_LINiTRO predicts gene pairs that rescue viral-induced metabolic states C_LIO_LIMitochondrial transport emerges as a key pan-coronavirus target C_LIO_LITop predictions validated by clinical trials and in vitro evidence C_LI eTOC BlurbDohai et al. develop NiTRO, a network-based algorithm that integrates coronavirus-induced transcriptomic changes with genome-scale metabolic models to identify gene-pair perturbations capable of rescuing infected metabolic states. The approach reveals shared and virus-specific druggable metabolic vulnerabilities, with top predictions corroborated by clinical evidence.