Seeking to inform development of drugs effective against multiple pathogenic human coronaviruses, David E. Gordon and colleagues compared host interactions of MERS-CoV, SARS-CoV-1 and SARS-CoV-2, uncovering host pathways commonly hijacked by all three. Studying patient data showed how COVID-19 patients treated with drugs that acted against selected coronavirus host factors fared, with results that will help guide COVID-19 drug targets, the authors say. SARS-CoV-2, which causes COVID-19, is closely related to the deadly coronaviruses SARS-CoV-1 and MERS-CoV. Significant efforts are focused on developing treatments for COVID-19 but given that other highly virulent human coronavirus strains have emerged and may do so again, therapies that work across coronaviruses would also be valuable. While traditional antivirals target viral enzymes that are often subject to mutation, and thus to the development of drug resistance, targeting the host proteins required for viral replication is a strategy that can avoid resistance and lead to therapeutics with broad-spectrum activity. Focused on this approach, Gordon et al. mapped the interactions between viral and human proteins for SARS-CoV-2, SARS-CoV-1 and MERS-CoV. After expressing viral proteins in human cells, they used mass spectrometry to identify human host proteins that physically associated with each viral protein, looking for conserved interactions across all three viruses. They then used genetic screening to identify host factors that either enhanced or inhibited viral infection. To connect their in vitro molecular data to clinical information for COVID-19 patients, the authors evaluated medical billing data on nearly 740,000 patients in the United States with documented SARS-CoV-2 infection. In this cohort, they studied the use of drugs against selected targets identified in their study, asking whether patients who received them fared better than controls treated with clinically similar drugs that do not act on coronavirus host factors. Patients that received drugs focused against certain selected targets fared better in some cases, the authors report. "Replication in other patient cohorts and further work will be needed to see if there is therapeutic value in these connections," say Gordon et al., "but at the very least we have demonstrated a strategy wherein protein network analyses can be used to make testable predictions from real-world, clinical information."