Background Pathogenic coronaviruses include Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and SARS-CoV-2 . These viruses have induced outbreaks worldwide, and there are currently no effective medications against them . Therefore, there is an urgent need to develop potential drugs against coronaviruses . Methods High-throughput technology is widely used to explore differences in messenger (m) RNA and micro (mi) RNA expression profiles, especially to investigate protein-protein interactions and search for new therapeutic compounds . We integrated miRNA and mRNA expression profiles in MERS-CoV-infected cells and compared them to mock-infected controls from public databases . Results Through the bioinformatics analysis, there were 251 upregulated genes and eight highly differentiated miRNAs that overlapped in the two datasets . External validation verified that these genes had high expression in MERS-CoV-infected cells, including RC3H1, NF-κB, CD69, TNFAIP3, LEAP-2, DUSP10, CREB5, CXCL2, etc . We revealed that immune, olfactory or sensory system-related, and signal-transduction networks were discovered from upregulated mRNAs in MERS-CoV-infected cells . In total , 115 genes were predicted to be related to miRNAs, with the intersection of upregulated mRNAs and miRNA-targeting prediction genes such as TCF4, NR3C1, and POU2F2 . Through the Connectivity Map (CMap) platform, we suggested potential compounds to use against MERS-CoV infection, including diethylcarbamazine, harpagoside, bumetanide, enalapril, and valproic acid . Conclusions The present study illustrates the crucial roles of miRNA-mRNA interacting networks in MERS-CoV-infected cells . The genes we identified are potential targets for treating MERS-CoV infection; however, these could possibly be extended to other coronavirus infections.