Emerging viruses pose significant challenges to human health, as exemplified by the current COVID19 pandemic. However, in addition to SARS-CoV-2, new viruses emerge each year and recently emerged viruses continue to pose threats. The focus of this project, the Ebola virus (EBOV), has continued to cause sporadic outbreaks since the largest outbreak in 2014. As recently as February 2021, two additional deaths were reported. EBOV, as with all viruses, is an obligate intracellular parasites that is both dependent upon cellular proteins for its replication and susceptible to inhibition by cellular antiviral responses. To promote their own replication and to overcome the cellular defenses, virus proteins interact with both viral and cellular proteins. Over the last decade, dozens of published studies have reported thousands of virus protein-protein interactions (PPIs). However, the vast majority of these interactions have not been characterized and choosing which interactions to prioritize for focused, hypothesis driven follow up experiments is often a challenging task. Better tools are needed to identify critical virus PPIs. To address this gap, in this project we develop an innovative, generally applicable approach to comprehensively identify virus peptides that can disrupt virus PPIs and inhibit virus replication. Our hypothesis is that critical virus-virus and virus-host cell PPIs are mediated by short linear interaction domains that can dominantly interfere with virus replication when expressed in host cells. Published reports from EBOV and several other viruses provide support for this hypothesis. For example, short proline-rich sequences from the EBOV nucleoprotein NP or from cellular proteins such as RBBP6 bind to EBOV VP30. Expressing these peptides in mammalian cells as fusions to GFP disrupts the interaction between NP and VP30 and inhibits EBOV replication. Here, we propose to systematically identify similar peptides using tiled peptide libraries containing all possible 30-mer EBOV peptides. In aim 1, we generate these peptide libraries as N- and C-terminal fusions to GFP and express them in cells that are sensitive to EBOV-induced cytopathic effect. Cells expressing inhibitory peptides will suppress EBOV replication and be more likely to survive, thus increasing in frequency in the population. These peptides will be identified by deep sequencing the pre- and post-infection populations to find those whose abundance increases. In aim 2, we verify the inhibitory effect of these peptides and evaluate their impact on interactions with viral and cellular proteins. Successful completion of this project will yield a high-resolution, genome-wide map of EBOV protein interaction domains that are most susceptible to disruption, as well as improved tools to rapidly characterize newly emerged viruses. The data from this project will enhance our understanding of EBOV replication and may lead the identification of new drug targets.