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Short linear motifs (SLiMs) are protein-protein interaction sites that play an essential role in distinct cellular processes. Those interactions are challenging to capture by common high-throughput methods. Therefore, we established an improved version of Proteomic Peptide Phage Display (ProP-PD) as a dedicated method to identify SLiM-based interactions. ProP-PD libraries were created for the discovery of endogenous and host-pathogen protein-protein interactions. The M13 bacteriophage libraries present 16 amino acid long peptides from the intrinsically disordered regions (IDRs) of the human (HD2) proteome or the proteomes of RNA viruses (RiboVD). Through benchmarking of the approach using 35 well-known SLiMs binding domains and the HD2 library, we defined parameters for assigning confidence levels to the results. The selections against the HD2 library revealed >2000 SLiMs-based interaction pairs. Regarding host-pathogen interactions, we focused on interactions mediated by coronavirus proteins, exploring how human proteins bind to viral peptides and how viral proteins bind to human SLiMs. By screening more than 130 human bait proteins against the RiboVD, we revealed several host proteins potentially being targeted by SARS-CoV-2 proteins. Viral hijacking of human G3BP1/2 by the N-protein from SARS-CoV-2 impacted stress granule formation, and inhibition of the interaction was found to have an antiviral effect. Using SARS-CoV-2 proteins in selections with our HD2 library, we found that viral proteins may bind host SLiMs. Selected interactions were validated via affinity measurements revealing a wide range of affinities. Finally, we uncovered that a peptide binding to the NSP9 has an antiviral effect. It is not always possible to establish binding determinants directly from ProP-PD derived peptides. Therefore, we developed a deep mutational scanning (DMS) by phage display protocol. To test the approach, we designed libraries in which all amino acid positions of binding peptides were individually mutated, and the effect on binding was investigated through peptide phage selection. The approach was validated against well-studied interactions and applied to SLiM-based interactions between human proteins and SARS-CoV-2 proteins. Based on the DMS by phage display data we could create a higher affinity binder for NSP9 with increased antiviral effects. The research presented in this thesis has established a platform for large-scale interaction screening through phage display. The results contribute to a deeper understanding of the SLiMs binding and function and also pinpoint novel potential targets for the development of antiviral agents.