Comprehensive Prediction of the SARS-CoV-2 vs. Human Interactome using PIPE4, SPRINT, and PIPE-Sites

Understanding the disease pathogenesis of the novel coronavirus, denoted SARS-CoV-2, is critical to the development of anti-SARS-CoV-2 therapeutics. To that end, we leverage two state-of-the-art, sequence-based PPI predictors (PIPE4 SPRINT) capable of generating the comprehensive SARS-CoV-2 vs. human interactome, comprising 285,124 pairwise predictions. Of these, we identify the conservative high-scoring subset of human proteins predicted to interact with each of the 14 SARS-CoV-2 proteins by both methods, comprising 279 high-confidence putative interactions involving 225 human proteins. Furthermore, the PIPE-Sites algorithm was used to predict the putative subsequence that might mediate each interaction and thereby inform the design of inhibitory polypeptide intended to disrupt the corresponding host-pathogen interactions, thereby acting as anti-SARS-CoV-2 therapeutics. The interaction landscape and three predicted sites of interaction for each of the 279 interactions are published here along with the predictions and their meta-data. All data and metadata are released under a CC-BY 4.0 license. The information provided is theoretical modeling only and caution should be exercised in its use. It is intended only as a resource for the scientific community at large in furthering our understanding of SARS-CoV-2.