Abstract: A global effort is underway to identify compounds to treat emerging virus infections, such as COVID-19. Since de novo compound design is an extremely long, time-consuming, and expensive process, efforts are underway to discover existing compounds that can be repurposed for COVID-19 and new viral diseases. The present invention discloses a machine learning representation framework that uses deep learning-induced vector embeddings of compounds and viral proteins as features to predict compound-viral protein activity. The prediction model uses a consensus framework to rank approved compounds against viral proteins of interest.