  Drug development is time-consuming and expensive. Repurposing existing drugs
for new therapies is an attractive solution that accelerates drug development
at reduced experimental costs, specifically for Coronavirus Disease 2019
(COVID-19), an infectious disease caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2). However, comprehensively obtaining and productively
integrating available knowledge and big biomedical data to effectively advance
deep learning models is still challenging for drug repurposing in other complex
diseases. In this review, we introduce guidelines on how to utilize deep
learning methodologies and tools for drug repurposing. We first summarized the
commonly used bioinformatics and pharmacogenomics databases for drug
repurposing. Next, we discuss recently developed sequence-based and graph-based
representation approaches as well as state-of-the-art deep learning-based
methods. Finally, we present applications of drug repurposing to fight the
COVID-19 pandemic, and outline its future challenges.
