Virology has seen significant advancement in virus detection, understanding, and containment due to advancements in traditional and computational methods. The use of deep learning models made significant improvements in prediction of accuracy, data analytics efficiency, and biological system pattern analysis. This chapter discusses the challenges and contributions of deep learning methods in virology, starting with an introduction to the field and discussing applications during the coronavirus pandemic. Key bottlenecks include data availability, interpretability, and ethical considerations. This chapter concludes with recommendations for the effective application of deep learning in virology. It emphasizes the importance of collaboration between virologists and AI experts to harness its potential to protect humanity against viral diseases.