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This chapter explores drug-target interactions in modern drug discovery, highlighting a shift from one-bullet-one-target to a holistic network approach. It reviews data sources, similarity-based and machine learning algorithms, and computational tools for interaction prediction and network analysis. Emphasizing the integration of big data and complex networks, the chapter underscores the potential to enhance our understanding of drug molecules, targets, and interactions.