Drug target discovery is a critical step in drug development. It is the basis of modern drug development
because it determines the target molecules related to specific diseases in advance. Predicting drug targets by computational
methods saves a great deal of financial and material resources compared to in vitro experiments. Therefore,
several computational methods for drug target discovery have been designed. Recently, machine learning (ML)
methods in biomedicine have developed rapidly. In this paper, we present an overview of drug target discovery
methods based on machine learning. Considering that some machine learning methods integrate network analysis to
predict drug targets, network-based methods are also introduced in this article. Finally, the challenges and future
outlook of drug target discovery are discussed.
Keywords: Drug target discovery, drug target interaction, machine learning, network-based methods, drug development, biomedicine.
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