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Introduction Deep discriminative and generative neural-network models are becoming an integral part of the modern approach to ligand-based novel drug discovery. The variety of different architectures of neural networks, the methods of their training, and the procedures of generating new molecules require expert knowledge to choose the most suitable approach.Areas covered Three different approaches to deep learning use in ligand-based drug discovery are considered virtual screening, neural generative models, an