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This Nature journal study used a deep learning approach to explore chemical sub-structures that helped discover structural classes of antibiotics. The study applied graph neural network models trained with large datasets linked to antibiotic activity measurements and human cell cytotoxicity. The results of the study indicated that model predictions could be explained by chemical sub-structures determined using graph search algorithms.
