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Fig. 9 | Journal of Cheminformatics

Fig. 9

From: DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach

Fig. 9

In silico generation by DeepGraphMolGen of novel molecules with predicted binding capacity to the dopamine transporter using a generative method in which the number of heavy atoms is constrained to be lower than 25. Molecules were generated as described in the text. a Top 10 molecules as predicted by DeepGraphMolGen versus the closest molecule in the BindingdB dataset and the TS thereto (encoded using the RDKit patterned fingerprint). b Distribution of Tanimoto similarities (RDKit patterned encoding) to the closest molecule in BindingdB dataset of the top 500 molecules. c Plot of those molecules with differential affinities for the dopamine and norepinephrine transporters

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