Drug repurposing. DeepChem package and Python Jupyter Notebooks were used to predict if drugs (DrugBank compounds) could be active for multiple protein targets (). DrugBank () contains comprehensive information about drugs, their mechanism of action, and their targets . The calculations used the GPU of Google Colab and the correspondent scripts could be found at GitHub repository: . The fully connected deep neuronal networks (FCNNs) have been used to find the best multitask classification model using 1,024 molecular circular fingerprints (CFPs) as input descriptors for 15,377 ChEMBL compounds and activity (1/0) for 25 target proteins as outputs/tasks . ChEMBL () is an open large-scale bioactivity database . The best model resulted from a grid search for the best parameters have been used to predict the activity of 10,672 drugs for 25 protein targets.