The predictive models generated for each target were evaluated by internal and external validations. Data sets were divided into training (80%) and test (20%) sets, using DeepChem library for Python, selecting Morgan Chiral of radius 2 (1024-bits) fingerprint. The internal validation of all the models was conducted by cross-validation, in which a new training/testing split multiple times from the available data is chosen.