We use the pChEMBL value to classify interacting compounds as active (1) or inactive (0) according to established activity thresholds. pChEMBL expresses the potency of molecules determined from one of several semi-comparable values from the ChEMBL database and is defined as the negative log10 (in molar concentration) of the IC50, XC50, EC50, AC50, Ki, Kd or potency . To classify compounds as active or inactive we use the Illuminating the Druggable Genome Knowledge Management Center (IDG-KMC) , where a compound is considered active against an ion channel, G protein-coupled receptor (GPCR), nuclear receptor or kinase, if the pChEMBL is greater than, 5.00, 7.00, 7.00. and 7.52 respectively. If the target of a given compound is not in the above-mentioned target classification, it enters to the Non-IDG Family Targets classification, and to be considered active it must have a pChEMBL greater than 6.0. To classify compounds as inactive, we selected activity thresholds with 1-fold respect to the adobe active classification (Table ). The SMILES of the compounds were filtered to remove salts using the RDKit Salt Stripper () node in KNIME . Table shows initial thresholds selected to build the ML models. We then selected the proteins that had at least 100 compounds reported in each category (active and inactive) with respect to the defined activity thresholds (Table ) and subsequently calculated the active: inactive ratio. Finally, for the final selection of proteins and ML model building, we kept the compounds that maintained a maximum ratio of 3:1 between both labels (active 1 and inactive 0) to avoid imbalance between active and inactive data and to improve the quality of the ML models. For some targets, which initially had unbalanced data between active and inactive, we manually moved the activity thresholds to better balance the data, but always maintaining a 1-fold factor for both active and inactive categories, and a ratio lower than 3:1 between the categories.