In the current work, we apply AL approaches to the lead optimization step of drug discovery. In the first part of the study we retrospectively analyzed a large set of phosphodiesterase 2 (PDE2) inhibitors for which experi-mentally measured binding affinities were readily available. We explored the optimization of the learning process with respect to the ligand selection procedure for the free energy calculations, the molecule encoding for ML, and the hyper-parameter tuning of the ML models.