The obtained VEGFR-2 dataset (Section 2.1.2) was utilized to train the QSAR model that predicts molecular pIC 50 values (Fig. ). The substances in the dataset were conducted fingerprints and descriptors calculations from SMILES strings using the RDKit 17 library as the input of the QSAR model. Here, we exam- ined 16 types of molecular features including molecular descriptors and fingerprints. Each dataset was built and cross-evaluated using 15 different machine learning regression algorithms. † 1.1 The random_state or seed variable was set to 42 to ensure reproducibility.