For machine learning, the molecular structures can be represented as numerical feature vectors, or molecular descriptors . We employed several features and their concatenations to benchmark different machine learning methods. Each combination had two compounds and therefore two feature vectors were averaged to yield a single feature vector per combination. Avalon1024, Avalon2048, Morgan1024, and Morgan2048 fingerprints and RDKit descriptors () were generated using python RDKit package. Additionally, an in-house Python 3.7.7 was used to generate biological descriptors from NCATS predictor () .