MACCS (Molecular ACCess System) Keys are structural keys and fall under a class of ambiguous molecular notations seeking to fingerprint compounds based on the presence or absence of a specific preset functional group or structural component. The RDKit (Landrum, 2016) implementation of this is used in this study. The other type of molecular descriptor notation is the hashed fingerprint, where each compound is represented by features generated by the specific molecule and depends on its physicochemical and structural characteristics. Unlike structural keys, the features and the positions are not preset. Morgan fingerprints are an implementation of this class of fingerprints, also called circular fingerprints , built using the Morgan algorithm. This set of molecular features is also generated using RDKit in this study. , which uses the Morgan algorithm derived chemical substructures as words and the compounds as sentences. A pre-trained skip-gram model built with the corpus from 19.9 million compounds of ZINC original and ChEMBL is used. A radius 1, a window size of 10, and embedding vectors of length 300 are used in our study, and this reflects the optimizations adopted in the original study . The SMILES2Vec approach obtains the embeddings for the compounds based on SMILES representation. We conformed to the best fitting hyperparameters of skip-gram wherein the size of the embedding vectors is fixed at 100, while the size of the context window and the number of negative samples are fixed at 12 and 15 respectively. In the current work, we adopted the publicly available implementations, Mol2vec .