Features that are used to train the models are listed in Table . This is a list of features that are used to build the ML models, and some of them are taken directly from the respective databases, while some are derived. An example of a derived feature is fingerprints. SMILES ) is a chemical notation to describe the structure of a compound. We extract SMILES from DrugBank and use this to get molecular fingerprints. For the fields used from each data source, we refer the reader to Section S1.2 of Supporting Information. The final feature set can be categorized as molecular fingerprint-based, drug properties, compound-target association indices.