We used the Random Forest (RF) as implemented in Scikit-Learn version 0.22.0 28 as our learning algorithm, as our previous results demonstrated that it consistently outperformed other tested machine learning methods. We built three models to predict the binding affinity of a protein-ligand complex that differed in the types of input features used: a purely ligand-based (LB) model; a traditional structure-based (SB) model using proteinligand intermolecular features; and a hybrid (HB) model consisting of both ligand-based and structure-based features.