In case you haven't noticed, ChEMBL_18 has arrived. As usual, it brings new additions, improvements and enhancements both on the data/annotation, as well as on the interface. One of the new features is the target predictions for small molecule drugs. If you go to the compound report card for such a drug, say imatinib or cabozantinib , and scroll down towards the bottom of the page, you'll see two tables with predicted single-protein targets, corresponding to the two models that we used for the predictions. - So what are these models and how were they generated? They belong to the family of the so-called ligand-based target prediction methods. That means that the models are trained using ligand information only. Specifically, the model learns what substructural features (encoded as fingerprints) of ligands correlate with activity against a certain target and assign a score to each of these features. Given a new molecule with a new set of feature...