Chemoinformatic methods, including ML/DL approaches, offer significant benefits for the discovery and development of bioactive compounds. However, one of the major drawbacks of ML/DL methods discussed during the Colloquium was the lack of or limited interpretability of their predictions. This is more evident for DL approaches, in which the user has no knowledge about internal features (or priorities) of the model and their assignment.