The discovery of novel molecules with desirable properties is a classic challenge in medicinal chemistry. With the recent advancements of machine learning, there has been a surge of de novo drug design tools. However, few resources exist that are both user-friendly as well as easily customisable. In this application note, we present the new versatile open-source software package DrugEx for multi-objective reinforcement learning. This package contains the consolidated and redesigned scripts from the prior DrugEx papers including multiple generator architectures and a variety of scoring tools and multi-objective optimisation methods. It has a flexible application programming interface and can readily be used via the command line interface or the graphical user interface GenUI. The DrugEx package is publicly available at https://github.com/CDDLeiden/DrugEx
Further details about the generator architectures (S1), the data pre-processing (S2), the environment (S3) and sampling statistics (S4).