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 ofde novodrug design tools. However, few resources exist that are user-friendly
as well as easily customizable. In this application note, we present
the new versatile open-source software package DrugEx for multiobjective
reinforcement learning. This package contains the consolidated and
redesigned scripts from the prior DrugEx papers including multiple
generator architectures, a variety of scoring tools, and multiobjective
optimization 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 athttps://github.com/CDDLeiden/DrugEx.