DrugEx: Deep Learning Models and Tools for Exploration of Drug-Like Chemical Space
DrugEx: Deep Learning Models and Tools for Exploration of Drug-Like Chemical Space
Martin Šícho,Sohvi Luukkonen,3 Authors,G. V. van Westen
TLDR
The new versatile open-source software package DrugEx for multiobjective reinforcement learning is presented, which contains the consolidated and redesigned scripts from the prior DrugEx papers including multiple generator architectures, a variety of scoring tools, and multi objective optimization methods.
Abstract
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 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 at https://github.com/CDDLeiden/DrugEx.