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DrugEx: Deep Learning Models and Tools for Exploration of Drug-Like Chemical Space

Martin Šícho, Sohvi Luukkonen, Helle W. van den Maagdenberg, Linde Schoenmaker, Olivier J. M. Béquignon, Gerard J. P. van Westen

2023Journal of Chemical Information and Modeling35 citationsDOIOpen Access PDF

Abstract

High Resolution Image Download MS PowerPoint Slide 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 .

Topics & Concepts

Computer scienceScripting languageChemical spaceGraphical user interfaceInterface (matter)Variety (cybernetics)Reinforcement learningSoftwareGenerator (circuit theory)Software engineeringUser interfaceHuman–computer interactionDrug discoveryProgramming languageArtificial intelligenceOperating systemBioinformaticsBubblePower (physics)Maximum bubble pressure methodQuantum mechanicsPhysicsBiologyComputational Drug Discovery MethodsInnovative Microfluidic and Catalytic Techniques InnovationMachine Learning in Materials Science
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