DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design
Miguel García-Ortegón, Gregor N. C. Simm, Austin Tripp, José Miguel Hernández-Lobato, Andreas Bender, Sergio Bacallado
Abstract
design of selective kinase inhibitors. The Python package implements a robust ligand and target preparation protocol that allows nonexperts to obtain meaningful docking scores. Our dataset is the first to include docking poses, as well as the first of its size that is a full matrix, thus facilitating experiments in multiobjective optimization and transfer learning. Overall, our results indicate that docking scores are a more realistic evaluation objective than simple physicochemical properties, yielding benchmark tasks that are more challenging and more closely related to real problems in drug discovery.
Topics & Concepts
Docking (animal)Virtual screeningComputer sciencePython (programming language)Protein–ligand dockingDrug discoveryMachine learningComputational biologyArtificial intelligenceData miningBioinformaticsProgramming languageBiologyMedicineNursingComputational Drug Discovery MethodsMachine Learning in Materials ScienceProtein Structure and Dynamics