Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets
Taras Voitsitskyi, Volodymyr G. Bdzhola, Roman Stratiichuk, Ihor Koleiev, Zakhar Ostrovsky, Volodymyr Vozniak, Ivan Khropachov, Pavlo Henitsoi, Leonid Popryho, Roman Zhytar, Semen Yesylevskyy, Alan Nafiiev, Sergiy A. Starosyla
Abstract
We introduce introduces the PocketCFDM generative diffusion model, aimed at improving the prediction of small molecule poses in the protein binding pockets.
Topics & Concepts
Generative grammarDocking (animal)Generative modelTraining setComputer scienceDiffusionArtificial intelligencePhysicsThermodynamicsMedicineNursingComputational Drug Discovery MethodsProtein Structure and DynamicsBioinformatics and Genomic Networks