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Generating 3D Molecular Structures Conditional on a Receptor Binding Site with Deep Generative Models
Tomohide Masuda, Matthew Ragoza, David Ryan Koes
Deep generative models have been applied with increasing success to the generation of two dimensional molecules as SMILES strings and molecular graphs. In this work we describe for…
Learning a Continuous Representation of 3D Molecular Structures with Deep Generative Models
Matthew Ragoza, Tomohide Masuda, David Ryan Koes
Machine learning in drug discovery has been focused on virtual screening of molecular libraries using discriminative models. Generative models are an entirely different approach th…
SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning
Jonathan E. King, David Ryan Koes
Despite recent advancements in deep learning methods for protein structure prediction and representation, little focus has been directed at the simultaneous inclusion and predictio…