95 citations · 108 across the 4 of their papers we have counts for
4 papers
In-Pocket 3D Graphs Enhance Ligand-Target Compatibility in Generative Small-Molecule Creation
Seung-gu Kang, Jeffrey K. Weber, Joseph A. Morrone +3
Proteins in complex with small molecule ligands represent the core of structure-based drug discovery. However, three-dimensional representations are absent from most deep-learning-…
Analysis of training and seed bias in small molecules generated with a conditional graph-based variational autoencoder -- Insights for practical AI-driven molecule generation
Seung-gu Kang, Joseph A. Morrone, Jeffrey K. Weber +1
The application of deep learning to generative molecule design has shown early promise for accelerating lead series development. However, questions remain concerning how factors li…
Combining docking pose rank and structure with deep learning improves protein-ligand binding mode prediction
Joseph A. Morrone, Jeffrey K. Weber, Tien Huynh +2
We present a simple, modular graph-based convolutional neural network that takes structural information from protein-ligand complexes as input to generate models for activity and b…
Folding and Stabilization of Native-Sequence-Reversed Proteins
Yuanzhao Zhang, Jeffrey K Weber, Ruhong Zhou
Though the problem of sequence-reversed protein folding is largely unexplored, one might speculate that reversed native protein sequences should be significantly more foldable than…