Drug Discovery

REINVENT is a Python molecular-design toolkit that uses generative models, reinforcement learning and transfer learning for configurable small-molecule generation and optimization.

Molecular Generation · Drug Discovery

TANKBind is a research model for predicting protein–ligand binding structures and affinity, with repository notebooks for prediction, dataset preparation, self-docking evaluation and virtual screening.

Drug Discovery

EquiBind is an SE(3)-equivariant model for predicting receptor binding locations and ligand poses directly from protein–ligand structures, with workflows for inference and training.

Drug Discovery

DiffDock predicts protein–small-molecule binding poses using a diffusion-based model, with single-complex and batch inference, sequence-based protein inputs, and pose confidence scores.

Drug Discovery

DeepChem is an open-source Python toolchain for scientific deep learning in drug discovery, materials science, quantum chemistry and biology, with backend-specific dependencies and guided tutorials.

Drug Discovery