Torchdrug

This is your go-to for building graph neural networks on molecules and proteins with PyTorch. It comes with 40+ datasets (BBBP, Tox21, QM9 for molecules; EnzymeCommission, PDBBind for proteins), 20+ model architectures (GIN, GAT, SchNet, GearNet), and task wrappers for property prediction, retrosynthesis, and knowledge graph reasoning. The installation is a bit finicky since you need to match PyTorch versions with torch-scatter and torch-cluster wheels, but once that's sorted you get a complete drug discovery stack. It's genuinely comprehensive but last updated July 2023, so you're working with PyTorch 2.0 max and Python 3.10. Best for custom model development where you need full control over the architecture rather than just running inference on pre-trained models.