torchdrug
TorchDrug
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction, retrosynthesis. For pre-trained models and diverse featurizers use deepchem; for benchmark datasets use pytdc.
This page mirrors an upstream repository entry. It does not mean the skill is already part of the SCI Skills curated catalog.
- Raw path
- scientific-skills/torchdrug
- Allowed tools
- -
- Repository version
- 2.31.0
- Synced at
- March 27, 2026
About this skill
About this skill
TorchDrug is a comprehensive PyTorch-based machine learning toolbox for drug discovery and molecular science. Apply graph neural networks, pre-trained models, and task definitions to molecules, proteins, and biological knowledge graphs, including molecular property prediction, protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis planning, with 40+ curated datasets and 20+ model architectu
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