TorchDrug

When to Use This Skill

This skill should be used when working with:

Data Types:

• SMILES strings or molecular structures
• Protein sequences or 3D structures (PDB files)
• Chemical reactions and retrosynthesis
• Biomedical knowledge graphs
• Drug discovery datasets

Tasks:

• Predicting molecular properties (solubility, toxicity, activity)
• Protein function or structure prediction
• Drug-target binding prediction
• Generating new molecular structures
• Planning chemical synthesis routes
• Link prediction in biomedical knowledge bases
• Training graph neural networks on scientific data

Libraries and Integration:

• TorchDrug is the primary library
• Often used with RDKit for cheminformatics
• Compatible with PyTorch and PyTorch Lightning
• Integrates with AlphaFold and ESM for proteins

Quick Example

from torchdrug import datasets, models, tasks
from torch.utils.data import DataLoader

## Load molecular dataset

dataset = datasets.BBBP("~/molecule-datasets/")
train_set, valid_set, test_set = dataset.split()