kexinhuang12345/DeepPurpose

Health v2 · maintenance only

Adoption not part of the score

1184 stars · 305 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DeepPurpose is a PyTorch-based deep learning library for molecular modeling, supporting drug-target interaction (DTI), drug property, drug-drug interaction, protein-protein interaction, and protein function prediction. It enables drug repurposing, virtual screening, and QSAR workflows with just a few lines of code.

Use cases

• predict drug-target interactions with deep learning
• run virtual screening for drug repurposing
• predict drug-drug interactions and side effects
• build QSAR models for compound property prediction
• predict protein-protein interactions
• screen compounds against SARS-CoV-2 targets

When to choose

• you need pretrained models for DTI or drug property prediction
• you want a simple, few-lines-of-code API for molecular ML tasks
• you are doing drug repurposing or virtual screening research
• you want graph neural network encodings for compounds

When to avoid

• you need a production clinical decision system rather than research tooling
• you need non-PyTorch frameworks or custom training loops beyond its abstractions
• you need actively developed features - development has slowed

Facets

library · maturity maintenance

deep-learning machine-learning nlp data-science bioinformatics healthcare machine-learning artificial-intelligence python cross-platform drug-discovery drug-target-interaction virtual-screening drug-repurposing qsar ddi ppi pytorch molecular-modeling

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