aqlaboratory/openfold

Health v2 · maintenance only

Adoption not part of the score

3420 stars · 689 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

OpenFold is a faithful, trainable PyTorch reproduction of DeepMind's AlphaFold 2 for protein structure prediction. It is memory-efficient and GPU-friendly, supporting both inference and retraining with open training data (OpenProteinSet).

Use cases

• predict 3D protein structures from amino acid sequences
• retrain or fine-tune an AlphaFold2-like model on custom data
• run protein folding inference on GPU with PyTorch
• study AlphaFold2's learning mechanisms and generalization
• predict protein complex structures with multimer modeling

When to choose

• you need a trainable or fine-tunable AlphaFold2 implementation in PyTorch
• you want an open-source, permissively licensed alternative to AlphaFold2
• you need memory-efficient GPU inference or training for protein folding

When to avoid

• you only need quick protein structure predictions without customization (use AlphaFold2 or ColabFold)
• you work outside PyTorch ecosystems (e.g., JAX-based workflows)
• you need pretrained weights under a fully unrestricted license (weights are CC BY 4.0)

Facets

library · maturity active

machine-learning deep-learning llm-training bioinformatics machine-learning deep-learning python protein-structure-prediction alphafold2 pytorch structural-biology computational-biology gpu linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="aqlaboratory/openfold")