OpenFold
A trainable, memory-efficient PyTorch reproduction of AlphaFold 2 for protein structure prediction.
What is OpenFold?
OpenFold is a PyTorch-based reproduction of DeepMind's AlphaFold 2 system for predicting protein 3D structures from amino acid sequences. It provides a trainable and memory-efficient implementation that allows researchers to retrain and modify the model. The project enables scientific exploration of AlphaFold 2's learning mechanisms and capacity for generalization.
Computational biologists, bioinformatics researchers, and machine learning scientists working on protein structure prediction who need a flexible, trainable implementation of AlphaFold 2.
OpenFold offers the only fully trainable open-source implementation of AlphaFold 2, providing memory optimizations and PyTorch compatibility that enable research modifications and custom training not possible with the original system.
Overview
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
Use Cases
Best For
- Retraining AlphaFold 2 models on custom protein datasets
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