AlphaFold 3, developed by Google DeepMind, is an advanced deep learning system for predicting biomolecular structures and interactions with exceptional accuracy. This repository provides the complete inference pipeline for running AlphaFold 3, though access to the model parameters is restricted and must be obtained directly from Google under specific terms of use. The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. The software includes flexible options for running both data preprocessing and GPU-accelerated inference, allowing users to adapt to available computational resources.
Features
- Implements the full inference pipeline of AlphaFold 3 for structure prediction
- Supports CPU-based data preprocessing and GPU-accelerated inference modes
- Docker-based environment for simplified deployment and reproducibility
- JSON-based input configuration for customizable prediction tasks
- Designed for biomolecular structure and interaction modeling
- Extensive documentation for installation, input/output formats, and known issues
Project Samples
