google-deepmind/alphafold3

Health v2 · maintenance only

Adoption not part of the score

8643 stars · 1378 forks observed · 2026-10-15

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

Google DeepMind's official implementation of the AlphaFold 3 inference pipeline for predicting biomolecular structures and interactions. It runs protein, nucleic acid, and ligand complex structure predictions using model parameters obtained directly from Google.

Use cases

• predict 3D structure of a protein complex from amino acid sequence
• model protein-ligand interactions computationally
• run alphafold 3 inference on my own gpu
• predict dna rna protein complex structures
• fold a protein sequence into a pdb structure
• model biomolecular interactions with deep learning

When to choose

• you need local, reproducible AlphaFold 3 predictions with full control over inputs and outputs
• you want to run the complete data pipeline (MSA and template search) plus inference on your own hardware
• you need to predict complexes involving proteins, nucleic acids, and ligands beyond alphafoldserver.com limits

When to avoid

• you only need occasional non-commercial predictions without GPU infrastructure - use alphafoldserver.com instead
• you cannot obtain model parameters directly from Google under the terms of use
• you lack GPUs or cannot run the CPU-heavy genetic search pipeline

Facets

library · maturity active

machine-learning deep-learning llm-inference bioinformatics deep-learning machine-learning python protein-structure-prediction alphafold structural-biology molecular-modeling inference-pipeline docker gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google-deepmind/alphafold3")