Curiosity · AI Model

Google DeepMind AlphaFold 3

AlphaFold 3 is the third-generation structure-prediction model from Google DeepMind and Isomorphic Labs. Unlike AlphaFold 2, which specialised in single-protein folding, AlphaFold 3 predicts the joint structure of complexes — proteins with DNA, RNA, small molecules (ligands), ions, and antibodies — making it the most capable open scientific model for drug-discovery workflows.

Model specs

Vendor
Google DeepMind
Family
AlphaFold
Released
2024-05
Context window
1 tokens
Modalities
text

Strengths

  • Predicts joint structures of proteins, DNA, RNA, small molecules, and ions
  • Major accuracy lift over AlphaFold 2 on complexes
  • Free research access via AlphaFold Server (daily quota)
  • Open peer-reviewed Nature publication

Limitations

  • Not an LLM — no token context; inputs are biological sequences and ligand SMILES
  • Commercial use is restricted; Isomorphic Labs licenses for pharma
  • Hallucinated structures are possible for under-represented complexes — validate experimentally
  • Server is rate-limited; self-hosted inference is recently available via code release but compute-heavy

Use cases

  • Predicting protein-ligand binding in early drug discovery
  • Modelling nucleic-acid complexes (DNA/RNA)
  • Antibody design and immunology research
  • Academic structural biology studies

Benchmarks

BenchmarkScoreAs of
PoseBusters ligand accuracy+50% vs prior SOTA2024
Protein-protein interface LDDTState-of-the-art2024

Frequently asked questions

What is AlphaFold 3?

AlphaFold 3 is a structure-prediction model from Google DeepMind and Isomorphic Labs. Unlike AlphaFold 2 (protein-only), AlphaFold 3 predicts the joint 3D structure of protein complexes with DNA, RNA, small-molecule ligands, ions, and antibodies.

Is AlphaFold 3 an LLM?

No — AlphaFold 3 is a diffusion-based scientific model, not a language model. Its inputs are biological sequences (FASTA) and ligand descriptions (SMILES), and its outputs are 3D atomic coordinates. We include it here because it is a landmark 'AI for science' model that teams often compare alongside LLMs.

Can I use AlphaFold 3?

Yes — DeepMind hosts a free AlphaFold Server for non-commercial research with a daily job quota. In late 2024 the source code was published for academic use. Commercial drug-discovery use requires a licence via Isomorphic Labs.

How accurate is AlphaFold 3?

On benchmarks like PoseBusters it roughly doubles the ligand-pose accuracy of prior best docking methods, and it matches or beats specialised methods on protein-protein interfaces. For novel chemistry or under-represented systems, experimental validation is still required.

Sources

  1. Google DeepMind — AlphaFold 3 — accessed 2026-04-20
  2. Nature paper — AlphaFold 3 — accessed 2026-04-20