jwohlwend/boltz

Health v2 · maintenance only

Adoption not part of the score

4177 stars · 884 forks observed · 2026-08-28

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

Boltz is a family of open-source biomolecular interaction models (Boltz-1 and Boltz-2) that predict complex structures and binding affinities of proteins, ligands, nucleic acids, and other molecules. It approaches AlphaFold3 accuracy and enables fast in silico screening for early-stage drug discovery.

Use cases

• predict protein-ligand complex structures
• estimate binding affinity of small molecules to protein targets
• screen compound libraries for binders in early drug discovery
• cofold protein complexes with nucleic acids and ligands
• find an open-source alternative to AlphaFold3
• run batched structure predictions from YAML inputs

When to choose

• you need open-source (MIT) biomolecular structure and affinity prediction for academic or commercial use
• you want near-FEP accuracy binding affinity estimates at much lower compute cost
• you need GPU-accelerated batch inference of biomolecular complexes

When to avoid

• you need physics-based free-energy perturbation precision for lead optimization
• you lack GPU hardware and need fast predictions, since CPU inference is significantly slower
• you need a polished GUI or web service rather than a Python/CLI workflow

Facets

library · maturity active

machine-learning deep-learning llm-inference bioinformatics artificial-intelligence healthcare python cli protein-structure-prediction binding-affinity drug-discovery alphafold molecular-modeling cofolding linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="jwohlwend/boltz")