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SettingsResearch demo · not for clinical or commercial use
Corollary
  1. Catalog
  2. Protein Structure
  3. Boltz-2

Protein Structure · MIT × Recursion

Boltz-2

Structure and binding affinity in one pass, approaching FEP accuracy 1000× faster.

Commercial use permittedThe MIT licence allows use in commercial research and products.MIT
Availability
Ready
Typical latency
45s
Credits per run
~252
Compute tier
B · Standard

30s–5min

Runs on Managed GPU endpoint

Runs on managed compute. Availability and startup time depend on current capacity.

Run this model

Boltz-2

Single-letter amino acid code. Whitespace and FASTA headers are stripped automatically.

Optional. Omit to fold the protein alone.

Needs target protein sequence

About this model

Boltz-2 co-folds a protein with its ligand and predicts binding affinity in the same forward pass. It approaches free-energy-perturbation accuracy at roughly a thousandth of the cost, which makes it the default engine for hit-to-lead triage inside Corollary. MIT licensed end to end, so there is no commercial-use asterisk.

Reported performance

vs. physics-based FEP
~1000× faster
Affinity correlation
FEP-level

Standardized I/O contract

Every model in the Hub speaks the same contract, which is what lets the Router and the agent call any of them without special-casing.

Inputs

  • sequencesequence · required

    Target protein sequence

  • smilessmiles

    Ligand SMILES

Outputs

  • pdbstructure

    All-atom coordinates in PDB format, viewable and downloadable.

  • affinityscalar

    Binding affinity estimate for the protein–ligand pair.

  • plddtvector

    pLDDT score per residue (0–100). Above 70 is generally reliable.

Specification

Hardware
1× A100 40GB
GPU memory
40 GB
Version
2.1.0
Licence
MIT
Backend
ReadyManaged GPU endpoint
MCP server
mcp-protein-server

Tasks

structure predictionbinding affinity

Chains well with

  • ESM2-3BHigh-quality 1,280-dimensional protein embeddings for everything downstream.
  • DiffDockDiffusion docking: 38% top-1 success versus 23% for classical AutoDock.
  • ADMET-AI52 ADMET endpoints in one call — hERG, BBB, CYP, clearance, solubility, Tox21.

Source

  • Repository
co-foldingaffinitydrug-discoverymit-licenseflagship