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SettingsResearch demo · not for clinical or commercial use
Corollary
  1. Catalog
  2. Protein Design
  3. ProteinMPNN

Protein Design · Baker Lab

ProteinMPNN

Inverse folding: given a backbone, design sequences that actually fold onto it.

Commercial use permittedThe MIT licence allows use in commercial research and products.MIT
Availability
Ready
Typical latency
6.0s
Credits per run
~42
Compute tier
A · Fast

1–30s

Runs on Managed GPU endpoint

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

Run this model

ProteinMPNN

Typically the output of RFDiffusion, or an existing structure to redesign.

Needs backbone (pdb)

About this model

ProteinMPNN is the second half of nearly every design pipeline. Give it a backbone and it returns sequences with dramatically higher experimental success rates than Rosetta's physics-based design. Apache-2.0 licensed, fast, and reliable enough to be boring — which is the highest praise a design tool can earn.

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

  • pdbtextarea · required

    Backbone (PDB)

  • num_sequencesnumber

    Sequences

  • sampling_tempnumber

    Sampling temperature

Outputs

  • sequencestable

    Sequences with per-design score and global recovery rate.

Specification

Hardware
1× A100 16GB
GPU memory
8 GB
Version
1.0.1
Licence
MIT
Backend
ReadyManaged GPU endpoint
MCP server
mcp-protein-server

Tasks

inverse foldingsequence design

Chains well with

  • ESMFoldSingle-sequence folding in seconds — no MSA, no waiting.
  • RFDiffusionDe novo backbone generation by denoising diffusion — the binder-design workhorse.

Source

  • Repository
inverse-foldingdesignmit-licenseflagship