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

Protein Design · Harvard / Broad Institute

EVOLVEpro

Few-shot active learning for directed evolution — 24 mutants per round.

Commercial use permittedThe MIT licence allows use in commercial research and products.MIT
Availability
Not runnable yet

No backend is configured for this model.

Typical latency
30s
Credits per run
~210
Compute tier
B · Standard

30s–5min

Not runnable yet

This model isn't available to run right now.

Run this model

EVOLVEpro

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

Prior rounds of measurements. Leave empty to seed round one.

Needs wild-type sequence

About this model

EVOLVEpro sits on top of ESM2 and learns from your assay data as it arrives, proposing the next round of mutants. Validated across diverse enzymes with as few as 24 measurements per round, which turns directed evolution from a screening problem into a design problem.

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

    Wild-type sequence

  • measurementstextarea

    Assay data (CSV)

  • batch_sizenumber

    Next batch size

Outputs

  • proposalstable

    Ranked next-round candidates with predicted fitness and diversity.

Specification

Hardware
1× A100 40GB
GPU memory
16 GB
Version
1.0
Licence
MIT
Backend
not configured
MCP server
mcp-protein-server

Tasks

directed evolutionactive learning
directed-evolutionactive-learningenzymes