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Biohub Platform and ESMFold2

skills/esm/references/biohub-platform.md

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Biohub Platform and ESMFold2

Overview

EvolutionaryScale is migrating hosted inference from Forge to the Biohub platform. The Python SDK still uses esm.sdk.forge client classes and "Forge" naming in many places, but newer structure-prediction APIs (ESMFold2) run on Biohub endpoints.

Use this reference when you need all-atom structure prediction (ESMFold2) or when upstream docs point to biohub.ai instead of forge.evolutionaryscale.ai.

Authentication

Create API keys in the Biohub developer console. Store the key in ESM_API_KEY (same env var used by esm.sdk.client() on Forge).

python
import os

token = os.environ["ESM_API_KEY"]

Never commit API keys or paste them into notebooks checked into git.

Installation

For ESMFold2 and latest Biohub SDK features, upstream may recommend installing from the Biohub GitHub repo (pin a specific commit for reproducibility):

bash
uv pip install "esm@git+https://github.com/Biohub/esm.git@c94ed8d"

For ESM3/ESM C workflows on PyPI, uv pip install "esm==3.2.3" remains the standard path. Confirm which install source your task requires before mixing both in one environment.

ESMFold2 Structure Prediction

ESMFold2 is a structure prediction model built on ESMC 6B, available through SequenceStructureForgeInferenceClient with Biohub as the API host.

python
import os
from esm.sdk.forge import SequenceStructureForgeInferenceClient
from esm.sdk.api import FoldingConfig
from esm.utils.structure.input_builder import ProteinInput, StructurePredictionInput

client = SequenceStructureForgeInferenceClient(
    model="esmfold2-fast-2026-05",
    url="https://biohub.ai",
    token=os.environ["ESM_API_KEY"],
)

sequence = "MSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPTLVTTFSYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTLVNRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLADHYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITLGMDELYK"

fold_input = StructurePredictionInput(
    sequences=[ProteinInput(id="A", sequence=sequence)]
)

config = FoldingConfig(num_loops=3, num_sampling_steps=32)
result = client.fold_all_atom(fold_input, config=config)

with open("result.cif", "w") as f:
    f.write(result.complex.to_mmcif())

Model IDs

Model IDUse case
esmfold2-fast-2026-05Fast single-sequence folding
Check Biohub docs for additional variantsMSA-augmented or higher-accuracy modes

Relationship to Forge (ESM3 / ESM C)

CapabilityTypical endpointClient
ESM3 generationhttps://forge.evolutionaryscale.aiesm.sdk.client() or ESM3ForgeInferenceClient
ESM C 6B embeddings (hosted)ForgeESM3ForgeInferenceClient with esmc-6b-2024-12
ESMFold2 structure predictionhttps://biohub.aiSequenceStructureForgeInferenceClient

For ESM3 and ESM C cloud usage patterns, see forge-api.md. For local open-weight models, see esm3-api.md and esm-c-api.md.

Additional Resources