ESMFold2

ESMFold2 is the successor to ESMFold that sets a new state of the art for single-sequence structure prediction and enables the generation of new functional proteins through searching the ESMC model’s latent space. The model predicts high-resolution, all-atom 3D structures of biomolecular complexes directly from sequence, with optional multiple sequence alignment (MSA) input for enhanced accuracy on challenging targets.

Structure Prediction•Version 2026-04
Fold ProteinsAPI Reference
PaperGitHubHugging Face

Get Started

Quickstart Guide

API Reference
1

Install the esm Python package

Python
pip install esm@git+https://github.com/Biohub/esm.git@main
2

Create an API key

3

Connect to the Biohub Platform API

Python
from esm.sdk.forge import SequenceStructureForgeInferenceClient

client = SequenceStructureForgeInferenceClient(model="esmfold2-fast-2026-05", url="https://biohub.ai", token="<your API token>")
4

Run your inference

Model Tutorials

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Folding with ESMFold2

Fold proteins in combination with DNA, RNA, and small-molecule ligands.

Open Notebook

Binder design

Design antibodies and minibinders with high hit rates. Implements the protocol featured in our paper, which produced binders exhibiting nanomolar affinity, target, specificity, and functional activity in laboratory assays.

Coming soon

Model Details

Model Card

Open in Hugging Face

Version

2026-05

Architecture

ESM representations that power a series of looped folding layers. A diffusion model projects pairwise representations to atomic resolution predictions.

Supported Modalities

Sequence and structure

Training Data

ESMFold2 was trained on sequences from the Protein Data Bank (PDB) and the AlphaFold DB (AFDB).

Intended Use

ESMFold2 predicts high-resolution, all-atom 3D protein structures directly from amino acid sequences, with optional multiple sequence alignment (MSA) input. The outputs include comprehensive structural information including all-atom coordinates (backbone and side chains), confidence metrics, and optional distogram predictions for detailed analysis of predicted structures.

Limitations & Risks

The model predicts single static conformations and is not designed for modeling protein dynamics, conformational flexibility, or multiple conformations of the same protein. Outputs should be validated experimentally. Not intended for clinical or therapeutic applications without further validation.

This model is released under the MIT License.

Explore the Model

ESM Atlas Data

ESMFold2 Protein Structure Prediction | Biohub Platform