Description
ESMFold2 is an advanced protein structure prediction model that predicts high-resolution, all-atom 3D structures directly from amino acid sequences. As the successor to ESMFold, it sets a new state of the art for single-sequence structure prediction and enables the generation of new functional proteins through exploring the ESMC model’s latent space.
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The model can utilize optional multiple sequence alignment (MSA) input, which significantly enhances accuracy, especially on challenging targets. ESMFold2 outputs comprehensive structural information, including all-atom coordinates for both backbone and side chains, confidence metrics, and optional distogram predictions for detailed analysis of the predicted structures. This makes it a valuable tool for researchers and professionals in the field of protein science.
To get started with ESMFold2, users can refer to the Quickstart Guide and Tutorials available on the Biohub platform. The installation process involves installing the esm Python package, creating an API key from a Biohub account, and connecting to the Biohub Platform API. Once set up, users can run their inference and explore various use cases, such as folding proteins in combination with DNA, RNA, and small-molecule ligands, or designing antibodies and minibinders with high hit rates.
ESMFold2 was trained on extensive datasets, including sequences from the Protein Data Bank (PDB) and the AlphaFold DB (AFDB). However, it is important to note that the model predicts single static conformations and is not designed for modeling protein dynamics or conformational flexibility. Outputs should be validated experimentally, and it is not intended for clinical or therapeutic applications without further validation. Overall, ESMFold2 represents a significant advancement in the field of protein structure prediction, offering researchers powerful tools to explore protein structures and functions.
- CategoryScientific Discovery & Lab Tools
- Pricing ModelFree
- DeploymentCloud
- PlatformsWeb
ESMFold2 Protein Structure Prediction Highlights
High-resolution 3D structure prediction
Single-sequence and MSA-conditioned models
All-atom coordinate outputs
Confidence metrics included
Distogram predictions available
API access for integration
Open access to model
Trained on PDB and AFDB datasets
Getting Started with ESMFold2 Protein Structure Prediction
Install the esm Python package: Follow the installation instructions provided in the Quickstart Guide.
Create an API key: Generate an API key from your Biohub account to manage access.
Connect to the Biohub Platform API: Use the API key to authenticate your requests.
Run your inference: Call the inference client with the selected model and your API token.
ESMFold2 Protein Structure Prediction's Use Cases
- Protein Folding
- Antibody Design
- Structural Analysis
- Functional Protein Generation
- Research Applications
