ESM-IF1
Predict alternative sequences for an input protein structure with high accuracy.
Overview
The ESM-IF1 inverse folding model predicts protein sequences from their backbone atom coordinates, trained with 12M protein structures predicted by AlphaFold2.
Run ESM-IF1 on Neurosnap
The ESM-IF1 online webserver allows anybody with a Neurosnap account to run and access ESM-IF1, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- Allows you to inverse fold any protein or complex of proteins.
- Includes options to control which chains to design and which to keep fixed.
- Supports different sampling techniques to better explore the protein landscape.
- Includes per sequence metrics such as an overall score and sequence recovery.
- Includes amino acid probabilities by position.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access ESM-IF1 using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using ESM-IF1 in publications or research outputs.
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Hsu, Chloe, et al. “Learning Inverse Folding from Millions of Predicted Structures.” bioRxiv, 1 Jan. 2022, www.biorxiv.org/content/10.1101/2022.04.10.487779v2. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |