NeuroFold
Optimize enzyme thermostability, pH stability, solubility, and reaction rate with high accuracy.
Overview
The most accurate approach for in silico enzyme optimization. NeuroFold makes it trivial to optimize multiple enzyme properties, simultaneously.
Run NeuroFold on Neurosnap
The NeuroFold online webserver allows anybody with a Neurosnap account to run and access NeuroFold, 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
- Utilizes our proprietary NeuroFold model to optimize enzymes.
- 40-fold increase in Spearman rank correlation when compared to Meta's ESM-1v model.
- Can optimize the thermostability, pH stability, and reaction rate of a target enzyme.
- Output sequences tend to be evolutionarily distinct and diverse.
- Typical sequence identity to wild type is around 49-56%.
- When tested on β-lactamase, NeuroFold was found to have a 100% experimental success rate.
- Currently only supports monomeric enzymes that do not form complex interactions with nucleotides.
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 NeuroFold 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 NeuroFold in publications or research outputs.
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Keaun Amani, Michael Fish, Matthew D. Smith, Christian Danve M. Castroverde bioRxiv 2024.03.12.584504; doi: https://doi.org/10.1101/2024.03.12.584504 |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |