Efficient Evolution
A protein language model-based tool for efficient, task-agnostic design of high-functionality protein variants.
Overview
Efficient Evolution leverages general protein language models to guide the efficient evolution of proteins. These models utilize evolutionary-scale data to recommend mutations that are evolutionarily plausible and likely to enhance protein functionality. By operating in sequence space without requiring knowledge of target-specific details, Efficient Evolution streamlines the design process. It generates small, high-confidence variant sets for experimental validation, offering a scalable and task-agnostic solution for protein engineering applications.
Run Efficient Evolution on Neurosnap
The Efficient Evolution online webserver allows anybody with a Neurosnap account to run and access Efficient Evolution, 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
- Offers a general-purpose approach applicable across diverse protein families.
- Utilizes evolutionary-scale data to recommend plausible and functional mutations.
- Facilitates the exploration of sequence space while maintaining evolutionary plausibility.
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 Efficient Evolution 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 Efficient Evolution in publications or research outputs.
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Hie BL, Shanker VR, Xu D, Bruun TU, Weidenbacher PA, Tang S, Wu W, Pak JE, Kim PS. Efficient evolution of human antibodies from general protein language models. Nature Biotechnology. 2024 Feb;42(2):275-83. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |