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An optimization framework for iterative protein engineering
$
pip install protuna
01 / Key Features
Guided generation
Steer protein language models towards your design objectives with reward-guided generation.
Generation and selection →Modular campaigns
Combine interchangeable samplers, predictors, constraints, and acquisition strategies.
Model adapters →Scalable screening
Ray-based distributed streaming APIs for large-scale screening on local accelerators or clusters.
Serving patterns →02 / Reference
If you use Protuna in your research, please cite the software:
@software{protuna2026,
title = {{Protuna: An optimization framework for AI-guided protein engineering}},
author = {Shreshtha, Kumar},
year = {2026},
url = {https://github.com/kumarshreshtha/protuna},
version = {0.1.0}
}