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Clustering predicted structures at the scale of the known protein universe

Code, intermediate results and an interactive visualisation on prediction of putative novel enzymes and small molecule binding proteins presented in (Barrio-Hernandez et al. 2023).

Interactive visualisation

A publicly accessible instance is currently accessible at this address on the Streamlit Community Cloud. Alternatively, install the web app locally by cloning the repository and setting up a conda/mamba environment as follows:

$ git clone git@github.com:jurgjn/af-protein-universe.git
$ cd af-protein-universe/
$ conda create -p streamlit-env python numpy matplotlib seaborn 'pandas<2.0.0'
$ conda run -p ./streamlit-env pip install -r requirements.txt

After that, run the web app locally with:

$ conda run -p ./streamlit-env streamlit run app.py

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