Code and data used for the AF2χ project (Cagiada M., Thomasen F.E., et al., bioRxiv 2025). AF2χ is a software for predicting side-chain heterogeneity using AlphaFold2 and its internal side-chain representations. AF2χ outputs side-chain χ-angle distributions and a structural ensemble around the predicted AF2 structure.
AF2χ is currently available for the Linux distribution of localColabFold, you can find the implementaiton and all the information on how to use it here.
The contents of this repository allow you to reproduce the results and figures that appear in the AF2χ manuscript.
notebooks: Folder containing all the Jupyter notebooks used to generate the analysis and figures in the manuscript.data: Folder containing all the data necessary to run the analysis notebook and reproduce the manuscript results.figures: collection of the output figures from the analysis notebooks.
N.B.: Due to their large size, the ATLAS MD predictions are not included in the current repository. The ATLAS MD data can be found here.
If you use our model please cite:
Cagiada, M., Thomasen, F.E., Ovchinnikov S., Deane C.M & Lindorff-Larsen, K. (2025). AF2χ: Predicting protein side-chain rotamer distributions with AlphaFold2. In bioRxiv (p. 2024.05.21.595203). https://doi.org/10.1101/2024.05.21.595203
@ARTICLE{Cagiada2025-ax,
title = "AF2χ: Predicting protein side-chain rotamer distributions with AlphaFold2",
author = "Cagiada, Matteo and Thomasen, F. Emil and Ovchinnikov, Sergey and Deane, Charlotte M. and Lindorff-Larsen, Kresten",
journal = "bioRxiv",
pages = "",
month = ,
year = ,
language = "en"
Also if you use this localColab implementation remember to cite:
- Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S and Steinegger M. ColabFold - Making protein folding accessible to all. Nature Methods (2022) doi: 10.1038/s41592-022-01488-1
- If you’re using AlphaFold, please also cite: Jumper et al. "Highly accurate protein structure prediction with AlphaFold." Nature (2021) doi: 10.1038/s41586-021-03819-2
- If you’re using AlphaFold-multimer, please also cite: Evans et al. "Protein complex prediction with AlphaFold-Multimer." BioRxiv (2022) doi: 10.1101/2021.10.04.463034v2
The research was supported by the PRISM (Protein Interactions and Stability in Medicine and Genomics) centre funded by the Novo Nordisk Foundation (NNF18OC0033950, to K.L.-L.), a Novo Nordisk Foundation Postdoctoral Fellowship (NNF23OC0082912; to MC). We acknowledge access to computational resources via a grant from the Carlsberg Foundation (CF21-0392; to K.L.-L.).
This project is licensed under the MIT License. See LICENSE for details.
For questions or support with this repository, please use the GitHub issue tab or reach out to us via email:
📧 Matteo Cagiada: [email protected]
📧 Emil Thomasen: [email protected]
📧 Kresten Lindorff-Larsen: [email protected]