Any publication that discloses findings arising from using AlphaFold 3 source code, model parameters, or outputs must cite the AlphaFold 3 paper.
Citation Requirement
If you use AlphaFold 3 in your research, you must cite the following paper: Accurate structure prediction of biomolecular interactions with AlphaFold 3 Published in Nature, Volume 630, Issue 8016, Pages 493-500 (2024) DOI: 10.1038/s41586-024-07487-wBibTeX Format
For LaTeX and BibTeX users, use the following citation:Text Citation Formats
APA Style
MLA Style
Chicago Style
Nature Style
Authors
Lead Authors
Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, Alexander Pritzel, Olaf Ronneberger, Lindsay WillmoreContributing Authors
Andrew J. Ballard, Joshua Bambrick, Sebastian W. Bodenstein, David A. Evans, Chia-Chun Hung, Michael O’Neill, David Reiman, Kathryn Tunyasuvunakool, Zachary Wu, Akvilė Žemgulytė, Eirini Arvaniti, Charles Beattie, Ottavia Bertolli, Alex Bridgland, Alexey Cherepanov, Miles Congreve, Alexander I. Cowen-Rivers, Andrew Cowie, Michael Figurnov, Fabian B. Fuchs, Hannah Gladman, Rishub Jain, Yousuf A. Khan, Caroline M. R. Low, Kuba Perlin, Anna Potapenko, Pascal Savy, Sukhdeep Singh, Adrian Stecula, Ashok Thillaisundaram, Catherine Tong, Sergei Yakneen, Ellen D. Zhong, Michal Zielinski, Augustin ŽídekSenior Authors
Victor Bapst, Pushmeet Kohli, Max Jaderberg, Demis Hassabis, John M. JumperWhat to Cite
You must cite AlphaFold 3 if you use any of the following:Source Code
- The AlphaFold 3 GitHub repository
- Any code derived from AlphaFold 3
- Modified versions of AlphaFold 3
Model Parameters
- Pre-trained model weights
- Fine-tuned models based on AlphaFold 3
Outputs
- Predicted structures (CIF files)
- Confidence scores
- Any analysis or findings derived from AlphaFold 3 predictions
Methods
- If AlphaFold 3 was used in your methodology
- Even if results are not shown but informed the research
Additional References
Supplementary Information
For detailed method descriptions, please also refer to the Supplementary Information of the AlphaFold 3 paper:- Detailed architecture descriptions
- Training procedures
- Validation benchmarks
- Limitations and caveats
Related Work
If you also use AlphaFold 2, cite:License Information
Source Code License
The AlphaFold 3 source code is licensed under: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC-BY-NC-SA 4.0)- Attribution: Must cite the paper
- NonCommercial: No commercial use
- ShareAlike: Derivative works must use the same license
Model Parameters License
The AlphaFold 3 model parameters are subject to separate terms: AlphaFold 3 Model Parameters Terms of Use- You may only use parameters received directly from Google
- Non-commercial use only
- Additional restrictions apply
Acknowledgments in Publications
Suggested Acknowledgment Text
Consider including an acknowledgment like:“Structure predictions were performed using AlphaFold 3 (Abramson et al., Nature 2024). We thank Google DeepMind for making the AlphaFold 3 code and model parameters available for non-commercial use.”
Funding and Support
If appropriate, acknowledge:- Google DeepMind and Isomorphic Labs for developing AlphaFold 3
- Computational resources used for running predictions
- Any grants or funding that supported the research
Questions About Citation
If you have questions about how to cite AlphaFold 3 or licensing: Email: [email protected]Disclaimer
AlphaFold 3 outputs are predictions with varying confidence levels and should be interpreted carefully. Always:- Validate predictions experimentally when possible
- Check confidence scores (pLDDT, ranking scores)
- Use discretion before relying on predictions
- Do not use for clinical or medical decisions
- Clearly communicate prediction uncertainty in publications