AlphaSAXS: Reconstructing Protein Structure with Physiologically Relevant Conformations from Small Angle X-Ray Scattering Data
Abstract
AlphaFold has revolutionized structural biology with accurate protein predictions, yet challenges remain due to the dynamic nature of proteins. Over 40% of human proteins have flexible regions crucial in diseases like Alzheimer's and COVID-19. To overcome AlphaFold's limitations, we integrated small-angle X-ray scattering (SAXS) data, leveraging its ability to provide structural insights on flexible macromolecules. Using computationally generated SAXS data to inform network inputs during fine-tuning and inference, we enhanced AlphaFold to improve conformation predictions for flexible protein regions. This approach can advance our understanding of experimentally guided structural prediction and provides a potential solution for improving computational prediction of physiologically relevant conformations.
Cite
Text
Yu et al. "AlphaSAXS: Reconstructing Protein Structure with Physiologically Relevant Conformations from Small Angle X-Ray Scattering Data." ICLR 2025 Workshops: GEM, 2025.Markdown
[Yu et al. "AlphaSAXS: Reconstructing Protein Structure with Physiologically Relevant Conformations from Small Angle X-Ray Scattering Data." ICLR 2025 Workshops: GEM, 2025.](https://mlanthology.org/iclrw/2025/yu2025iclrw-alphasaxs/)BibTeX
@inproceedings{yu2025iclrw-alphasaxs,
title = {{AlphaSAXS: Reconstructing Protein Structure with Physiologically Relevant Conformations from Small Angle X-Ray Scattering Data}},
author = {Yu, Feng and Prince, Stephanie and Tritt, Andrew and Pande, Kanupriya and Hura, Greg L. and Ruebel, Oliver and Tsutakawa, Susan E.},
booktitle = {ICLR 2025 Workshops: GEM},
year = {2025},
url = {https://mlanthology.org/iclrw/2025/yu2025iclrw-alphasaxs/}
}