XDXD: End-to-end crystal structure determination with low resolution X-ray diffraction

• URL: http://arxiv.org/abs/2510.17936v1
• Date: Mon, 20 Oct 2025 15:50:21 GMT
• Title: XDXD: End-to-end crystal structure determination with low resolution X-ray diffraction
• Authors: Jiale Zhao, Cong Liu, Yuxuan Zhang, Chengyue Gong, Zhenyi Zhang, Shifeng Jin, Zhenyu Liu,
• Abstract summary: We introduce XDXD, the first end-to-end deep learning framework to determine a complete atomic model directly from low-resolution single-crystal X-ray diffraction data.<n>Our model achieves a 70.4% match rate for structures with data limited to 2.0AA resolution, with a root-mean-square error (RMSE) below 0.05.
• Score: 22.50406008374185
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Determining crystal structures from X-ray diffraction data is fundamental across diverse scientific fields, yet remains a significant challenge when data is limited to low resolution. While recent deep learning models have made breakthroughs in solving the crystallographic phase problem, the resulting low-resolution electron density maps are often ambiguous and difficult to interpret. To overcome this critical bottleneck, we introduce XDXD, to our knowledge, the first end-to-end deep learning framework to determine a complete atomic model directly from low-resolution single-crystal X-ray diffraction data. Our diffusion-based generative model bypasses the need for manual map interpretation, producing chemically plausible crystal structures conditioned on the diffraction pattern. We demonstrate that XDXD achieves a 70.4\% match rate for structures with data limited to 2.0~\AA{} resolution, with a root-mean-square error (RMSE) below 0.05. Evaluated on a benchmark of 24,000 experimental structures, our model proves to be robust and accurate. Furthermore, a case study on small peptides highlights the model's potential for extension to more complex systems, paving the way for automated structure solution in previously intractable cases.

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