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Revealing the structure of complex biological macromolecules, such as proteins, is an essential step for understanding the chemical mechanisms that determine the diversity of their functions. Synchrotron based x-ray crystallography and…

Understanding complex biological macromolecules, especially proteins, is vital for grasping their diverse chemical functions with direct impact in biology and pharmacology. While techniques like X-ray crystallography and cryo-electron…

Biomolecules · Quantitative Biology 2024-04-12 S. H. Mejias , A. L. Cortajarena , R. Mincigrucci , C. Svetina , C. Masciovecchio

Protein structure prediction models are now capable of generating accurate 3D structural hypotheses from sequence alone. However, they routinely fail to capture the conformational diversity of dynamic biomolecular complexes, often requiring…

Machine Learning · Computer Science 2025-12-02 Rishwanth Raghu , Axel Levy , Gordon Wetzstein , Ellen D. Zhong

Proteins are dynamic, adopting ensembles of conformations. The nature of this conformational heterogenity is imprinted in the raw electron density measurements obtained from X-ray crystallography experiments. Fitting an ensemble of protein…

Quantitative Methods · Quantitative Biology 2024-12-19 Sai Advaith Maddipatla , Nadav Bojan Sellam , Sanketh Vedula , Ailie Marx , Alex Bronstein

Atomic structure analysis of crystalline materials is a paramount endeavor in both chemical and material sciences. This sophisticated technique necessitates not only a solid foundation in crystallography but also a profound comprehension of…

Machine Learning · Computer Science 2026-04-27 Kaipeng Zheng , Weiran Huang , Wanli Ouyang , Han-Sen Zhong , Yuqiang Li

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to…

Accurate crystal structure determination is critical across all scientific disciplines involving crystalline materials. However, solving and refining inorganic crystal structures from powder X-ray diffraction (PXRD) data is traditionally a…

Materials Science · Physics 2024-09-10 Qi Li , Rui Jiao , Liming Wu , Tiannian Zhu , Wenbing Huang , Shifeng Jin , Yang Liu , Hongming Weng , Xiaolong Chen

The generation of protein crystals is necessary for the study of protein molecular function and structure. This is done empirically by processing large numbers of crystallization trials and inspecting them regularly in search of those with…

Computer Vision and Pattern Recognition · Computer Science 2018-05-15 Soheil Ghafurian , Peter Orth , Corey Strickland , Hua Su , Sangita Patel , Steven Soisson , Belma Dogdas

Determining crystal structures from powder X-ray diffraction (PXRD) has been a significant challenge in materials science, particularly when experimental data contain noise or the target structure has a high complexity. While recent AI…

Materials Science · Physics 2026-05-26 Kaixiang Su , Osman Goni Ridwan , Hongfei Xue , Qiang Zhu

Single-crystal X-ray diffraction (SC-XRD) is the gold standard technique to characterize crystal structures in solid state. Despite significant advances in automation for structure solution, the refinement stage still depends heavily on…

Materials Science · Physics 2025-12-04 Wen-Lin Luo , Yi Yuan , Cheng-Hui Li , Yue Zhao , Jing-Lin Zuo

Determining whether a candidate crystalline material is thermodynamically stable depends on identifying its true ground-state structure, a central challenge in computational materials science. We introduce CrystalGRW, a diffusion-based…

The design of crystal materials plays a critical role in areas such as new energy development, biomedical engineering, and semiconductors. Recent advances in data-driven methods have enabled the generation of diverse crystal structures.…

Artificial Intelligence · Computer Science 2025-12-12 Chao Huang , Jiahui Chen , Chen Chen , Chen Chen , Chunyan Chen , Renjie Su , Shiyu Du

The discovery of inorganic crystal structures with targeted properties is a significant challenge in materials science. Generative models, especially state-of-the-art diffusion models, offer the promise of modeling complex data…

Accurately determining the crystallographic structure of a material, organic or inorganic, is a critical primary step in material development and analysis. The most common practices involve analysis of diffraction patterns produced in…

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…

Materials Science · Physics 2025-10-22 Jiale Zhao , Cong Liu , Yuxuan Zhang , Chengyue Gong , Zhenyi Zhang , Shifeng Jin , Zhenyu Liu

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the three-dimensional (3D) conformation of a protein, yet it remains…

Artificial Intelligence · Computer Science 2014-11-17 L. Leherte , J. Glasgow , K. Baxter , E. Steeg , S. Fortier

Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse-grained level. The more…

Chemical Physics · Physics 2025-02-11 Qingsi Lai , Fanjie Xu , Lin Yao , Zhifeng Gao , Siyuan Liu , Hongshuai Wang , Shuqi Lu , Di He , Liwei Wang , Cheng Wang , Guolin Ke

Determining protein structures at an atomic level remains a significant challenge in structural biology. We introduce $\texttt{RecCrysFormer}$, a hybrid model that exploits the strengths of transformers with the aim of integrating…

Quantitative Methods · Quantitative Biology 2026-01-30 Tom Pan , Evan Dramko , Mitchell D. Miller , George N. Phillips , Anastasios Kyrillidis

X-ray diffraction (XRD) is an essential technique to determine a material's crystal structure in high-throughput experimentation, and has recently been incorporated in artificially intelligent agents in autonomous scientific discovery…

Knowledge of a protein's atomic conformational ensemble is critical to determining its function, yet state-of-the-art ensemble prediction models are limited by lack of high-quality conformational data from simulation or experiment. Recent…

Machine Learning · Computer Science 2026-05-12 Jay Shenoy , Miro Astore , Axel Levy , Frédéric Poitevin , Sonya M. Hanson , Gordon Wetzstein
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