AIMC Topic: Crystallography, X-Ray

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Cyclic peptide structure prediction and design using AlphaFold2.

Nature communications May 21, 2025
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here...
Computational Biology Models, Molecular Amino Acid Sequence Drug Design Deep Learning Protein Conformation Proto-Oncogene Proteins c-mdm2 Kelch-Like ECH-Associated Protein 1 Peptides, Cyclic Crystallography, X-Ray Humans
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Crystal Structure Prediction Using a Self-Attention Neural Network and Semantic Segmentation.

Journal of chemical information and modeling Apr 14, 2025
The development of new materials is a time-consuming and resource-intensive process. Deep learning has emerged as a promising approach to accelerate this process. However, accurately predicting crystal structures using deep learning remains a signifi...
Deep Learning Models, Molecular Crystallography, X-Ray Semantics Neural Networks, Computer
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Atomic context-conditioned protein sequence design using LigandMPNN.

Nature methods Mar 28, 2025
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Protein Binding Proteins Models, Molecular Deep Learning Crystallography, X-Ray Protein Conformation Amino Acid Sequence Ligands
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Deep-Learning-Driven Discovery of SN3-1, a Potent NLRP3 Inhibitor with Therapeutic Potential for Inflammatory Diseases.

Journal of medicinal chemistry Sep 20, 2024
The NLRP3 inflammasome plays a central role in the pathogenesis of various intractable human diseases, making it an urgent target for therapeutic intervention. Here, we report the development of SN3-1, a novel orally potent NLRP3 inhibitor, designed ...
Inflammasomes Crystallography, X-Ray Structure-Activity Relationship NLR Family, Pyrin Domain-Containing 3 Protein Drug Discovery Humans Deep Learning Animals Inflammation Mice Male Mice, Inbred C57BL
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An artificial intelligence accelerated virtual screening platform for drug discovery.

Nature communications Sep 5, 2024
Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding p...
Crystallography, X-Ray Ubiquitin-Protein Ligases Small Molecule Libraries Drug Evaluation, Preclinical Ligands NAV1.7 Voltage-Gated Sodium Channel Humans Artificial Intelligence Drug Discovery Protein Binding Molecular Docking Simulation
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Deep-learning map segmentation for protein X-ray crystallographic structure determination.

Acta crystallographica. Section D, Structural biology Jun 27, 2024
When solving a structure of a protein from single-wavelength anomalous diffraction X-ray data, the initial phases obtained by phasing from an anomalously scattering substructure usually need to be improved by an iterated electron-density modification...
Neural Networks, Computer Databases, Protein Deep Learning Crystallography, X-Ray Proteins Models, Molecular Protein Conformation
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KINNTREX: a neural network to unveil protein mechanisms from time-resolved X-ray crystallography.

IUCrJ May 1, 2024
Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. Th...
Kinetics Neural Networks, Computer Crystallography, X-Ray Photoreceptors, Microbial Machine Learning Bacterial Proteins
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Deep residual networks for crystallography trained on synthetic data.

Acta crystallographica. Section D, Structural biology Jan 1, 2024
The use of artificial intelligence to process diffraction images is challenged by the need to assemble large and precisely designed training data sets. To address this, a codebase called Resonet was developed for synthesizing diffraction data and tra...
Artificial Intelligence Crystallography, X-Ray Synchrotrons Algorithms Computer Simulation
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The bad and the good of trends in model building and refinement for sparse-data regions: pernicious forms of overfitting versus good new tools and predictions.

Acta crystallographica. Section D, Structural biology Nov 3, 2023
Model building and refinement, and the validation of their correctness, are very effective and reliable at local resolutions better than about 2.5 Å for both crystallography and cryo-EM. However, at local resolutions worse than 2.5 Å both the procedu...
Protein Conformation Cryoelectron Microscopy Models, Molecular Peptides Artificial Intelligence Crystallography, X-Ray Proteins
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Exploring the World of Membrane Proteins: Techniques and Methods for Understanding Structure, Function, and Dynamics.

Molecules (Basel, Switzerland) Oct 19, 2023
In eukaryotic cells, membrane proteins play a crucial role. They fall into three categories: intrinsic proteins, extrinsic proteins, and proteins that are essential to the human genome (30% of which is devoted to encoding them). Hydrophobic interacti...
Crystallography, X-Ray Cryoelectron Microscopy Humans Membrane Proteins Artificial Intelligence Microscopy, Electron
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