AIMC Topic: Cryoelectron Microscopy

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Improving Protein-Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge.

Biomolecules Jan 9, 2023
Elucidating protein-ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein-ligand interaction is traditionally tackled by molecular docking a...
Molecular Docking Simulation Deep Learning Protein Conformation Proteins Cryoelectron Microscopy Ligands
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Mass-Spec, Cryo-EM and AI join forces for a close look at the transporter complex in cilia.

The EMBO journal Dec 15, 2022
The intraflagellar transport (IFT) complex transports components between the cytoplasm and the ciliary tip. Two studies now report on the atomic structure of IFT-B, the core of IFT, using cutting-edge technology, such as cross-linking mass spectromet...
Flagella Artificial Intelligence Cilia Mass Spectrometry Biological Transport Cryoelectron Microscopy
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Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Methods in enzymology Dec 8, 2022
Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray...
Deep Learning Proteins Humans X-Ray Diffraction Protein Conformation Models, Molecular Epitopes Antigen-Antibody Complex Cryoelectron Microscopy Scattering, Small Angle Proprotein Convertase 9
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Deep Learning-Based Segmentation of Cryo-Electron Tomograms.

Journal of visualized experiments : JoVE Nov 11, 2022
Cryo-electron tomography (cryo-ET) allows researchers to image cells in their native, hydrated state at the highest resolution currently possible. The technique has several limitations, however, that make analyzing the data it generates time-intensiv...
Electrons Cryoelectron Microscopy Deep Learning Image Processing, Computer-Assisted Software
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Concluding remarks: Challenges and future developments in biological electron cryo-microscopy.

Faraday discussions Nov 8, 2022
During the past 10 years, biological electron cryo-microscopy (cryoEM) has undergone a process of rapid transformation. Many things we could only dream about a decade ago have now become almost routine. Nevertheless, a number of challenges remain, to...
Cryoelectron Microscopy Artificial Intelligence Electrons
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Isotropic reconstruction for electron tomography with deep learning.

Nature communications Oct 29, 2022
Cryogenic electron tomography (cryoET) allows visualization of cellular structures in situ. However, anisotropic resolution arising from the intrinsic "missing-wedge" problem has presented major challenges in visualization and interpretation of tomog...
Software Deep Learning Electron Microscope Tomography Image Processing, Computer-Assisted Cryoelectron Microscopy
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New opportunities in integrative structural modeling.

Current opinion in structural biology Oct 21, 2022
Integrative structural modeling enables structure determination of macromolecules and their complexes by integrating data from multiple sources. It has been successfully used to characterize macromolecular structures when a single structural biology ...
Molecular Structure Cryoelectron Microscopy Artificial Intelligence Electron Microscope Tomography Macromolecular Substances
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Robust deep learning-based protein sequence design using ProteinMPNN.

Science (New York, N.Y.) Sep 15, 2022
Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning-based pro...
Amino Acid Sequence Crystallography, X-Ray Deep Learning Proteins Cryoelectron Microscopy Protein Conformation Protein Engineering
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Hallucinating symmetric protein assemblies.

Science (New York, N.Y.) Sep 15, 2022
Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-...
Deep Learning Cryoelectron Microscopy Protein Conformation Protein Subunits Models, Molecular Protein Engineering Biocompatible Materials
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A Transfer Learning-Based Classification Model for Particle Pruning in Cryo-Electron Microscopy.

Journal of computational biology : a journal of computational molecular cell biology Aug 18, 2022
Image Processing, Computer-Assisted Signal-To-Noise Ratio Machine Learning Cryoelectron Microscopy Macromolecular Substances Humans Algorithms
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