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Cryoelectron Microscopy

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Concluding remarks: Challenges and future developments in biological electron cryo-microscopy.

Faraday discussions
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...

Isotropic reconstruction for electron tomography with deep learning.

Nature communications
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...

New opportunities in integrative structural modeling.

Current opinion in structural biology
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 ...

Robust deep learning-based protein sequence design using ProteinMPNN.

Science (New York, N.Y.)
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...

Hallucinating symmetric protein assemblies.

Science (New York, N.Y.)
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-...

I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction.

Nature protocols
Most proteins in cells are composed of multiple folding units (or domains) to perform complex functions in a cooperative manner. Relative to the rapid progress in single-domain structure prediction, there are few effective tools available for multi-d...

Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly.

Nature communications
Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-electron microscopy (cryo-EM) maps. However, building accurate models into intermediate-resolution EM maps remains challenging and labor-inten...

MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells....

Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold.

Science (New York, N.Y.)
INTRODUCTION The nuclear pore complex (NPC) is the molecular conduit in the nuclear membrane of eukaryotic cells that regulates import and export of biomolecules between the nucleus and the cytosol, with vertebrate NPCs ~110 to 125 MDa in molecular m...