AIMC Topic: Cryoelectron Microscopy

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Overcoming the preferred-orientation problem in cryo-EM with self-supervised deep learning.

Nature methods Nov 18, 2024
While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the 'preferred' orientation problem) remains a complication for most specimens. Existing ...
Software Algorithms Deep Learning Cryoelectron Microscopy Image Processing, Computer-Assisted Anisotropy Macromolecular Substances Ribosomes Imaging, Three-Dimensional
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Deep Spatio-Temporal Network for Low-SNR Cryo-EM Movie Frame Enhancement.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2024
Cryo-EM in single particle analysis is known to have low SNR and requires to utilize several frames of the same particle sample to restore one high-quality image for visualizing that particle. However, the low SNR of cryo-EM movie and motion caused b...
Signal-To-Noise Ratio Cryoelectron Microscopy Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Algorithms
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Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.

International journal of molecular sciences Sep 8, 2024
Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence...
Humans Machine Learning Cryoelectron Microscopy Protein Conformation Proteins Nuclear Magnetic Resonance, Biomolecular Molecular Dynamics Simulation Magnetic Resonance Spectroscopy
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Smart parallel automated cryo-electron tomography.

Nature methods Aug 8, 2024
In situ cryo-electron tomography enables investigation of macromolecules in their native cellular environment. Samples have become more readily available owing to recent software and hardware advancements. Data collection, however, still requires an ...
Software Image Processing, Computer-Assisted Workflow Humans Machine Learning Electron Microscope Tomography Automation Cryoelectron Microscopy
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Accurate Prediction of Protein Structural Flexibility by Deep Learning Integrating Intricate Atomic Structures and Cryo-EM Density Information.

Nature communications Jul 2, 2024
The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and...
Proteins Databases, Protein Protein Conformation Cryoelectron Microscopy Molecular Dynamics Simulation Neural Networks, Computer Deep Learning Computational Biology
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RAIN: machine learning-based identification for HIV-1 bNAbs.

Nature communications Jun 24, 2024
Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infections. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoires is still lacking. Here, we develop a ...
HIV Antibodies HIV Envelope Protein gp120 CD4 Antigens Amino Acid Sequence Humans HIV-1 Machine Learning Cryoelectron Microscopy HIV Infections Antibodies, Neutralizing
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AlphaFold2 structures guide prospective ligand discovery.

Science (New York, N.Y.) Jun 21, 2024
AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules a...
Serotonin 5-HT2 Receptor Antagonists Receptors, sigma Humans Molecular Docking Simulation Protein Conformation Protein Folding Deep Learning Serotonin 5-HT2 Receptor Agonists Cryoelectron Microscopy Ligands Small Molecule Libraries Receptor, Serotonin, 5-HT2A Drug Design Drug Discovery
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The dynamic duo: cryo-EM teams up with machine learning to visualize biomolecules in motion.

BioTechniques Jun 12, 2024
Cryo-EM has been a key technique in our understanding of biomolecular structures. Now, machine learning techniques are being used to put these structures in motion, revealing dynamic interactions and processes happening on a molecular and cellular le...
Proteins Humans Motion Machine Learning Cryoelectron Microscopy
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Missing Wedge Completion via Unsupervised Learning with Coordinate Networks.

International journal of molecular sciences May 17, 2024
Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, whi...
Electron Microscope Tomography Neural Networks, Computer Unsupervised Machine Learning Algorithms Imaging, Three-Dimensional Cryoelectron Microscopy Deep Learning Image Processing, Computer-Assisted
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Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures.

Scientific data May 6, 2024
The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structu...
Artificial Intelligence Cryoelectron Microscopy Models, Molecular Proteins Protein Conformation
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