AIMC Topic: Protein Conformation

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

Nature communications Jul 13, 2022
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...
Models, Molecular Protein Conformation Cryoelectron Microscopy Reproducibility of Results Deep Learning
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Automated Protein Secondary Structure Assignment from C Positions Using Neural Networks.

Biomolecules Jun 17, 2022
The assignment of secondary structure elements in protein conformations is necessary to interpret a protein model that has been established by computational methods. The process essentially involves labeling the amino acid residues with H (Helix), E ...
Neural Networks, Computer Machine Learning Proteins Protein Conformation Protein Structure, Secondary
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Simultaneous prediction of antibody backbone and side-chain conformations with deep learning.

PloS one Jun 15, 2022
Antibody engineering is becoming increasingly popular in medicine for the development of diagnostics and immunotherapies. Antibody function relies largely on the recognition and binding of antigenic epitopes via the loops in the complementarity deter...
Antigen-Antibody Complex Deep Learning Structural Homology, Protein Protein Conformation
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Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold.

Science (New York, N.Y.) Jun 10, 2022
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...
Protein Subunits Artificial Intelligence Animals Xenopus Proteins Software Oocytes Nuclear Pore Cryoelectron Microscopy Cytosol Nuclear Pore Complex Proteins Protein Conformation Xenopus laevis
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Using Big Data Analytics to "Back Engineer" Protein Conformational Selection Mechanisms.

Molecules (Basel, Switzerland) Apr 13, 2022
In the living cells, proteins bind small molecules (or "ligands") through a "conformational selection" mechanism, where a subset of protein structures are capable of binding the small molecules well while most other protein structures are not capable...
Data Science Protein Binding Proteins Machine Learning Ligands Protein Conformation
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Affinity prediction using deep learning based on SMILES input for D3R grand challenge 4.

Journal of computer-aided molecular design Mar 22, 2022
Modern molecular docking comprises the prediction of pose and affinity. Prediction of docking poses is required for affinity prediction when three-dimensional coordinates of the ligand have not been provided. However, a large number of feature engine...
Proteins Databases, Protein Protein Conformation Binding Sites Ligands Deep Learning Humans Thermodynamics Protein Binding Molecular Docking Simulation Drug Design
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EvoRator: Prediction of Residue-level Evolutionary Rates from Protein Structures Using Machine Learning.

Journal of molecular biology Mar 11, 2022
Measuring evolutionary rates at the residue level is indispensable for gaining structural and functional insights into proteins. State-of-the-art tools for estimating rates take as input a large set of homologous proteins, a probabilistic model of ev...
Software Algorithms Phylogeny Humans Machine Learning Sequence Alignment Proteins Internet Use Protein Conformation
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Accurate positioning of functional residues with robotics-inspired computational protein design.

Proceedings of the National Academy of Sciences of the United States of America Mar 7, 2022
SignificanceComputational protein design promises to advance applications in medicine and biotechnology by creating proteins with many new and useful functions. However, new functions require the design of specific and often irregular atom-level geom...
Proteins Structure-Activity Relationship Isomerases Models, Molecular Amino Acids Reproducibility of Results Protein Conformation Robotics Protein Engineering Computer-Aided Design Computational Biology Algorithms
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Researchers turn to deep learning to decode protein structures.

Proceedings of the National Academy of Sciences of the United States of America Mar 2, 2022
Problem Solving Computational Biology Proteins Research Personnel Protein Conformation Models, Molecular Deep Learning
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DLPacker: Deep learning for prediction of amino acid side chain conformations in proteins.

Proteins Feb 22, 2022
Prediction of side chain conformations of amino acids in proteins (also termed "packing") is an important and challenging part of protein structure prediction with many interesting applications in protein design. A variety of methods for packing have...
Neural Networks, Computer Deep Learning Amino Acids Proteins Protein Conformation
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