AIMC Topic: Protein Conformation

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XENet: Using a new graph convolution to accelerate the timeline for protein design on quantum computers.

PLoS computational biology Sep 27, 2021
Graph representations are traditionally used to represent protein structures in sequence design protocols in which the protein backbone conformation is known. This infrequently extends to machine learning projects: existing graph convolution algorith...
Neural Networks, Computer Proteins Models, Molecular Protein Conformation Computer Graphics Computers Computer-Aided Design Computational Biology Machine Learning Algorithms
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FALCON2: a web server for high-quality prediction of protein tertiary structures.

BMC bioinformatics Sep 15, 2021
BACKGROUND: Accurate prediction of protein tertiary structures is highly desired as the knowledge of protein structures provides invaluable insights into protein functions. We have designed two approaches to protein structure prediction, including a ...
Protein Conformation Computers Proteins Amino Acid Sequence Neural Networks, Computer Software
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Improved 3-D Protein Structure Predictions using Deep ResNet Model.

The protein journal Sep 12, 2021
Protein Structure Prediction (PSP) is considered to be a complicated problem in computational biology. In spite of, the remarkable progress made by the co-evolution-based method in PSP, it is still a challenging and unresolved problem. Recently, alon...
Neural Networks, Computer Software Models, Molecular Protein Conformation Protein Folding Computational Biology Proteins Databases, Protein
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Protein inter-residue contact and distance prediction by coupling complementary coevolution features with deep residual networks in CASP14.

Proteins Aug 19, 2021
This article reports and analyzes the results of protein contact and distance prediction by our methods in the 14th Critical Assessment of techniques for protein Structure Prediction (CASP14). A new deep learning-based contact/distance predictor was ...
Sequence Alignment Sequence Analysis, Protein Software Deep Learning Computational Biology Proteins Models, Molecular Protein Conformation
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PYTHIA: Deep Learning Approach for Local Protein Conformation Prediction.

International journal of molecular sciences Aug 17, 2021
Protein Blocks (PBs) are a widely used structural alphabet describing local protein backbone conformation in terms of 16 possible conformational states, adopted by five consecutive amino acids. The representation of complex protein 3D structures as 1...
Databases, Protein Models, Molecular Protein Conformation Sequence Analysis, Protein Algorithms Humans Deep Learning Proteins Neural Networks, Computer Software
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On the Potential of Machine Learning to Examine the Relationship Between Sequence, Structure, Dynamics and Function of Intrinsically Disordered Proteins.

Journal of molecular biology Aug 12, 2021
Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) interspersed between folded domains-are generally characterized as having no ...
Humans Machine Learning Intrinsically Disordered Proteins Animals Protein Conformation Amino Acid Sequence Protein Folding
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Deep learning to design nuclear-targeting abiotic miniproteins.

Nature chemistry Aug 9, 2021
There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we show how machine learning enables the de novo design of ...
Molecular Weight Datasets as Topic Cell Nucleus Protein Conformation Protein Transport Cytosol Deep Learning Proteins Models, Molecular
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Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14.

Proteins Aug 7, 2021
In this article, we report 3D structure prediction results by two of our best server groups ("Zhang-Server" and "QUARK") in CASP14. These two servers were built based on the D-I-TASSER and D-QUARK algorithms, which integrated four newly developed com...
Computational Biology Proteins Models, Molecular Software Deep Learning Sequence Alignment Sequence Analysis, Protein Protein Conformation Hydrogen Bonding Protein Folding
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Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability in cryo-EM.

Nature methods Jul 29, 2021
Structural flexibility and/or dynamic interactions with other molecules is a critical aspect of protein function. Cryogenic electron microscopy (cryo-EM) provides direct visualization of individual macromolecules sampling different conformational and...
Imaging, Three-Dimensional Software Humans Spike Glycoprotein, Coronavirus Cryoelectron Microscopy Protein Conformation Algorithms Neural Networks, Computer Deep Learning
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Highly accurate protein structure prediction for the human proteome.

Nature Jul 22, 2021
Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues i...
Proteome Membrane Proteins Protein Folding Models, Molecular Humans Datasets as Topic Deep Learning Glucose-6-Phosphatase Reproducibility of Results Protein Conformation Computational Biology Diacylglycerol O-Acyltransferase
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