AIMC Topic: Protein Folding

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The AlphaFold Database of Protein Structures: A Biologist's Guide.

Journal of molecular biology Oct 29, 2021
AlphaFold, the deep learning algorithm developed by DeepMind, recently released the three-dimensional models of the whole human proteome to the scientific community. Here we discuss the advantages, limitations and the still unsolved challenges of the...
Humans Models, Molecular Protein Conformation Algorithms Protein Folding Molecular Biology Deep Learning Computational Biology Proteome Databases, Factual
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Protein Fold Recognition by Combining Support Vector Machines and Pairwise Sequence Similarity Scores.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Protein fold recognition is one of the most essential steps for protein structure prediction, aiming to classify proteins into known protein folds. There are two main computational approaches: one is the template-based method based on the alignment s...
Pattern Recognition, Automated Protein Folding Sequence Analysis, Protein Algorithms Computational Biology Support Vector Machine Proteins
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Mapping the glycosyltransferase fold landscape using interpretable deep learning.

Nature communications Sep 27, 2021
Glycosyltransferases (GTs) play fundamental roles in nearly all cellular processes through the biosynthesis of complex carbohydrates and glycosylation of diverse protein and small molecule substrates. The extensive structural and functional diversifi...
Protein Structure, Tertiary Glycosyltransferases Protein Structure, Secondary Protein Folding Sequence Alignment Databases, Genetic Amino Acid Sequence Datasets as Topic Computational Biology Glycosylation Deep Learning
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When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14-(tFold for CASP14 contact prediction).

Proteins Sep 23, 2021
In this paper, we report our tFold framework's performance on the inter-residue contact prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our tFold framework seamlessly combines both homologous sequences and st...
Neural Networks, Computer Sequence Analysis, Protein Structural Homology, Protein Proteins Models, Molecular Protein Folding Software Reproducibility of Results Computational Biology
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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...
Protein Folding Databases, Protein Models, Molecular Protein Conformation Neural Networks, Computer Software Computational Biology Proteins
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New Frontiers for Machine Learning in Protein Science.

Journal of molecular biology Sep 6, 2021
Protein function is fundamentally reliant on inter-molecular interactions that underpin the ability of proteins to form complexes driving biological processes in living cells. Increasingly, such interactions are recognised as being formed between pro...
Humans Machine Learning Protein Aggregates Phase Transition Protein Folding Animals Protein Interaction Maps Proteins
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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 ...
Machine Learning Animals Amino Acid Sequence Intrinsically Disordered Proteins Protein Conformation Protein Folding Humans
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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...
Hydrogen Bonding Protein Folding Sequence Alignment Sequence Analysis, Protein Proteins Models, Molecular Protein Conformation Software Deep Learning Computational Biology
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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...
Models, Molecular Computational Biology Humans Datasets as Topic Reproducibility of Results Diacylglycerol O-Acyltransferase Proteome Protein Conformation Deep Learning Membrane Proteins Protein Folding Glucose-6-Phosphatase
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Accurate prediction of protein structures and interactions using a three-track neural network.

Science (New York, N.Y.) Jul 15, 2021
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track ...
Protein Subunits Sphingosine N-Acyltransferase Cryoelectron Microscopy Protein Folding Membrane Proteins Multiprotein Complexes Proteins Databases, Protein ADAM Proteins Neural Networks, Computer Receptors, G-Protein-Coupled Crystallography, X-Ray Computer Simulation Models, Molecular Protein Conformation Deep Learning Amino Acid Sequence
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