AIMC Topic: Protein Folding

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ODiNPred: comprehensive prediction of protein order and disorder.

Scientific reports Sep 8, 2020
Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however...
Protein Folding Models, Molecular Amino Acids Intrinsically Disordered Proteins Neural Networks, Computer Software Algorithms Computational Biology Proteins Humans Databases, Protein
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A novel fusion based on the evolutionary features for protein fold recognition using support vector machines.

Scientific reports Sep 1, 2020
Protein fold recognition plays a crucial role in discovering three-dimensional structure of proteins and protein functions. Several approaches have been employed for the prediction of protein folds. Some of these approaches are based on extracting fe...
Computational Biology Support Vector Machine Amino Acid Sequence Protein Folding Sequence Analysis, Protein Evolution, Molecular Proteins Databases, Protein
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The proteome landscape of the kingdoms of life.

Nature Jun 17, 2020
Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported, ...
Proteomics Proteome Oxidation-Reduction Deep Learning Ion Transport Glycolysis Homeostasis Proteolysis Carbohydrate Metabolism Chromatography Classification Species Specificity Animals Peptides Bacteroides Iron-Sulfur Proteins Protein Folding Protein Biosynthesis Photosynthesis
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Exploring Successful Parameter Region for Coarse-Grained Simulation of Biomolecules by Bayesian Optimization and Active Learning.

Biomolecules Mar 21, 2020
Accompanied with an increase of revealed biomolecular structures owing to advancements in structural biology, the molecular dynamics (MD) approach, especially coarse-grained (CG) MD suitable for macromolecules, is becoming increasingly important for ...
Protein Folding Proton-Translocating ATPases Machine Learning Molecular Dynamics Simulation
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Sequence-Based Prediction of Fuzzy Protein Interactions.

Journal of molecular biology Feb 27, 2020
It is becoming increasingly recognised that disordered proteins may be fuzzy, in that they can exhibit a wide variety of binding modes. In addition to the well-known process of folding upon binding (disorder-to-order transition), many examples are em...
Protein Folding Sequence Analysis, Protein Protein Interaction Domains and Motifs Sequence Homology Amino Acid Sequence Intrinsically Disordered Proteins Protein Conformation Databases, Protein Models, Molecular Protein Domains Humans Algorithms Protein Binding Fuzzy Logic
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Improved protein structure prediction using potentials from deep learning.

Nature Jan 15, 2020
Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence. This problem is of fundamental importance as the structure of a protein largely determines its function; however, protein str...
Software Deep Learning Proteins Models, Molecular Amino Acid Sequence Protein Folding Caspases Datasets as Topic Protein Conformation
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Machine learning for protein folding and dynamics.

Current opinion in structural biology Dec 24, 2019
Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools. The way si...
Protein Folding Machine Learning Proteins Models, Molecular
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High-accuracy protein structures by combining machine-learning with physics-based refinement.

Proteins Nov 15, 2019
Protein structure prediction has long been available as an alternative to experimental structure determination, especially via homology modeling based on templates from related sequences. Recently, models based on distance restraints from coevolution...
Protein Folding Animals Protein Conformation, alpha-Helical Computational Biology Humans Proteins Protein Conformation, beta-Strand Machine Learning
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Analysis of distance-based protein structure prediction by deep learning in CASP13.

Proteins Sep 13, 2019
This paper reports the CASP13 results of distance-based contact prediction, threading, and folding methods implemented in three RaptorX servers, which are built upon the powerful deep convolutional residual neural network (ResNet) method initiated by...
Protein Conformation Machine Learning Protein Folding Software Sequence Alignment Sequence Analysis, Protein Algorithms Proteins Deep Learning Models, Molecular Computational Biology Crystallography, X-Ray
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Distance-based protein folding powered by deep learning.

Proceedings of the National Academy of Sciences of the United States of America Aug 9, 2019
Direct coupling analysis (DCA) for protein folding has made very good progress, but it is not effective for proteins that lack many sequence homologs, even coupled with time-consuming conformation sampling with fragments. We show that we can accurate...
Sequence Alignment Membrane Proteins Algorithms Models, Molecular Deep Learning Protein Folding Time Factors
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