AIMC Topic: Protein Conformation

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Protein model accuracy estimation empowered by deep learning and inter-residue distance prediction in CASP14.

Scientific reports May 25, 2021
The inter-residue contact prediction and deep learning showed the promise to improve the estimation of protein model accuracy (EMA) in the 13th Critical Assessment of Protein Structure Prediction (CASP13). To further leverage the improved inter-resid...
Caspases Protein Conformation Computational Biology Models, Molecular Deep Learning
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Deep Learning-Based Advances in Protein Structure Prediction.

International journal of molecular sciences May 24, 2021
Obtaining an accurate description of protein structure is a fundamental step toward understanding the underpinning of biology. Although recent advances in experimental approaches have greatly enhanced our capabilities to experimentally determine prot...
Sequence Analysis, Protein Databases, Protein Models, Molecular Protein Conformation Cryoelectron Microscopy Amino Acid Sequence Deep Learning Computational Biology Proteins Software Algorithms Neural Networks, Computer
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DeepDISE: DNA Binding Site Prediction Using a Deep Learning Method.

International journal of molecular sciences May 24, 2021
It is essential for future research to develop a new, reliable prediction method of DNA binding sites because DNA binding sites on DNA-binding proteins provide critical clues about protein function and drug discovery. However, the current prediction ...
Software Animals Deep Learning Humans DNA DNA-Binding Proteins Protein Conformation Computational Biology Proteome Binding Sites
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Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with DiffNets.

Nature communications May 21, 2021
Understanding the structural determinants of a protein's biochemical properties, such as activity and stability, is a major challenge in biology and medicine. Comparing computer simulations of protein variants with different biochemical properties is...
Molecular Dynamics Simulation Software Deep Learning Computational Biology Proteins Algorithms Computer Simulation Protein Conformation Myosins
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Ligand-Dependent Conformational Transitions in Molecular Dynamics Trajectories of GPCRs Revealed by a New Machine Learning Rare Event Detection Protocol.

Molecules (Basel, Switzerland) May 20, 2021
Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins,...
Ligands Machine Learning Protein Conformation Receptors, G-Protein-Coupled Humans Molecular Dynamics Simulation
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Beyond Tripeptides Two-Step Active Machine Learning for Very Large Data sets.

Journal of chemical theory and computation Apr 27, 2021
Self-assembling peptide nanostructures have been shown to be of great importance in nature and have presented many promising applications, for example, in medicine as drug-delivery vehicles, biosensors, and antivirals. Being very promising candidates...
Algorithms Supervised Machine Learning Datasets as Topic Oligopeptides Protein Conformation Computational Chemistry Nanostructures Programming Languages
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PCprophet: a framework for protein complex prediction and differential analysis using proteomic data.

Nature methods Apr 15, 2021
Despite the availability of methods for analyzing protein complexes, systematic analysis of complexes under multiple conditions remains challenging. Approaches based on biochemical fractionation of intact, native complexes and correlation of protein ...
Databases, Protein Bayes Theorem Chromatography, Gel Protein Conformation Software Proteomics Proteins Machine Learning
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The whole is greater than its parts: ensembling improves protein contact prediction.

Scientific reports Apr 13, 2021
The prediction of amino acid contacts from protein sequence is an important problem, as protein contacts are a vital step towards the prediction of folded protein structures. We propose that a powerful concept from deep learning, called ensembling, c...
Neural Networks, Computer Models, Molecular Protein Conformation Sequence Analysis, Protein Deep Learning Protein Folding Computational Biology Software Proteins Algorithms
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Reconstruction of ARNT PAS-B Unfolding Pathways by Steered Molecular Dynamics and Artificial Neural Networks.

Journal of chemical theory and computation Mar 29, 2021
Several experimental studies indicated that large conformational changes, including partial domain unfolding, have a role in the functional mechanisms of the basic helix loop helix Per/ARNT/SIM (bHLH-PAS) transcription factors. Recently, single-molec...
Protein Unfolding Molecular Dynamics Simulation Neural Networks, Computer Microscopy, Atomic Force Basic Helix-Loop-Helix Transcription Factors Protein Conformation
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Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks.

PLoS computational biology Mar 26, 2021
The topology of protein folds can be specified by the inter-residue contact-maps and accurate contact-map prediction can help ab initio structure folding. We developed TripletRes to deduce protein contact-maps from discretized distance profiles by en...
Sequence Analysis, Protein Protein Conformation Protein Folding Computational Biology Reproducibility of Results Neural Networks, Computer Proteins
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