AIMC Topic: Nuclear Magnetic Resonance, Biomolecular

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Recapitulating the Binding Affinity of Nrf2 for KEAP1 in a Cyclic Heptapeptide, Guided by NMR, X-ray Crystallography, and Machine Learning.

Journal of the American Chemical Society Mar 8, 2021
Macrocycles, including macrocyclic peptides, have shown promise for targeting challenging protein-protein interactions (PPIs). One PPI of high interest is between Kelch-like ECH-Associated Protein-1 (KEAP1) and Nuclear Factor (Erythroid-derived 2)-li...
Machine Learning Peptides Protein Binding Humans Cyclization Kelch-Like ECH-Associated Protein 1 Crystallography, X-Ray Fluorescence Polarization Hydrogen Bonding Mutagenesis, Site-Directed Recombinant Proteins Nuclear Magnetic Resonance, Biomolecular Amino Acid Motifs Structure-Activity Relationship NF-E2-Related Factor 2
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Using Deep Neural Networks to Reconstruct Non-uniformly Sampled NMR Spectra.

Journal of biomolecular NMR Jul 10, 2019
Non-uniform and sparse sampling of multi-dimensional NMR spectra has over the last decade become an important tool to allow for fast acquisition of multi-dimensional NMR spectra with high resolution. The success of non-uniform sampling NMR hinge on b...
Sample Size Supervised Machine Learning Algorithms Image Processing, Computer-Assisted Nuclear Magnetic Resonance, Biomolecular Neural Networks, Computer
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Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index.

Nature communications Jun 7, 2019
Chemical shifts (CS) are determined from NMR experiments and represent the resonance frequency of the spin of atoms in a magnetic field. They contain a mixture of information, encompassing the in-solution conformations a protein adopts, as well as th...
Biophysical Phenomena Nuclear Magnetic Resonance, Biomolecular Protein Structure, Secondary Magnetic Resonance Spectroscopy Models, Molecular Amino Acids Magnetic Resonance Imaging Proteins Neural Networks, Computer
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NMR-STAR: comprehensive ontology for representing, archiving and exchanging data from nuclear magnetic resonance spectroscopic experiments.

Journal of biomolecular NMR Dec 22, 2018
The growth of the biological nuclear magnetic resonance (NMR) field and the development of new experimental technology have mandated the revision and enlargement of the NMR-STAR ontology used to represent experiments, spectral and derived data, and s...
Information Storage and Retrieval Biological Ontologies Software Nuclear Magnetic Resonance, Biomolecular Vocabulary, Controlled
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Environmental metabolomics with data science for investigating ecosystem homeostasis.

Progress in nuclear magnetic resonance spectroscopy Nov 21, 2017
A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems,...
Biota Ecosystem Databases, Factual Humans Metabolomics Animals Nuclear Magnetic Resonance, Biomolecular Machine Learning Multivariate Analysis Ecology Homeostasis
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Publication of nuclear magnetic resonance experimental data with semantic web technology and the application thereof to biomedical research of proteins.

Journal of biomedical semantics May 5, 2016
BACKGROUND: The nuclear magnetic resonance (NMR) spectroscopic data for biological macromolecules archived at the BioMagResBank (BMRB) provide a rich resource of biophysical information at atomic resolution. The NMR data archived in NMR-STAR ASCII fo...
Semantics Biological Ontologies Nuclear Magnetic Resonance, Biomolecular Databases, Protein Internet Proteins
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EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning models.

Protein science : a publication of the Protein Society Aug 1, 2024
Nuclear magnetic resonance (NMR) crystallography is one of the main methods in structural biology for analyzing protein stereochemistry and structure. The chemical shift of the resonance frequency reflects the effect of the protons in a molecule prod...
Machine Learning Software Deep Learning Amino Acid Sequence Proteins Protein Conformation Models, Molecular Nuclear Magnetic Resonance, Biomolecular
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NMRNet: a deep learning approach to automated peak picking of protein NMR spectra.

Bioinformatics (Oxford, England) Aug 1, 2018
MOTIVATION: Automated selection of signals in protein NMR spectra, known as peak picking, has been studied for over 20 years, nevertheless existing peak picking methods are still largely deficient. Accurate and precise automated peak picking would ac...
Software Deep Learning Nuclear Magnetic Resonance, Biomolecular Proteins Macromolecular Substances
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Protein structural information derived from NMR chemical shift with the neural network program TALOS-N.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors, and the artificial neural network based TALOS-N program has been trai...
Carbon Isotopes Neural Networks, Computer Software Models, Molecular Protein Conformation Nuclear Magnetic Resonance, Biomolecular Proteomics Proteins
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