AIMC Topic: Nuclear Magnetic Resonance, Biomolecular
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NMR spectrum reconstruction as a pattern recognition problem.
Journal of magnetic resonance (San Diego, Calif. : 1997)
Nov 24, 2022
A new deep neural network based on the WaveNet architecture (WNN) is presented, which is designed to grasp specific patterns in the NMR spectra. When trained at a fixed non-uniform sampling (NUS) schedule, the WNN benefits from pattern recognition of...
Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA.
Nature communications
Oct 18, 2022
Nuclear Magnetic Resonance (NMR) spectroscopy is a major technique in structural biology with over 11,800 protein structures deposited in the Protein Data Bank. NMR can elucidate structures and dynamics of small and medium size proteins in solution, ...
Design and applications of water irradiation devoid RF pulses for ultra-high field biomolecular NMR spectroscopy.
Physical chemistry chemical physics : PCCP
Aug 10, 2022
Water suppression is of paramount importance for many biological and analytical NMR spectroscopy applications. Here, we report the design of a new set of binomial-like radio frequency (RF) pulses that elude water irradiation while exciting or refocus...
Towards autonomous analysis of chemical exchange saturation transfer experiments using deep neural networks.
Journal of biomolecular NMR
May 27, 2022
Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structur...
PHRONESIS: A One-Shot Approach for Sequential Assignment of Protein Resonances by Ultrafast MAS Solid-State NMR Spectroscopy.
Chemphyschem : a European journal of chemical physics and physical chemistry
May 19, 2022
Solid-state NMR (ssNMR) spectroscopy has emerged as the method of choice to analyze the structural dynamics of fibrillar, membrane-bound, and crystalline proteins that are recalcitrant to other structural techniques. Recently, H detection under fast...
Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra.
Journal of biomolecular NMR
Apr 7, 2022
Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) desig...
DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra.
Nature communications
Sep 1, 2021
The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Her...
FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling.
Journal of biomolecular NMR
Apr 19, 2021
In recent years, the transformative potential of deep neural networks (DNNs) for analysing and interpreting NMR data has clearly been recognised. However, most applications of DNNs in NMR to date either struggle to outperform existing methodologies o...
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...
Kelch-Like ECH-Associated Protein 1
Amino Acid Motifs
Cyclization
Structure-Activity Relationship
Crystallography, X-Ray
Protein Binding
Recombinant Proteins
Nuclear Magnetic Resonance, Biomolecular
NF-E2-Related Factor 2
Mutagenesis, Site-Directed
Machine Learning
Hydrogen Bonding
Peptides
Fluorescence Polarization
Humans
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...
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