Beyond traditional magnetic resonance processing with artificial intelligence.

Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained artificial neural networks to solve three problems that until now were deemed "impossible": quadrature detection using only Echo (or Anti-Echo) modulation from the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal intensity at each point in a spectrum processed by any given method; and defining a reference-free score for quantitative access of NMR spectrum quality.

Insights into mechanisms of MALT1 allostery from NMR and AlphaFold dynamic analyses.

Mucosa-associated lymphoid tissue lymphoma-translocation protein 1 (MALT1) is an attractive target for the development of modulatory compounds in the treatment of lymphoma and other cancers. While the three-dimensional structure of MALT1 has been previously determined through X-ray analysis, its dynamic behaviour in solution has remained unexplored. We present here dynamic analyses of the apo MALT1 form along with the E549A mutation.

Combined NMR and molecular dynamics conformational filter identifies unambiguously dynamic ensembles of Dengue protease NS2B/NS3pro.

The dengue protease NS2B/NS3pro has been reported to adopt either an 'open' or a 'closed' conformation. We have developed a conformational filter that combines NMR with MD simulations to identify conformational ensembles that dominate in solution. Experimental values derived from relaxation parameters for the backbone and methyl side chains were compared with the corresponding back-calculated relaxation parameters of different conformational ensembles obtained from free MD simulations.

Resolution enhancement of NMR by decoupling with the low-rank Hankel model.

Nuclear magnetic resonance (NMR) spectroscopy has become a formidable tool for biochemistry and medicine. Although -coupling carries essential structural information it may also limit the spectral resolution. Homonuclear decoupling remains a challenging problem.

Improved Measurement of Solar Neutrinos from the Carbon-Nitrogen-Oxygen Cycle by Borexino and Its Implications for the Standard Solar Model.

We present an improved measurement of the carbon-nitrogen-oxygen (CNO) solar neutrino interaction rate at Earth obtained with the complete Borexino Phase-III dataset. The measured rate, R_{CNO}=6.7_{-0.

NMR spectrum reconstruction as a pattern recognition problem.

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 the corresponding point spread function (PSF) pattern produced by each spectral peak resulting in the highest quality and robust reconstruction of the NUS spectra as demonstrated in simulations and exemplified in this work on 2D H-N correlation spectra of three representative globular proteins with different sizes: Ubiquitin (8.6 kDa), Azurin (14 kDa), and Malt1 (44 kDa).

Assignment of IVL-Methyl side chain of the ligand-free monomeric human MALT1 paracaspase-IgL domain in solution.

Mucosa-associated lymphoid tissue protein 1 (MALT1) plays a key role in adaptive immune responses by modulating specific intracellular signalling pathways that control the development and proliferation of both T and B cells. Dysfunction of these pathways is coupled to the progress of highly aggressive lymphoma as well as to potential development of an array of different immune disorders. In contrast to other signalling mediators, MALT1 is not only activated through the formation of the CBM complex together with the proteins CARMA1 and Bcl10, but also by acting as a protease that cleaves multiple substrates to promote lymphocyte proliferation and survival via the NF-κB signalling pathway.

H, C and N resonance assignment of backbone and IVL-methyl side chain of the S135A mutant NS3pro/NS2B protein of Dengue II virus reveals unique secondary structure features in solution.

The serotype II Dengue (DENV 2) virus is the most prevalent of all four known serotypes. Herein, we present nearly complete H, N, and C backbone and H, C isoleucine, valine, and leucine methyl resonance assignment of the apo S135A catalytically inactive variant of the DENV 2 protease enzyme folded as a tandem formed between the serine protease domain NS3pro and the cofactor NS2B, as well as the secondary structure prediction of this complex based on the assigned chemical shifts using the TALOS-N software. Our results provide a solid ground for future elucidation of the structure and dynamic of the apo NS3pro/NS2B complex, key for adequate development of inhibitors, and a thorough molecular understanding of their function(s).

A Sparse Model-Inspired Deep Thresholding Network for Exponential Signal Reconstruction-Application in Fast Biological Spectroscopy.

The nonuniform sampling (NUS) is a powerful approach to enable fast acquisition but requires sophisticated reconstruction algorithms. Faithful reconstruction from partially sampled exponentials is highly expected in general signal processing and many applications. Deep learning (DL) has shown astonishing potential in this field, but many existing problems, such as lack of robustness and explainability, greatly limit its applications.

Exponential Signal Reconstruction With Deep Hankel Matrix Factorization.

Exponential function is a basic form of temporal signals, and how to fast acquire this signal is one of the fundamental problems and frontiers in signal processing. To achieve this goal, partial data may be acquired but result in severe artifacts in its spectrum, which is the Fourier transform of exponentials. Thus, reliable spectrum reconstruction is highly expected in the fast data acquisition in many applications, such as chemistry, biology, and medical imaging.

NUScon: a community-driven platform for quantitative evaluation of nonuniform sampling in NMR.

Although the concepts of nonuniform sampling (NUS​​​​​​​) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge 4 decades ago , it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e.

Unambiguous Tracking of Protein Phosphorylation by Fast High-Resolution FOSY NMR*.

Dysregulation of post-translational modifications (PTMs) like phosphorylation is often involved in disease. NMR may elucidate exact loci and time courses of PTMs at atomic resolution and near-physiological conditions but requires signal assignment to individual atoms. Conventional NMR methods for this base on tedious global signal assignment that may often fail, as for large intrinsically disordered proteins (IDPs).

Resolution enhancement in NMR spectra by deconvolution with compressed sensing reconstruction.

NMR spectroscopy is one of the basic tools for molecular structure elucidation. Unfortunately, the resolution of the spectra is often limited by inter-nuclear couplings. The existing workarounds often alleviate the problem by trading it for another deficiency, such as spectral artefacts or difficult sample preparation and, thus, are rarely used.

Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting.

In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used 36 honey samples from different sources to which various fluorophores were added (-(2,2'-bipyridyl) dichlororuthenium(II) (Ru(bpy)), zinc(II) 8-hydroxyquinoline-5-sulfonate (8-Ox-Zn), and thiazole orange in the presence of two types of deoxyribonucleic acid).

Signaling Mechanism of Phytochromes in Solution.

Phytochrome proteins guide the red/far-red photoresponse of plants, fungi, and bacteria. Crystal structures suggest that the mechanism of signal transduction from the chromophore to the output domains involves refolding of the so-called PHY tongue. It is currently not clear how the two other notable structural features of the phytochrome superfamily, the so-called helical spine and a knot in the peptide chain, are involved in photoconversion.

Aβ(1-42) tetramer and octamer structures reveal edge conductivity pores as a mechanism for membrane damage.

Formation of amyloid-beta (Aβ) oligomer pores in the membrane of neurons has been proposed to explain neurotoxicity in Alzheimer's disease (AD). Here, we present the three-dimensional structure of an Aβ oligomer formed in a membrane mimicking environment, namely an Aβ(1-42) tetramer, which comprises a six stranded β-sheet core. The two faces of the β-sheet core are hydrophobic and surrounded by the membrane-mimicking environment while the edges are hydrophilic and solvent-exposed.

Review and Prospect: Deep Learning in Nuclear Magnetic Resonance Spectroscopy.

Since the concept of deep learning (DL) was formally proposed in 2006, it has had a major impact on academic research and industry. Nowadays, DL provides an unprecedented way to analyze and process data with demonstrated great results in computer vision, medical imaging, natural language processing, and so forth. Herein, applications of DL in NMR spectroscopy are summarized, and a perspective for DL as an entirely new approach that is likely to transform NMR spectroscopy into a much more efficient and powerful technique in chemistry and life sciences is outlined.

Fast time-resolved NMR with non-uniform sampling.

NMR spectroscopy is a versatile tool for studying time-dependent processes: chemical reactions, phase transitions or macromolecular structure changes. However, time-resolved NMR is usually based on the simplest among available techniques - one-dimensional spectra serving as "snapshots" of the studied process. One of the reasons is that multidimensional experiments are very time-expensive due to costly sampling of evolution time space.

Modulation of Structural Heterogeneity Controls Phytochrome Photoswitching.

Phytochromes sense red/far-red light and control many biological processes in plants, fungi, and bacteria. Although the crystal structures of dark- and light-adapted states have been determined, the molecular mechanisms underlying photoactivation remain elusive. Here, we demonstrate that the conserved tongue region of the PHY domain of a 57-kDa photosensory module of Deinococcus radiodurans phytochrome changes from a structurally heterogeneous dark state to an ordered, light-activated state.

Rapid Biophysical Characterization and NMR Spectroscopy Structural Analysis of Small Proteins from Bacteria and Archaea.

Proteins encoded by small open reading frames (sORFs) have a widespread occurrence in diverse microorganisms and can be of high functional importance. However, due to annotation biases and their technically challenging direct detection, these small proteins have been overlooked for a long time and were only recently rediscovered. The currently rapidly growing number of such proteins requires efficient methods to investigate their structure-function relationship.

Structural characterization and biological function of bivalent binding of CD2AP to intrinsically disordered domain of chikungunya virus nsP3 protein.

Alphavirus nsP3 proteins contain long, intrinsically disordered, hypervariable domains, HVD, which serve as hubs for interaction with many cellular proteins. Here, we have deciphered the mechanism and function of HVD interaction with host factors in alphavirus replication. Using NMR spectroscopy, we show that CHIKV HVD contains two SH3 domain-binding sites.

Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning.

Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental times. We present a proof-of-concept of the application of deep learning and neural networks for high-quality, reliable, and very fast NMR spectra reconstruction from limited experimental data. We show that the neural network training can be achieved using solely synthetic NMR signals, which lifts the prohibiting demand for a large volume of realistic training data usually required for a deep learning approach.

Inhibitors of DNA Methylation and Histone Deacetylation as Epigenetically Active Drugs for Anticancer Therapy.

Gene expression is regulated and tightly controlled by epigenetic mechanisms. Alterations of these mechanisms are frequently observed in various diseases, particularly, in various types of cancer. Malignant transformation is caused by the impairment of the mechanisms of cell differentiation and cell cycle control associated with epigenetic changes.

High-fidelity spectroscopy reconstruction in accelerated NMR.

Non-uniform sampling significantly accelerates the data acquisition time in NMR spectroscopy, but spectra must be reconstructed with appropriate methods. A high-fidelity reconstruction method is proposed to preserve low-intensity spectral peaks and provide stable reconstruction under different sampling trials.