Biomolecular NMR Research Articles

Expanding the Toolset of Biomolecular NMR with Efficient and Cost-Effective 17O-Labeling via Bacterial Expression.

Oxygen plays a central role in biomolecular structures and functions, with 17O NMR emerging as a powerful tool for elucidating biomolecular properties. However, the low natural abundance of the NMR-active isotope, 17O (0.0373 %), presents a significant hurdle to its widespread application. Here, we introduce a rapid and cost-effective approach for amino acid-specific 17O-labeling of recombinant proteins. Using a common bacterial expression system and with a 30-minute rapid synthesis protocol of 17O-labeled amino acids via mechanochemical saponification, we have generated Leu- and Phe-specific 17O-labeled recombinant proteins derived from diverse organisms, including CrgA and FtsQ from Mycobacterium tuberculosis and E protein from SARS-CoV-2 virus, demonstrating the applicability of our technique for amino acids known to be isotopically labeled without scrambling. We have acquired magic-angle-spinning 17O NMR of these proteins to confirm the successful 17O labeling and illustrate the sensitivity of 17O NMR to the protein's local structural environments. Our work significantly broadens the accessibility of 17O-NMR, empowering researchers to delve deeper into protein biophysics and biochemistry. This approach opens new avenues for understanding cellular processes at the molecular level by providing an effective tool for investigating oxygen-related interactions and chemistry within biomolecules.

Insights into the Structure and Dynamics of Proteins from 19F Solution NMR Spectroscopy.

19F NMR spectroscopy has recently witnessed a resurgence as an attractive analytical tool for the study of the structure and dynamics of biomolecules in vitro and in cells, despite reports of its applications in biomolecular NMR since the 1970s. The high gyromagnetic ratio, large chemical shift dispersion, and complete absence of the spin 1/2 19F nucleus from biomolecules results in background-free, high-resolution 19F NMR spectra. The introduction of 19F probes in a few selected locations in biomolecules reduces spectral crowding despite its increased line width in comparison to typical 1H NMR line widths and allows rapid site-specific measurements from simple 1D spectra alone. The design and synthesis of novel 19F probes with reduced line widths and increased chemical shift sensitivity to the surrounding environment, together with advances in labeling techniques, NMR methodology, and hardware, have overcome several drawbacks of 19F NMR spectroscopy. The increased interest and widespread use of 19F NMR spectroscopy of biomolecules is gradually establishing it as a sensitive and high-resolution probe of biomolecular structure and dynamics, supplementing traditional 13C/15N-based methods. This Review focuses on the advances in 19F solution NMR spectroscopy of proteins in the past 5 years, with an emphasis on novel 19F tags and labeling techniques, NMR experiments to probe protein structure and conformational dynamics in vitro, and in-cell NMR applications.

Synthesis of a 13C/2H Labeled Building Block to Probe the Phosphotyrosine Interactome Using Biomolecular NMR Spectroscopy.

Phosphotyrosine (pTyr) recognition coordinates the assembly of protein complexes, thus controlling key events of cell cycle, cell development and programmed cell death. Although many aspects of membrane receptor function and intracellular signal transduction have been deciphered in the last decades, the details of how phosphorylation alters protein-protein interaction and creates regulating switches of protein activity and localization often remains unclear. We developed a synthetic route to a protected phophotyrosine building block with isolated 13C-1H spins in the aromatic ring. The compound can be used for solid phase peptide synthesis (SPPS) and readily applied to study affinity, dynamics and interactions on an atomic level using NMR spectroscopy. As a first example, we prepared an isotopologue of a pTyr containing 12mer peptide (pY1021) as part of the platelet-derived growth factor to analyze the binding to the phospholipase C-γ (PLCγ-1) SH2 domain.

Perspective: on the importance of extensive, high-quality and reliable deposition of biomolecular NMR data in the age of artificial intelligence

Artificial intelligence (AI) models are revolutionising scientific data analysis but are reliant on large training data sets. While artificial training data can be used in the context of NMR processing and data analysis methods, relating NMR parameters back to protein sequence and structure requires experimental data. In this perspective we examine what the biological NMR community needs to do, in order to store and share its data better so that we can make effective use of AI methods to further our understanding of biological molecules. We argue, first, that the community should be depositing much more of its experimental data. In particular, we should be depositing more spectra and dynamics data. Second, the NMR data deposited needs to capture the full information content required to be able to use and validate it adequately. The NMR Exchange Format (NEF) was designed several years ago to do this. The widespread adoption of NEF combined with a new proposal for dynamics data specifications come at the right time for the community to expand its deposition of data. Third, we highlight the importance of expanding and safeguarding our experimental data repository, the Biological Magnetic Resonance Data Bank (BMRB), not only in the interests of NMR spectroscopists, but biological scientists more widely. With this article we invite others in the biological NMR community to champion increased (possibly mandatory) data deposition, to get involved in designing new NEF specifications, and to advocate on behalf of the BMRB within the wider scientific community.

Micromolar fluoride contamination arising from glass NMR tubes and a simple solution for biomolecular applications.

Fluorine (19F) NMR is emerging as an invaluable analytical technique in chemistry, biochemistry, structural biology, material science, drug discovery, and medicine, especially due to the inherent rarity of naturally occurring fluorine in biological, organic, and inorganic compounds. Here, we revisit the under-reported problem of fluoride leaching from new and unused glass NMR tubes. We characterised the leaching of free fluoride from various types of new and unused glass NMR tubes over the course of several hours and quantify this contaminant to be at micromolar concentrations for typical NMR sample volumes across multiple glass types and brands. We find that this artefact is undetectable for samples prepared in quartz NMR tubes within the timeframes of our experiments. We also observed that pre-soaking new glass NMR tubes combined with rinsing removes this contamination below micromolar levels. Given the increasing popularity of 19F NMR across a wide range of fields, increasing popularity of single-use screening tubes, the long collection times required for relaxation studies and samples of low concentrations, and the importance of avoiding contamination in all NMR experiments, we anticipate that our simple solution will be useful to biomolecular NMR spectroscopists.

Sensitivity enhancement in biomolecular NMR: Characterization and optimization of LC-photo-CIDNP for the structural analysis of proteins in solution

Sensitivity enhancement in biomolecular NMR: Characterization and optimization of LC-photo-CIDNP for the structural analysis of proteins in solution

The 100-protein NMR spectra dataset: A resource for biomolecular NMR data analysis

Multidimensional NMR spectra are the basis for studying proteins by NMR spectroscopy and crucial for the development and evaluation of methods for biomolecular NMR data analysis. Nevertheless, in contrast to derived data such as chemical shift assignments in the BMRB and protein structures in the PDB databases, this primary data is in general not publicly archived. To change this unsatisfactory situation, we present a standardized set of solution NMR data comprising 1329 2–4-dimensional NMR spectra and associated reference (chemical shift assignments, structures) and derived (peak lists, restraints for structure calculation, etc.) annotations. With the 100-protein NMR spectra dataset that was originally compiled for the development of the ARTINA deep learning-based spectra analysis method, 100 protein structures can be reproduced from their original experimental data. The 100-protein NMR spectra dataset is expected to help the development of computational methods for NMR spectroscopy, in particular machine learning approaches, and enable consistent and objective comparisons of these methods.

The synthesis of specifically isotope labelled fluorotryptophan and its use in mammalian cell-based protein expression for 19F-NMR applications.

19F nuclei serve as versatile sensors for detecting protein interactions and dynamics in biomolecular NMR spectroscopy. Although various methods have been developed to incorporate fluorine-containing aromatic residues into proteins using E. coli or cell-free expression techniques, similar approaches for protein production in mammalian cell lines remain limited. Here, we present a cost-effective synthetic route to obtain selectively deuterated, carbon-13 labeled fluorotryptophan and demonstrate its use in introducing 19F-13C spin pairs into carbonic anhydrase 2 and superoxide dismutase, following an expression protocol utilizing HEK cells.

Improving Geometric Validation Metrics and Ensuring Consistency with Experimental Data through TrioSA: An NMR Refinement Protocol.

Protein model refinement a the crucial step in improving the quality of a predicted protein model. This study presents an NMR refinement protocol called TrioSA (torsion-angle and implicit-solvation-optimized simulated annealing) that improves the accuracy of backbone/side-chain conformations and the overall structural quality of proteins. TrioSA was applied to a subset of 3752 solution NMR protein structures accompanied by experimental NMR data: distance and dihedral angle restraints. We compared the initial NMR structures with the TrioSA-refined structures and found significant improvements in structural quality. In particular, we observed a reduction in both the maximum and number of NOE (nuclear Overhauser effect) violations, indicating better agreement with experimental NMR data. TrioSA improved geometric validation metrics of NMR protein structure, including backbone accuracy and the secondary structure ratio. We evaluated the contribution of each refinement element and found that the torsional angle potential played a significant role in improving the geometric validation metrics. In addition, we investigated protein-ligand docking to determine if TrioSA can improve biological outcomes. TrioSA structures exhibited better binding prediction compared to the initial NMR structures. This study suggests that further development and research in computational refinement methods could improve biomolecular NMR structural determination.

Cross-Polarization Schemes for Improved Heteronuclear Transfers Involving Labile Protons in Biomolecular Solution NMR.

INEPT-based experiments are widely used for 1 H→15 N transfers, but often fail when involving labile protons due to solvent exchanges. J-based cross polarization (CP) strategies offer a more efficient alternative to perform such transfers, particularly when leveraging the Hwater HN exchange process to boost the 1 H→15 N transfer process. This leveraging, however, demands the simultaneous spin-locking of both Hwater and HN protons by a strong 1 H RF field, while fulfilling the γH B1,H =γN B1,N Hartmann-Hahn matching condition. Given the low value of γN /γH , however, these demands are often incompatible-particularly when experiments are executed by the power-limited cryogenic probes used in contemporary high field NMR. The present manuscript discusses CP alternatives that can alleviate this limitation, and evaluates their performance on urea, amino acids, and intrinsically disordered proteins. These alternatives include new CP variants based on frequency-swept and phase-modulated pulses, designed to simultaneously fulfill the aforementioned conflicting conditions. Their performances vis-à-vis current options are theoretically analyzed with Liouville-space simulations, and experimentally tested with double and triple resonance transfer experiments.

Cross‐Polarization Schemes for Improved Heteronuclear Transfers Involving Labile Protons in Biomolecular Solution NMR

AbstractINEPT‐based experiments are widely used for 1H→15N transfers, but often fail when involving labile protons due to solvent exchanges. J‐based cross polarization (CP) strategies offer a more efficient alternative to perform such transfers, particularly when leveraging the Hwater HN exchange process to boost the 1H→15N transfer process. This leveraging, however, demands the simultaneous spin‐locking of both Hwater and HN protons by a strong 1H RF field, while fulfilling the γHB1,H=γNB1,N Hartmann‐Hahn matching condition. Given the low value of γN/γH, however, these demands are often incompatible—particularly when experiments are executed by the power‐limited cryogenic probes used in contemporary high field NMR. The present manuscript discusses CP alternatives that can alleviate this limitation, and evaluates their performance on urea, amino acids, and intrinsically disordered proteins. These alternatives include new CP variants based on frequency‐swept and phase‐modulated pulses, designed to simultaneously fulfill the aforementioned conflicting conditions. Their performances vis‐à‐vis current options are theoretically analyzed with Liouville‐space simulations, and experimentally tested with double and triple resonance transfer experiments.

Molecular basis of β-lactam antibiotic resistance of ESKAPE bacterium E. faecium Penicillin Binding Protein PBP5

Penicillin-binding proteins (PBPs) are essential for the formation of the bacterial cell wall. They are also the targets of β-lactam antibiotics. In Enterococcus faecium, high levels of resistance to β-lactams are associated with the expression of PBP5, with higher levels of resistance associated with distinct PBP5 variants. To define the molecular mechanism of PBP5-mediated resistance we leveraged biomolecular NMR spectroscopy of PBP5 – due to its size (>70 kDa) a challenging NMR target. Our data show that resistant PBP5 variants show significantly increased dynamics either alone or upon formation of the acyl-enzyme inhibitor complex. Furthermore, these variants also exhibit increased acyl-enzyme hydrolysis. Thus, reducing sidechain bulkiness and expanding surface loops results in increased dynamics that facilitates acyl-enzyme hydrolysis and, via increased β-lactam antibiotic turnover, facilitates β-lactam resistance. Together, these data provide the molecular basis of resistance of clinical E. faecium PBP5 variants, results that are likely applicable to the PBP family.

Efficient 18.8T MAS-DNP NMR reveals hidden side chains in amyloid fibrils.

Amyloid fibrils are large and insoluble protein assemblies composed of a rigid core associated with a cross-β arrangement rich in β-sheet structural elements. It has been widely observed in solid-state NMR experiments that semi-rigid protein segments or side chains do not yield easily observable NMR signals at room temperature. The reasons for the missing peaks may be due to the presence of unfavorable dynamics that interfere with NMR experiments, which result in very weak or unobservable NMR signals. Therefore, for amyloid fibrils, semi-rigid and dynamically disordered segments flanking the amyloid core are very challenging to study. Here, we show that high-field dynamic nuclear polarization (DNP), an NMR hyperpolarization technique typically performed at low temperatures, can circumvent this issue because (i) the low-temperature environment (~ 100K) slows down the protein dynamics to escape unfavorable detection regime, (ii) DNP improves the overall NMR sensitivity including those offlexible side chains, and (iii) efficient cross-effect DNP biradicals (SNAPol-1) optimized for high-field DNP (≥ 18.8T) are employed to offer high sensitivity and resolution suitable for biomolecular NMR applications. By combining these factors, we have successfully established an impressive enhancement factor of ε ~ 50 on amyloid fibrils using an 18.8T/ 800MHz magnet. We have compared the DNP efficiencies of M-TinyPol, NATriPol-3, and SNAPol-1 biradicals on amyloid fibrils. We found that SNAPol-1 (with ε ~ 50) outperformed the other two radicals. The MAS DNP experiments revealed signals of flexible side chains previously inaccessible at conventional room-temperature experiments. These results demonstrate the potential of MAS-DNP NMR as a valuable tool for structural investigations of amyloid fibrils, particularly for side chains and dynamically disordered segments otherwise hidden at room temperature.

Facilitating the structural characterisation of non-canonical amino acids in biomolecular NMR.

Peptides and proteins containing non-canonical amino acids (ncAAs) are a large and important class of biopolymers. They include non-ribosomally synthesised peptides, post-translationally modified proteins, expressed or synthesised proteins containing unnatural amino acids, and peptides and proteins that are chemically modified. Here, we describe a general procedure for generating atomic descriptions required to incorporate ncAAs within popular NMR structure determination software such as CYANA, CNS, Xplor-NIH and ARIA. This procedure is made publicly available via the existing Automated Topology Builder (ATB) server (https://atb.uq.edu.au, last access: 17 February 2023) with all submitted ncAAs stored in a dedicated database. The described procedure also includes a general method for linking of sidechains of amino acids from CYANA templates. To ensure compatibility with other systems, atom names comply with IUPAC guidelines. In addition to describing the workflow, 3D models of complex natural products generated by CYANA are presented, including vancomycin. In order to demonstrate the manner in which the templates for ncAAs generated by the ATB can be used in practice, we use a combination of CYANA and CNS to solve the structure of a synthetic peptide designed to disrupt Alzheimer-related protein-protein interactions. Automating the generation of structural templates for ncAAs will extend the utility of NMR spectroscopy to studies of more complex biomolecules, with applications in the rapidly growing fields of synthetic biology and chemical biology. The procedures we outline can also be used to standardise the creation of structural templates for any amino acid and thus have the potential to impact structural biology more generally.

NMRtist: an online platform for automated biomolecular NMR spectra analysis.

We present NMRtist, an online platform that combines deep learning, large-scale optimization and cloud computing to automate protein NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking, chemical shift assignment and protein structure determination. The system can be used by non-experts and allows protein assignments and structures to be determined within hours after the measurements, strictly without any human intervention. NMRtist is freely available to non-commercial users at https://nmrtist.org. Supplementary data are available at Bioinformatics online.

Band-selective universal 90° and 180° rotation pulses covering the aliphatic carbon chemical shift range for triple resonance experiments on 1.2 GHz spectrometers

Biomolecular NMR spectroscopy requires large magnetic field strengths for high spectral resolution. Today’s highest fields comprise proton Larmor frequencies of 1.2 GHz and even larger field strengths are to be expected in the future. In protein triple resonance experiments, various carbon bandwidths need to be excited by selective pulses including the large aliphatic chemical shift range. When the spectrometer field strength is increased, the length of these pulses has to be decreased by the same factor, resulting in higher rf-amplitudes being necessary in order to cover the required frequency region. Currently available band-selective pulses like Q3/Q5 excite a narrow bandwidth compared to the necessary rf-amplitude. Because the maximum rf-power allowed in probeheads is limited, none of the selective universal rotation pulses reported so far is able to cover the full ^{13}C aliphatic region on 1.2 GHz spectrometers. In this work, we present band-selective 90° and 180° universal rotation pulses (SURBOP90 and SURBOP180) that have a higher ratio of selective bandwidth to maximum rf-amplitude than standard pulses. Simulations show that these pulses perform better than standard pulses, e. g. Q3/Q5, especially when rf-inhomogeneity is taken into account. The theoretical and experimental performance is demonstrated in offset profiles and by implementing the SURBOP pulses in an HNCACB experiment at 1.2 GHz.

INTERFACES. A program for determining the 3D structures of surfaces sites using NMR data

Dynamic nuclear polarization surface enhanced NMR spectroscopy has enabled the determination of high-resolution structures from surface-supported molecules, including single-site heterogeneous catalysts. Structure determinations have largely mimicked the approaches used in biomolecular NMR spectroscopy, namely, using distance measurements to constrain a conformational search. These early demonstrations made use of purpose-built software, which has limited the adoption of the technique. Herein, we describe the open-source program INTERFACES (Interpret NMR to Elucidate or Reconstruct the Full Atomistic Configurations of External Surfaces) which automates the analysis of RE(SP)DOR data as well as the structure determination for surface sites. Distances, angles, dihedral angles, complex orientation, and distance from the support can all be sampled to find all structures that agree with the experimental data. A χ2 metric is used to define the error ranges of the REDOR fits and produce structures with an arbitrary level of confidence. Structural solutions are then provided as both overlays and ORTEP-like probability ellipsoids.

High-fidelity control of spin ensemble dynamics via artificial intelligence: from quantum computing to NMR spectroscopy and imaging.

High-fidelity control of spin ensemble dynamics is essential for many research areas, spanning from quantum computing and radio-frequency (RF) engineering to NMR spectroscopy and imaging. However, attaining robust and high-fidelity spin operations remains an unmet challenge. Using an evolutionary algorithm and artificial intelligence (AI), we designed new RF pulses with customizable spatial or temporal field inhomogeneity compensation. Compared with the standard RF shapes, the new AI-generated pulses show superior performance for bandwidth, robustness, and tolerance to field imperfections. As a benchmark, we constructed a spin entanglement operator for the weakly coupled two-spin-1/2 system of 13CHCl3, achieving high-fidelity transformations under multiple inhomogeneity sources. We then generated band-selective and ultra-broadband RF pulses typical of biomolecular NMR spectroscopy. When implemented in multipulse NMR experiments, the AI-generated pulses significantly increased the sensitivity of medium-size and large protein spectra relative to standard pulse sequences. Finally, we applied the new pulses to typical imaging experiments, showing a remarkable tolerance to changes in the RF field. These AI-generated RF pulses can be directly implemented in quantum information, NMR spectroscopy of biomolecules, magnetic resonance imaging techniques for in vivo and materials sciences.

SpecDB: A relational database for archiving biomolecular NMR spectral data

NMR is a valuable experimental tool in the structural biologist’s toolkit to elucidate the structures, functions, and motions of biomolecules. The progress of machine learning, particularly in structural biology, reveals the critical importance of large, diverse, and reliable datasets in developing new methods and understanding in structural biology and science more broadly. Biomolecular NMR research groups produce large amounts of data, and there is renewed interest in organizing these data to train new, sophisticated machine learning architectures and to improve biomolecular NMR analysis pipelines. The foundational data type in NMR is the free-induction decay (FID). There are opportunities to build sophisticated machine learning methods to tackle long-standing problems in NMR data processing, resonance assignment, dynamics analysis, and structure determination using NMR FIDs. Our goal in this study is to provide a lightweight, broadly available tool for archiving FID data as it is generated at the spectrometer, and grow a new resource of FID data and associated metadata. This study presents a relational schema for storing and organizing the metadata items that describe an NMR sample and FID data, which we call Spectral Database (SpecDB). SpecDB is implemented in SQLite and includes a Python software library providing a command-line application to create, organize, query, backup, share, and maintain the database. This set of software tools and database schema allow users to store, organize, share, and learn from NMR time domain data. SpecDB is freely available under an open source license at https://github.rpi.edu/RPIBioinformatics/SpecDB.

Current limitations of solid-state NMR in carbohydrate and cell wall research

High-resolution investigation of cell wall materials has emerged as an important application of biomolecular solid-state NMR (ssNMR). Multidimensional correlation experiments have become a standard method for obtaining sufficient spectral resolution to determine the polymorphic structure of carbohydrates and address biochemical questions regarding the supramolecular organization of cell walls. Using plant cellulose and matrix polysaccharides as examples, we will review how the multifaceted complexity of polysaccharide structure is impeding the resonance assignment process and assess the available biochemical and spectroscopic approaches that could circumvent this barrier. We will emphasize the ineffectiveness of the current methods in reconciling the ever-growing dataset and deriving structural information. We will evaluate the protocols for achieving efficient and homogeneous hyperpolarization across the cell wall material using magic-angle spinning dynamic nuclear polarization (MAS-DNP). Critical questions regarding the line-broadening effects of cell wall molecules at cryogenic temperature and by paramagnetic biradicals will be considered. Finally, the MAS-DNP method will be placed into a broader context with other structural characterization techniques, such as cryo-electron microscopy, to advance ssNMR research in carbohydrate and cell wall biomaterials.