Size Sensitivity of Metabolite Diffusion in Macromolecular Crowds.

Metabolites play crucial roles in cellular processes, yet their diffusion in the densely packed interiors of cells remains poorly understood, compounded by conflicting reports in existing studies. Here, we employ pulsed-gradient stimulated-echo NMR and Brownian/Stokesian dynamics simulations to elucidate the behavior of nano- and subnanometer-sized tracers in crowded environments. Using Ficoll as a crowder, we observe a linear decrease in tracer diffusivity with increasing occupied volume fraction, persisting─somewhat surprisingly─up to volume fractions of 30-40%. While simulations suggest a linear correlation between diffusivity slowdown and particle size, experimental findings hint at a more intricate relationship, possibly influenced by Ficoll's porosity. Simulations and numerical calculations of tracer diffusivity in the E. coli cytoplasm show a nonlinear yet monotonic diffusion slowdown with particle size. We discuss our results in the context of nanoviscosity and discrepancies with existing studies.

A pH-enhanced resolution in benchtop NMR spectroscopy.

NMR spectroscopy is one of the most potent methods in analytical chemistry. NMR titration experiments are particularly useful since they measure molecular binding affinities and other concentration-dependent effects. These experiments, however, require a long series of measurements. An alternative to these serial measurements has recently been presented, exploiting a pH (or generally - a concentration) gradient along the NMR tube. The proposed experiment, although efficient, was based on the sensitivity- and hardware-demanding chemical shift imaging (CSI) method. Thus, it is practically limited to high-resolution NMR spectrometers. This paper proposes modifying and adapting the approach to the popular and cost-efficient benchtop NMR machines. Instead of CSI, we use a device that shifts the NMR tube vertically to measure the spectra of different sample volumes, which have different pH values due to the established gradient along the tube. We demonstrate the potential of the method on the test samples of L-tyrosine and 2,6-lutidine, and two real samples from the food industry - an infant formula and an energy drink. The proposed method boosts spectral resolution and allows for the sampling of a broader range of pH values when compared to the original approach.

Supporting the assignment of NMR spectra with variable-temperature experiments.

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful tools in analytical chemistry. An important step in the analysis of NMR data is the assignment of resonance frequencies to the corresponding atoms in the molecule being investigated. The traditional approach considers the spectrum's characteristic parameters: chemical shift values, internuclear couplings, and peak intensities. In this paper, we show how to support the process of assigning a series of spectra of similar organic compounds by using temperature coefficients, that is, the rates of change in chemical shift values associated with given changes in temperature.

Optimizing measurements of linear changes of NMR signal parameters.

Serial NMR experiments are commonly applied in variable-temperature studies, reaction monitoring, and other tasks. The resonance frequencies often shift linearly over the series, and the shift rates help to characterize the studied system. They can be determined using a classical fitting of peak positions or a more advanced method of Radon transform. However, the optimal procedure for data collection remains to be determined. In this paper, we discuss how to invest experimental time, i.e., whether to measure more scans at the expense of the number of spectra or vice versa. The results indicate that classical fitting provides slightly less error than the Radon transform, although the latter can be the method of choice for a low signal-to-noise ratio. We demonstrate this fact through theoretical consideration, simulations, and an experiment. Finally, we extend our considerations to the linear fitting of peak amplitudes. Interestingly, the optimal setup for measuring peak height changes differs from the one for resonance frequency changes - fewer spectra with more scans provide better results.

Magnetstein: An Open-Source Tool for Quantitative NMR Mixture Analysis Robust to Low Resolution, Distorted Lineshapes, and Peak Shifts.

1H NMR spectroscopy is a powerful tool for analyzing mixtures including determining the concentrations of individual components. When signals from multiple compounds overlap, this task requires computational solutions. They are typically based on peak-picking and the comparison of obtained peak lists with libraries of individual components. This can fail if peaks are not sufficiently resolved or when peak positions differ between the library and the mixture. In this paper, we present Magnetstein, a quantification algorithm rooted in the optimal transport theory that makes it robust to unexpected frequency shifts and overlapping signals. Thanks to this, Magnetstein can quantitatively analyze difficult spectra with the estimation trueness an order of magnitude higher than that of commercial tools. Furthermore, the method is easier to use than other approaches, having only two parameters with default values applicable to a broad range of experiments and requiring little to no preprocessing of the spectra.

Biphasic NMR of Hyperpolarized Suspensions-Real-Time Monitoring of Solute-to-Solid Conversion to Watch Materials Grow.

Nuclear magnetic resonance (NMR) spectroscopy is a key method for the determination of molecular structures. Due to its intrinsically high (i.e., atomistic) resolution and versatility, it has found numerous applications for investigating gases, liquids, and solids. However, liquid-state NMR has found little application for suspensions of solid particles as the resonances of such systems are excessively broadened, typically beyond the detection threshold. Herein, we propose a route to overcoming this critical limitation by enhancing the signals of particle suspensions by >3.000-fold using dissolution dynamic nuclear polarization (d-DNP) coupled with rapid solid precipitation. For the proof-of-concept series of experiments, we employed calcium phosphate (CaP) as a model system. By d-DNP, we boosted the signals of phosphate 31P spins before rapid CaP precipitation inside the NMR spectrometer, leading to the inclusion of the hyperpolarized phosphate into CaP-nucleated solid particles within milliseconds. With our approach, within only 1 s of acquisition time, we obtained spectra of biphasic systems, i.e., micrometer-sized dilute solid CaP particles coexisting with their solution-state precursors. Thus, this work is a step toward real-time characterization of the solid-solution equilibrium. Finally, integrating the hyperpolarized data with molecular dynamics simulations and electron microscopy enabled us to shed light on the CaP formation mechanism in atomistic detail.

Non-uniform sampling of similar NMR spectra and its application to studies of the interaction between alpha-synuclein and liposomes.

The accelerated acquisition of multidimensional NMR spectra using sparse non-uniform sampling (NUS) has been widely adopted in recent years. The key concept in NUS is that a major part of the data is omitted during measurement, and then reconstructed using, for example, compressed sensing (CS) methods. CS requires spectra to be compressible, that is, they should contain relatively few "significant" points. The more compressible the spectrum, the fewer experimental NUS points needed in order for it to be accurately reconstructed. In this paper we show that the CS processing of similar spectra can be enhanced by reconstructing only the differences between them. Accurate reconstruction can be obtained at lower sampling levels as the difference is sparser than the spectrum itself. In many situations this method is superior to "conventional" compressed sensing. We exemplify the concept of "difference CS" with one such case-the study of alpha-synuclein binding to liposomes and its dependence on temperature. To obtain information on temperature-dependent transitions between different states, we need to acquire several dozen spectra at various temperatures, with and without the presence of liposomes. Our detailed investigation reveals that changes in the binding modes of the alpha-synuclein ensemble are not only temperature-dependent but also show non-linear behavior in their transitions. Our proposed CS processing approach dramatically reduces the number of NUS points required and thus significantly shortens the experimental time.

Towards hydrogen-rich ionic (NH4)(BH3NH2BH2NH2BH3) and related molecular NH3BH2NH2BH2NH2BH3.

Attempts of the synthesis of ionic (NH4)(BH3NH2BH2NH2BH3) via a metathetical approach resulted in a mixture of the target compound and partly dehydrogenated molecular NH3BH2NH2BH2NH2BH3 product. The mixed specimen was characterised by NMR and vibrational spectroscopies, and the cocrystal structure was analyzed from powder X-ray diffraction data supported by theoretical density functional theory calculations. The compound crystallises in a P21/c unit cell with the lattice parameters of a = 13.401(11) Å, b = 13.196(8) Å, c = 17.828(12) Å, ß = 128.83(4)°, V = 2556(3) Å3 and Z = 16. Despite their impressive hydrogen content, similar to ammonia borane, both title compounds release hydrogen substantially polluted with borazine and traces of ammonia and diborane.

The assignment of 11 B and 1 H resonances in the post-reaction mixture from the dry synthesis of Li(BH3 NH2 BH2 NH2 BH3 ).

We report a detailed 1 H NMR and 11 B NMR study of as synthesised Li ( BH 3 NH 2 BH 2 NH 2 BH 3 ) obtained in a novel dry-synthesis method. A combination of 1D and 2D single- and triple-quantum techniques was used for the assignment of all observed signals. Minor side-products and reactants were detected in the product: NH 3 BH 3 , Li ( NH 2 BH 3 ) , Li ( BH 4 ) , and two yet unknown salts containing 7-membered chain anions: ( BH 3 NH 2 BH 2 NH 2 BH 2 NH 2 BH 3 ) - and ( BH ( NH 2 BH 3 ) 3 ) - . We believe the assignment provided within this study might be helpful when analysing the mixtures containing numerous ammonia borane derivatives, which often give overlapping signals that are hard to distinguish.

Linear discriminant analysis reveals hidden patterns in NMR chemical shifts of intrinsically disordered proteins.

NMR spectroscopy is key in the study of intrinsically disordered proteins (IDPs). Yet, even the first step in such an analysis-the assignment of observed resonances to particular nuclei-is often problematic due to low peak dispersion in the spectra of IDPs. We show that the assignment process can be aided by finding "hidden" chemical shift patterns specific to the amino acid residue types. We find such patterns in the training data from the Biological Magnetic Resonance Bank using linear discriminant analysis, and then use them to classify spin systems in an α-synuclein sample prepared by us. We describe two situations in which the procedure can greatly facilitate the analysis of NMR spectra. The first involves the mapping of spin systems chains onto the protein sequence, which is part of the assignment procedure-a prerequisite for any NMR-based protein analysis. In the second, the method supports assignment transfer between similar samples. We conducted experiments to demonstrate these cases, and both times the majority of spin systems could be unambiguously assigned to the correct residue types.

Design of a D3h-symmetry prismatic tris-(ferrocene-1,1'-diyl) molecular cage bearing boronate ester linkages.

This paper presents a simple, highly selective, and efficient (isolated yield of 68%) synthesis of a novel D3h-symmetry prismatic tris-(ferrocene-1,1'-diyl) organic cage (FcB-cage) by incorporating a boronate ester as a linkage motif. 1,1'-Diboronated derivatives of ferrocene and 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) were used as the starting materials. The synthesized cage was comprehensively characterized by spectroscopic and microscopic methods, powder X-ray diffraction, thermogravimetry and voltammetry. Cyclic voltammetry analysis revealed the electronic communication between the ferrocene units of the FcB-cage. In addition, to better understand the mechanism behind the synthesis of such a cage, as well as its geometric properties, we performed DFT calculations.

Enhanced Nuclear Magnetic Resonance Spectroscopy with Isotropic Mixing as a Pseudodimension.

Chemical analysis based on liquid-state nuclear magnetic resonance spectroscopy exploits numerous observables, mainly chemical shifts, relaxation rates, and internuclear coupling constants. Regarding the latter, the efficiencies of internuclear coherence transfers may be encoded in spectral peak intensities. The dependencies of these intensities on the experimental parameter that influences the transfer, for example, mixing time, are an important source of structural information. Yet, they are costly to measure and difficult to analyze. Here, we show that peak intensity build-up curves in two-dimensional total correlation spectroscopy (2D TOCSY) experiments may be quickly measured by employing nonuniform sampling and that their analysis can be effective if supported by quantum mechanical calculations. Thus, such curves can be used to form a new, third pseudodimension of the TOCSY spectrum. Similarly to the other two frequency dimensions, this one also resolves ambiguities and provides characteristic information. We show how the approach supports the analysis of a fragment of protein Tau Repeat-4 domain. Yet, its potential applications are far broader, including the analysis of complex mixtures or other polymers.

Clustered sparsity and Poisson-gap sampling.

Non-uniform sampling (NUS) is a popular way of reducing the amount of time taken by multidimensional NMR experiments. Among the various non-uniform sampling schemes that exist, the Poisson-gap (PG) schedules are particularly popular, especially when combined with compressed-sensing (CS) reconstruction of missing data points. However, the use of PG is based mainly on practical experience and has not, as yet, been explained in terms of CS theory. Moreover, an apparent contradiction exists between the reported effectiveness of PG and CS theory, which states that a "flat" pseudo-random generator is the best way to generate sampling schedules in order to reconstruct sparse spectra. In this paper we explain how, and in what situations, PG reveals its superior features in NMR spectroscopy. We support our theoretical considerations with simulations and analyses of experimental data from the Biological Magnetic Resonance Bank (BMRB). Our analyses reveal a previously unnoticed feature of many NMR spectra that explains the success of "blue-noise" schedules, such as PG. We call this feature "clustered sparsity". This refers to the fact that the peaks in NMR spectra are not just sparse but often form clusters in the indirect dimension, and PG is particularly suited to deal with such situations. Additionally, we discuss why denser sampling in the initial and final parts of the clustered signal may be useful.

Development of a universal conductive platform for anchoring photo- and electroactive proteins using organometallic terpyridine molecular wires.

The construction of an efficient conductive interface between electrodes and electroactive proteins is a major challenge in the biosensor and bioelectrochemistry fields to achieve the desired nanodevice performance. Concomitantly, metallo-organic terpyridine wires have been extensively studied for their great ability to mediate electron transfer over a long-range distance. In this study, we report a novel stepwise bottom-up approach for assembling bioelectrodes based on a genetically modified model electroactive protein, cytochrome c553 (cyt c553) and an organometallic terpyridine (TPY) molecular wire self-assembled monolayer (SAM). Efficient anchoring of the TPY derivative (TPY-PO(OH)2) onto the ITO surface was achieved by optimising solvent composition. Uniform surface coverage with the electroactive protein was achieved by binding the cyt c553 molecules via the C-terminal His6-tag to the modified TPY macromolecules containing Earth abundant metallic redox centres. Photoelectrochemical characterisation demonstrates the crucial importance of the metal redox centre for the determination of the desired electron transfer properties between cyt and the ITO electrode. Even without the cyt protein, the ITO-TPY nanosystem reported here generates photocurrents whose densities are 2-fold higher that those reported earlier for ITO electrodes functionalised with the photoactive proteins such as photosystem I in the presence of an external mediator, and 30-fold higher than that of the pristine ITO. The universal chemical platform for anchoring and nanostructuring of (photo)electroactive proteins reported in this study provides a major advancement for the construction of efficient (bio)molecular systems requiring a high degree of precise supramolecular organisation as well as efficient charge transfer between (photo)redox-active molecular components and various types of electrode materials.

Temperature as an Extra Dimension in Multidimensional Protein NMR Spectroscopy.

NMR spectroscopy is a particularly informative method for studying protein structures and dynamics in solution; however, it is also one of the most time-consuming. Modern approaches to biomolecular NMR spectroscopy are based on lengthy multidimensional experiments, the duration of which grows exponentially with the number of dimensions. The experimental time may even be several days in the case of 3D and 4D spectra. Moreover, the experiment often has to be repeated under several different conditions, for example, to measure the temperature-dependent effects in a spectrum (temperature coefficients (TCs)). Herein, a new approach that involves joint sampling of indirect evolution times and temperature is proposed. This allows TCs to be measured through 3D spectra in even less time than that needed to acquire a single spectrum by using the conventional approach. Two signal processing methods that are complementary, in terms of sensitivity and resolution, 1) dividing data into overlapping subsets followed by compressed sensing reconstruction, and 2) treating the complete data set with a variant of the Radon transform, are proposed. The temperature-swept 3D HNCO spectra of two intrinsically disordered proteins, osteopontin and CD44 cytoplasmic tail, show that this new approach makes it possible to determine TCs and their non-linearities effectively. Non-linearities, which indicate the presence of a compact state, are particularly interesting. The complete package of data acquisition and processing software for this new approach are provided.

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., "resolution") or peaks of weak intensity (i.e., "sensitivity"). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the "Nonuniform Sampling Contest" (NUScon), with the objective of determining best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals, and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses, and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a roadmap for continued community-driven development with the ultimate aim of providing best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform.

Variable-temperature NMR spectroscopy for metabolite identification in biological materials.

Nuclear magnetic resonance is a "workhorse technique" used in metabolomics, complementary to mass spectrometry. Unfortunately, only the most basic NMR methods are sensitive enough to allow fast medical screening. The most common of them, a simple 1H NMR, suffers from low dispersion of resonance frequencies, which often hampers the identification of metabolites. In this article we show that 1H NMR spectra contain previously overlooked parameters potentially helpful in metabolite identification, namely the rates of temperature-induced changes of chemical shifts. We prove that they are reproducible between various metabolite mixtures and can be determined quickly when Radon transform is used to process the data.

Benefits of time-resolved nonuniform sampling in reaction monitoring: The case of aza-Michael addition of benzylamine and acrylamide.

Monitoring of chemical reactions is best carried out using methods that sample the test object at a rate greater than the time scale of the processes taking place. The recently proposed time-resolved nonuniform sampling (TR-NUS) method allows the use of two-dimensional (2D) nuclear magnetic resonance (NMR) spectra for this purpose and provides a time resolution equivalent to that achievable using one-dimensional spectra. Herein, we show that TR-NUS acquired data eliminates 2D spectral line disturbances and enables more accurate signal integration and kinetics conclusions. The considerations are exemplified with a seemingly simple aza-Michael reaction of benzylamine and acrylamide. Surprisingly, the product identification is possible only using 2D spectra, although credible monitoring requires TR-NUS.

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. We suggest an approach using the coupling deconvolution in the framework of compressed sensing (CS) spectra processing that leads to a major increase in resolution, sensitivity, and overall quality of NUS reconstruction. A new mathematical description of the decoupling by deconvolution explains the effects of thermal noise and reveals a relation with the underlying assumption of the CS. The gain in resolution and sensitivity for challenging molecular systems is demonstrated for the key HNCA experiment used for protein backbone assignment applied to two large proteins: intrinsically disordered 441-residue Tau and a 509-residue globular bacteriophytochrome fragment. The approach will be valuable in a multitude of chemistry applications, where NMR experiments are compromised by the homonuclear scalar coupling.