Unexploited Dimension: New Software for Mixture Analysis by 3D Diffusion-Ordered NMR Spectroscopy

Rapid Characterization of Structural and Behavioral Changes of Therapeutic Proteins by Relaxation and Diffusion 1H-SOFAST NMR Experiments

Biologic drugs have emerged as a rapidly expanding and important modality, offering promising therapeutic solutions by interacting with previously "undruggable" targets, thus significantly expanding the range of modern pharmaceutical applications. However, the inherent complexity of these drugs also introduces liabilities and poses challenges in their development, necessitating efficient screening methods to evaluate the structural stability and behavior. Although nuclear magnetic resonance (NMR) spectroscopy is well-suited for detecting weak interactions, changes in dynamics, high-order structure, and association states of macromolecules in fully formulated samples, the inherent low sensitivity limits its utility as a fast screening and characterization tool. In this study, we present two fast pulsing NMR experiments, namely the band-Selective Optimized Flip-Angle Internally encoded Relaxation (SOFAIR) and the band-Selective Optimized Flip-angle Internally encoded Translational diffusion (SOFIT)), which enable rapid and reliable measurements of transverse relaxation rates and diffusion coefficients with more than 10-fold higher sensitivity compared to commonly used methods, like Carr-Purcell-Meiboom-Gill and diffusion-ordered spectroscopy, allowing the rapid assessment of biologics even at low concentrations. We demonstrated the effectiveness and versatility of these experiments by evaluating several examples, including thermally stressed proteins, proteins at different concentrations, and a therapeutic protein in various formulations. We anticipate that these novel approaches will greatly facilitate the analysis and characterization of biologics during drug discovery.

UV/Visible Diffusion-Ordered Spectroscopy: A Simultaneous Probe of Molecular Size and Electronic Absorption

Based on concepts from nuclear magnetic resonance, we have developed UV/vis diffusion-ordered spectroscopy, which simultaneously probes the size and electronic absorption spectrum of molecules and particles. We use simple flow technology to create a step-function concentration profile inside an optical sample cell, and by measuring the time-dependent absorption spectrum in an initially solvent-filled part of the sample volume, we obtain the diffusion coefficients and UV/vis spectra of the species present in the sample solution. From these data, we construct a two-dimensional spectrum with absorption wavelength on one axis and diffusion coefficient (or equivalently, size) on the other, in which the UV/vis spectrum of a mixture with different molecular sizes is separated into the spectra of the different species, sorted by size. We demonstrate this method on mixed solutions of fluorescent dyes, biomolecules, and the UV-absorbing components of coffee, caffeine, and chlorogenic acid, all with concentrations in the μM range.

NMR methods for the analysis of mixtures

NMR spectroscopy is a powerful approach for the analysis of mixtures. Its usefulness arises in large part from the vast landscape of methods, and corresponding pulse sequences, that have been and are being designed to tackle the specific properties of mixtures of small molecules. This feature article describes a selection of methods that aim to address the complexity, the low concentrations, and the changing nature that mixtures can display. These notably include pure-shift and diffusion NMR methods, hyperpolarisation methods, and fast 2D NMR methods such as ultrafast 2D NMR and non-uniform sampling. Examples or applications are also described, in fields such as reaction monitoring and metabolomics, to illustrate the relevance and limitations of different methods.

Mechanistic analysis by NMR spectroscopy: A users guide

A 'principles and practice' tutorial-style review of the application of solution-phase NMR in the analysis of the mechanisms of homogeneous organic and organometallic reactions and processes. This review of 345 references summarises why solution-phase NMR spectroscopy is uniquely effective in such studies, allowing non-destructive, quantitative analysis of a wide range of nuclei common to organic and organometallic reactions, providing exquisite structural detail, and using instrumentation that is routinely available in most chemistry research facilities. The review is in two parts. The first comprises an introduction to general techniques and equipment, and guidelines for their selection and application. Topics include practical aspects of the reaction itself, reaction monitoring techniques, NMR data acquisition and processing, analysis of temporal concentration data, NMR titrations, DOSY, and the use of isotopes. The second part comprises a series of 15 Case Studies, each selected to illustrate specific techniques and approaches discussed in the first part, including in situ NMR (^1/2H, ^10/11B, ¹³C, ¹⁵N, ¹⁹F, ²⁹Si, ³¹P), kinetic and equilibrium isotope effects, isotope entrainment, isotope shifts, isotopes at natural abundance, scalar coupling, kinetic analysis (VTNA, RPKA, simulation, steady-state), stopped-flow NMR, flow NMR, rapid injection NMR, pure shift NMR, dynamic nuclear polarisation, ¹H/¹⁹F DOSY NMR, and in situ illumination NMR.

Natural products dereplication by diffusion ordered NMR spectroscopy (DOSY)

Diffusion-ordered NMR spectroscopy (DOSY) can be used to analyze mixtures of compounds since resonances deriving from different compounds are distinguished by their diffusion coefficients (D). Previously, DOSY has mostly been used for organometallic and polymer analysis, we have now applied DOSY to investigate diffusion coefficients of structurally diverse organic compounds such as natural products (NP). The experimental Ds derived from 55 diverse NPs has allowed us to establish a power law relationship between D and molecular weight (MW) and therefore predict MW from experimental D. We have shown that D is also affected by factors such as hydrogen bonding, molar density and molecular shape of the compound and we have generated new models that incorporate experimentally derived variables for these factors so that more accurate predictions of MW can be calculated from experimental D. The recognition that multiple physicochemical properties affect D has allowed us to generate a polynomial equation based on multiple linear regression analysis of eight calculated physicochemical properties from 63 compounds to accurately correlate predicted D with experimental D for any known organic compound. This equation has been used to calculate predicted D for 217 043 compounds present in a publicly available natural product database (DEREP-NP) and to dereplicate known NPs in a mixture based on matching of experimental D and structural features derived from NMR analysis with predicted D and calculated structural features in the database. These models have been validated by the dereplication of a mixture of two known sesquiterpenes obtained from Tasmannia xerophila and the identification of new alkaloids from the bryozoan Amathia lamourouxi. These new methodologies allow the MW of compounds in mixtures to be predicted without the need for MS analysis, the dereplication of known compounds and identification of new compounds based solely on parameters derived by DOSY NMR.

We report accurate DOSY NMR based molecular weight and diffusion coefficient prediction tools. These tools can be used to dereplicate known natural products from databases using structurally rich NMR data as a surrogate for mass spectrometric data.

Applicability of high-resolution NMR in combination with chemometrics for the compositional analysis and quality control of spices and plant-derived condiments

Over the last years, the consumption of spices and plant-derived condiments has increased considerably, owing to new culinary trends. Unfortunately, the current marketing channels make them highly vulnerable to adulteration and food fraud. High-resolution nuclear magnetic resonance (NMR) is a powerful tool for the compositional study of spices and plant-derived condiments. It allows the chemical characterization of a wide range of polar and non-polar metabolites, and provides unique structural information not available by other techniques. The chemometric-based analysis of NMR 'fingerprints' has been used to discriminate samples according to species and geographical origin and to detect adulterations, among other applications. The comprehensive identification and quantification of marker compounds can be achieved even in complex mixtures, demonstrating a great potential for high-throughtput quality control applications. © 2020 Society of Chemical Industry.

Matrix-assisted DOSY

The analysis of mixtures by NMR spectroscopy is challenging. Diffusion-ordered NMR spectroscopy enables a pseudo-separation of species based on differences in their translational diffusion coefficients. Under the right circumstances, this is a powerful technique; however, when molecules diffuse at similar rates separation in the diffusion dimension can be poor. In addition, spectral overlap also limits resolution and can make interpretation challenging. Matrix-assisted diffusion NMR seeks to improve resolution in the diffusion dimension by utilising the differential interaction of components in the mixture with an additive to the solvent. Tuning these matrix-analyte interactions allows the diffusion resolution to be optimised. This review presents the background to matrix-assisted diffusion experiments, surveys the wide range of matrices employed, including chromatographic stationary phases, surfactants and polymers, and demonstrates the current state of the art.

Automatised pharmacophoric deconvolution of plant extracts - application to Cinchona bark crude extract

We present a development of the "Plasmodesma" dereplication method [Margueritte et al., Magn. Reson. Chem., 2018, 56, 469]. This method is based on the automatic acquisition of a standard set of NMR experiments from a medium sized set of samples differing by their bioactivity. From this raw data, an analysis pipeline is run and the data is analysed by leveraging machine learning approaches in order to extract the spectral fingerprints of the active compounds. The optimal conditions for the analysis are determined and tested on two different systems, a synthetic sample where a single active molecule is to be isolated and characterized, and a complex bioactive matrix with synergetic interactions between the components. The method allows the identification of the active compounds and performs a pharmacophoric deconvolution. The program is freely available on the Internet, with an interactive visualisation of the statistical analysis, at https://plasmodesma.igbmc.science.

A pure shift and spin echo based approach for high-resolution diffusion-ordered NMR spectroscopy

Diffusion-ordered NMR spectroscopy (DOSY) can be used for separating mixture components according to their individual diffusion behaviors, thus offering a powerful tool for the analysis of compound mixtures. However, conventional DOSY experiments generally encounter the problem of limited resolution in the spectral domain, particularly for applications to complex mixtures that contains crowed resonances in 1D NMR. In addition, chemical exchange effects, bringing about spurious component signals, pose another limitation for interpreting DOSY measurements. Here, a general DOSY method is proposed based on pure shift extraction and spin echo evolution to obtain high-resolution 2D DOSY spectra, along with the suppression on effects of chemical exchange and J coupling. Both theoretical analyses and experimental results suggest that the proposed method is useful for high-resolution DOSY measurements on complex mixtures that contains crowded or even overlapped NMR resonances and exchanging spin systems.