Unravelling structural information from complex mixtures utilizing correlation spectroscopy applied to HSQC spectra

Analysis of Heparin Samples by Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy in the Solid State

Heparin is a polydisperse, heterogeneous polysaccharide of the glycosaminoglycan (GAG) class that has found widespread clinical use as a potent anticoagulant and is classified as an essential medicine by the World Health Organization. The importance of rigorous monitoring and quality control of pharmaceutical heparin was highlighted in 2008, when the existing regulatory procedures failed to identify a life-threatening adulteration of pharmaceutical heparin with oversulfated chondroitin sulfate (OSCS). The subsequent contamination crisis resulted in the exploration of alternative approaches for which the use of multidimensional nuclear magnetic resonance (NMR) spectroscopy techniques and multivariate analysis emerged as the gold standard. This procedure is, however, technically demanding and requires access to expensive equipment. An alternative approach, utilizing attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) combined with multivariate analysis, has been developed. The method described enables the differentiation of diverse GAG samples, the classification of samples of distinct species provenance, and the detection of both established heparin contaminants and alien polysaccharides. This methodology has sensitivity comparable to that of NMR and can facilitate the rapid, cost-effective monitoring and analysis of pharmaceutical heparin. It is therefore suitable for future deployment throughout the supply chain.

Retrieving Spectra of Pure Components from the DOSY-NMR Experiment via a Comprehensive Approach Involving the 2D Asynchronous Spectrum, 2D Quotient Spectrum, and Genetic Algorithm Refinement

When diffusion coefficients of different components in a mixture are similar, NMR spectra of pure individual components are difficult to be obtained via a diffusion-ordered spectroscopy (DOSY) experiment. Two-dimensional correlation spectroscopy (2D-COS) is used to analyze the data from the DOSY experiment. Through the properties of the systematic absence of cross-peak (SACP) in the 2D asynchronous spectra, spectra of pure components can be obtained even if their diffusion coefficients are similar. However, fluctuations in peak-position and peak-width are often unavoidable in NMR spectra, which makes SACPs unrecognizable. To address the problem, a 2D quotient spectrum is used to identify the masked SACPs. However, undesirable interference peaks due to the fluctuations in peak-position and peak-width are still present when we extract a spectrum of a component by slicing the 2D asynchronous spectrum across the SACP. A genetic algorithm (GA) is used to select a suitable subset of spectra where the diversities of peak-position and peak-width are significantly reduced. Then, we used the selected spectra to construct a refined 2D asynchronous spectrum so that the spectra of pure components with significant attenuated interference can be obtained. The above approach has been proven to be effective on a model system and a real-world example, demonstrating that 2D-COS possesses a bright perspective in the analysis of the bilinear data from DOSY experiments.

Saturated tetrasaccharide profile of enoxaparin. An additional piece to the heparin biosynthesis puzzle

Enoxaparin, widely used antithrombotic drug, is a polydisperse glycosaminoglycan with highly microheterogeneous structure dictated by both parent heparin heterogeneity and depolymerization conditions. While the process-related modifications of internal and terminal sequences of enoxaparin have been extensively studied, very little is known about the authentic non-reducing ends (NRE). In the present study a multi-step isolation and thorough structural elucidation by NMR and LC/MS allowed to identify 16 saturated tetramers along with 23 unsaturated ones in the complex enoxaparin tetrasaccharide fraction. Altogether the elucidated structures represent a unique enoxaparin signature, whereas the composition of saturated tetramers provides a structural readout strictly related to the biosynthesis of parent heparin NRE. In particular, both glucuronic and iduronic acids were detected at the NRE of macromolecular heparin. The tetrasaccharides bearing glucosamine at the NRE are most likely associated with the heparanase hydrolytic action. High sulfation degree and 3-O-sulfation are characteristic for both types of NRE.

Specific Non-Reducing Ends in Heparins from Different Animal Origins: Building Blocks Analysis Using Reductive Amination Tagging by Sulfanilic Acid

Heparins are linear sulfated polysaccharides widely used as anticoagulant drugs. Their nonreducing-end (NRE) has been little investigated due to challenges in their characterization, but is known to be partly generated by enzymatic cleavage with heparanases, resulting in N-sulfated glucosamines at the NRE. Uronic NRE (specifically glucuronic acids) have been isolated from porcine heparin, with GlcA-GlcNS,3S,6S identified as a porcine-specific NRE marker. To further characterize NRE in heparinoids, a building block analysis involving exhaustive heparinase digestion and subsequent reductive amination with sulfanilic acid was performed. This study describes a new method for identifying heparin classical building blocks and novel NRE building blocks using strong anion exchange chromatography on AS11 columns for the assay, and ion-pair liquid chromatography-mass spectrometry for building block identification. Porcine, ovine, and bovine intestine heparins were analyzed. Generally, NRE on these three heparins are highly sulfated moieties, particularly with 3-O sulfates, and the observed composition of the NRE is highly dependent on heparin origin. At the highest level of specificity, the isolated marker was only detected in porcine heparin. However, the proportion of glucosamines in the NRE and the proportion of glucuronic/iduronic configurations in the NRE uronic moieties greatly varied between heparin types.

Multivariate analysis applied to complex biological medicines

A biological medicine (or biologicals) is a term for a medicinal compound that is derived from a living organism. By their very nature, they are complex and often heterogeneous in structure, composition and biological activity. Some of the oldest pharmaceutical products are biologicals, for example insulin and heparin. The former is now produced recombinantly, with technology being at a point where this can be considered a defined chemical entity. This is not the case for the latter, however. Heparin is a heterogeneous polysaccharide that is extracted from the intestinal mucosa of animals, primarily porcine, although there is also a significant market for non-porcine heparin due to social and economical reasons. In 2008 heparin was adulterated with another sulfated polysaccharide. Unfortunately this event was disastrous and resulted in a global public health emergency. This was the impetuous to apply modern analytical techniques, principally NMR spectroscopy, and multivariate analyses to monitor heparin. Initially, traditional unsupervised multivariate analysis (principal component analysis (PCA)) was applied to the problem. This was able to distinguish animal heparins from each other, and could also separate adulterated heparin from what was considered bona fide heparin. Taught multivariate analysis functions by training the analysis to look for specific patterns within the dataset of interest. If this approach was to be applied to heparin, or any other biological medicine, it would have to be taught to find every possible alien signal. The opposite approach would be more efficient; defining the complex heterogeneous material by a library of bona fide spectra and then filtering test samples with these spectra to reveal alien features that are not consistent with the reference library. This is the basis of an approach termed spectral filtering, which has been applied to 1D and 2D-NMR spectra, and has been very successful in extracting the spectral features of adulterants in heparin, as well as being able to differentiate supposedly biosimilar products. In essence, the filtered spectrum is determined by subtracting the covariance matrix of the library spectra from the covariance matrix of the library spectra plus the test spectrum. These approaches are universal and could be applied to biological medicines such as vaccine polysaccharides and monoclonal antibodies.

SAX-HPLC and HSQC NMR Spectroscopy: Orthogonal Methods for Characterizing Heparin Batches Composition

Heparin is a complex mixture of heterogeneous sulfated polysaccharidic chains. Its physico-chemical characterization is based on the contribution of several methods, but advantages of the use of complementary techniques have not been fully investigated yet. Strong-Anion-Exchange HPLC after enzymatic digestion and quantitative bidimensional ¹H-¹³C NMR (HSQC) are the most used methods for the determination of heparin structure, providing the composition of its building blocks. The SAX-HPLC method is based on a complete enzymatic digestion of the sample with a mixture of heparinases I, II and III, followed by the separation of the resulting di- and oligo-saccharides by liquid chromatography. The NMR-HSQC analysis is performed on the intact sample and provides the percentage of mono- and di-saccharides by integration of diagnostic peaks. Since, for both methods, accuracy cannot be proved with the standard procedures, it is interesting to compare these techniques, highlighting their capabilities and drawbacks. In the present work, more than 30 batches of porcine mucosa heparin, from 8 manufacturers, have been analyzed with the two methods, and the corresponding results are discussed, based on similarities and differences of the outcomes. The critical comparison of both common and complementary information from the two methods can be used to identify which structural features are best evaluated by each method, and to verify from the concordance of the results the accuracy of the two methods, providing a powerful tool for the regular characterization of single, commercial preparations of Heparin.

Tackling the Peak Overlap Issue in NMR Metabolomics Studies: 1D Projected Correlation Traces from Statistical Correlation Analysis on Nontilted 2D 1H NMR J-Resolved Spectra

The identification of metabolites in complex biological matrices is a challenging task in 1D ¹H-NMR-based metabolomics studies. Statistical total correlation spectroscopy (STOCSY) has emerged for aiding the structural elucidation by revealing the peaks that present a high correlation to a driver peak of interest (which would likely belong to the same molecule). However, in these studies, the signals from metabolites are normally present as a mixture of overlapping resonances, limiting the performance of STOCSY. As an alternative to avoid the overlap issue, 2D ¹H homonuclear J-resolved (JRES) spectra were projected, in their usual tilted and symmetrized processed form, and STOCSY was applied on these 1D projections (p-JRES-STOCSY). Nonetheless, this approach suffers in cases where the signals are very close. In addition, STOCSY was applied to the whole JRES spectra (also tilted) to identify correlated multiplets, although the overlap issue in itself was not addressed directly and the subsequent search in databases is complicated in cases of higher order coupling. With these limitations in mind, in the present work, we propose a new methodology based on the application of STOCSY on a set of nontilted JRES spectra, detecting peaks that would overlap in 1D spectra of the same sample set. Correlation comparison analysis for peak overlap detection (COCOA-POD) is able to reconstruct projected 1D STOCSY traces that result in more suitable database queries, as all peaks are summed at their f2 resonances instead of the resonance corresponding to the multiplet center in the tilted JRES spectra. (The peak dispersion and resolution enhancement gained are not sacrificed by the projection.) Besides improving database queries with better peak lists obtained from the projections of the 2D STOCSY analysis, the overlap region is examined, and the multiplet itself is analyzed from the correlation trace at 45° to obtain a cleaner multiplet profile, free from contributions from uncorrelated neighboring peaks.

Recent innovations in the structural analysis of heparin

Heparin, the widely used anticoagulant drug, is unusual among major pharmaceutical agents being neither single chemical entity nor a defined mixture of compounds. Its composition, while conforming to approximate average disaccharide composition or sulfation levels, exhibits heterogeneity and variability depending on the source, as well as its geographical origin. Furthermore, individual polysaccharide chains, whose physico-chemical properties are extremely similar, cannot be separated with current state-of-the-art techniques, presenting a challenge to those interested in the quality control of heparin, in ensuring its provenance and safety, and those with an interest in investigating the relationships between its structure and biological activity. The review consists of two main sections: The first is the Introduction, comprising (i) The History, Occurrence and Use of Heparin and (ii) Approaches to Structure-Activity Relationships. The second section is Improved Techniques for Structural Analysis, comprising; (i) Separation and Identification, (ii) Spectroscopic Methods, (iii) Enzymatic Approaches and (iv) Other Physico-Chemical Approaches. The ~60 references cover recent technological advances in the study of heparin structural analysis, largely since 2010.

Identification of metabolites from 2D (1)H-(13)C HSQC NMR using peak correlation plots

BACKGROUND

Identification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies. NMR spectroscopy is an excellent technique for analysis of mixtures of organic compounds and gives a detailed chemical fingerprint of most individual components above the detection limit. For the identification of individual metabolites in metabolomics, correlation or covariance between peaks in (1)H NMR spectra has previously been successfully employed. Similar correlation of 2D (1)H-(13)C Heteronuclear Single Quantum Correlation spectra was recently applied to investigate the structure of heparine. In this paper, we demonstrate how a similar approach can be used to identify metabolites in human biofluids (post-prostatic palpation urine).

RESULTS

From 50 (1)H-(13)C Heteronuclear Single Quantum Correlation spectra, 23 correlation plots resembling pure metabolites were constructed. The identities of these metabolites were confirmed by comparing the correlation plots with reported NMR data, mostly from the Human Metabolome Database.

CONCLUSIONS

Correlation plots prepared by statistically correlating (1)H-(13)C Heteronuclear Single Quantum Correlation spectra from human biofluids provide unambiguous identification of metabolites. The correlation plots highlight cross-peaks belonging to each individual compound, not limited by long-range magnetization transfer as conventional NMR experiments.

Re-visiting the structure of heparin

The sulfated polysaccharide heparin has been used as a life-saving anticoagulant in clinics well before its detailed structure was known. This mini-review is a survey of the evolution in the discovery of the primary and secondary structure of heparin. Highlights in this history include elucidation and synthesis of the specific sequence that binds to antithrombin, the development of low-molecular-weight heparins currently used as antithrombotic drugs, and the most promising start of chemo-enzymatic synthesis. Special emphasis is given to peculiar conformational properties contributing to interaction with proteins that modulate different biological properties.

Structural features of glycol-split low-molecular-weight heparins and their heparin lyase generated fragments

Periodate oxidation followed by borohydride reduction converts the well-known antithrombotics heparin and low-molecular-weight heparins (LMWHs) into their "glycol-split" (gs) derivatives of the "reduced oxyheparin" (RO) type, some of which are currently being developed as potential anti-cancer and anti-inflammatory drugs. Whereas the structure of gs-heparins has been recently studied, details of the more complex and more bioavailable gs-LMWHs have not been yet reported. We obtained RO derivatives of the three most common LMWHs (tinzaparin, enoxaparin, and dalteparin) and studied their structures by two-dimensional nuclear magnetic resonance spectroscopy and ion-pair reversed-phase high-performance liquid chromatography coupled with electrospray ionization mass spectrometry. The liquid chromatography-mass spectrometry (LC-MS) analysis was extended to their heparinase-generated oligosaccharides. The combined NMR/LC-MS analysis of RO-LMWHs provided evidence for glycol-splitting-induced transformations mainly involving internal nonsulfated glucuronic and iduronic acid residues (including partial hydrolysis with formation of "remnants") and for the hydrolysis of the gs uronic acid residues when formed at the non-reducing ends (mainly, in RO-dalteparin). Evidence for minor modifications, such as ring contraction of some dalteparin internal aminosugar residues, was also obtained. Unexpectedly, the N-sulfated 1,6-anhydromannosamine residues at the enoxaparin reducing end were found to be susceptible to the periodate oxidation. In addition, in tinzaparin and enoxaparin, the borohydride reduction converts the hemiacetalic aminosugars at the reducing end to alditols. Typical LC-MS signatures of RO-derivatives of individual LMWH both before and after digestion with heparinases included oligosaccharides generated from the original antithrombin-binding and "linkage" regions.