2 Structural analysis

2.1 Introduction

The structural analysis of oligo- and polysaccharides poses some unique problems since, unlike the amino acids in peptides or nucleosides in DNA, sugar residues can have different ring structures, be linked at several different positions and may form not only linear, but also branched and cyclic structures. Most bacterial polysaccharides are regular, i.e. composed of repeating units, and may contain branches. There are other carbohydrate polymers which are dendritic or irregular but they will not be considered here as their structure can not be uniquely defined but requires statistical treatments. The structural analysis of oligo- and polysaccharides by chemical methods ⁸ alone may be tedious and often requires large amounts of material. Modern analytical methods such as NMR-spectroscopy and mass spectrometry ^9-11 have made it possible to reduce both the amount of substance and the time required to perform analyses. The use of these new sensitive methods has also made it possible to identify components which are easily lost or transformed during chemical analysis. In particular the ability of NMR-spectroscopy to determine the anomeric configuration has led to revision of older structure proposals. Despite this, chemical analysis remains the preferred method for component and linkage analysis.

2.2 NMR-spectroscopy ^12,13

There are several advantages in using NMR-spectroscopy in structure analysis. Labile components, such as diaminosugars or O-acetyl groups, which may be destroyed or transformed during chemical manipulations can be detected. Ring size and anomeric configuration may be difficult to determine with other methods. In order to use NMR-spectroscopy for sequence determination it is, however, necessary to assign individual resonances which in itself may require several time-consuming NMR-experiments. Several computer programs have been developed to aid in structure determination using NMR-spectroscopy and to speed up sequence determination. There are two different strategies:

2.2.1 Database search

If a compound is already known and its spectrum has been recorded it may be identified by direct comparison with a reference spectrum. No chemical manipulations are required and hence only a minimum of substance is needed. This approach has been successfully used in the structure determination of glycoprotein ¹⁴ and xyloglycan ¹⁵ derived oligosaccharides based on ¹H-NMR data. The use of databases has one disadvantage - it requires a reference spectrum. The identification of new compounds is therefore difficult, although substructures may be recognised.

2.2.2 Spectrum simulation

If NMR spectra are calculated from the chemical shifts of the constituent sugars using some rules, the spectra of new structures can be approximated. ^16-19 The glycosylation of a monosaccharide causes changes in its NMR spectrum referred to as glycosylation shifts. Their size depends on the geometry of the glycosidic bond. Using glycosylation shifts for different linkages and the chemical shifts of the monosaccharides, the calculation of a spectrum for any sequence and substitution pattern is possible. Providing that only short distance interactions are present additivity of glycosylation shifts is obeyed. Notable exceptions are residues where vicinal substitution, e.g. branch points, causes steric interactions not present in the model disaccharides. This can be compensated to some extent by including corrections based on trisaccharide fragments. Disadvantages of this approach are that a large set of assigned di- and trisaccharide fragments is required to obtain glycosylation shifts and that the simulated spectra are less accurate than spectra in a database.

**Scheme 2.1:** Calculation of chemical shifts
1) Chemical shifts are taken from the monosaccharide

2) Glycosylation shifts are added

3) In the case of vicinal substitution corrections are added

Using results from component and linkage analysis all possible permutations of sequences and anomeric configurations are generated. The calculated spectra of all generated structures are compared with experimental data and ranked according to fit. If the spectrum simulation performs well there will be at least one calculated spectrum which shows good agreement with experiment allowing other structures to be rejected. A comparison between the simulated and experimental spectra gives not only the structure but also the assignments for all signals, something which is advantageous when several plausible structures are to be discriminated by additional NMR experiments.

2.3 Enhancement of the CASPER program (Paper I)

CASPER is a computer program which automates the generation of trial structures and the calculation of chemical shifts according to the above scheme. It has previously been successfully applied to linear ¹⁷ and branched ¹⁸ oligo- and polysaccharides. Structure determinations have required complete sets of experimental ¹³C-NMR chemical shifts, in addition to information on the component sugars and their linkages. The inclusion of coupling constants of the anomeric protons can be used to reduce the number of simulated structures. Some of the limitations of earlier versions have now been addressed:

The format of the database containing the chemical shifts of the monosaccharide residues, glycosylation shifts and branch point corrections has been changed to facilitate database maintenance and extension.
The possibility to simulate multiply branched structures has been added.
The use of incomplete sets of chemical shifts is now possible so that poorly resolved spectra may be used.

The enhanced program was tested on one oligo- and three polysaccharides of known structure.

2.3.1 Simulation using a reduced number of resonances

The complete ¹³C-NMR spectrum of the O-polysaccharide of the LPS from Shigella flexneri type 4a ¹⁹ was used as a starting point since the spectrum is well simulated by CASPER. Omission of resonances from the experimental spectrum were made at random before it was used as input for structure determination. Successive removals of signals diminishes the error of the fit for all the simulated structures making them increasingly difficult to discriminate. Although no rigorous treatment was attempted, the results suggest that a substantial number of signals may be omitted before it becomes uncertain which structure is correct.

2.3.2 Multiply branched polysaccharides

Two doubly branched polysaccharides were investigated; the O-polysaccharide of the LPS from an Aeromonas caviae strain ²⁰ and the capsular polysaccharide from Klebsiella K8,52,59. ²¹ In the A. caviae polysaccharide both branches are attached to the same residue in the backbone, in the Klebsiella CPS to different residues. Of the 30 signals expected in the spectrum of the Klebsiella CPS, only 28 were easily identified and therefore a reduced set of experimental chemical shifts was used. In both the above cases the correct structure was ranked highest but the fit was not as good as for the S. flexneri polysaccharide. The largest errors are confined to the residues around the branch points where deviations from additivity due to steric crowding are to be expected. Extending the database with more corrections for branching will help to reduce this problem.

2.3.3 An oligosaccharide of the high-mannose type ²²

Oligosaccharides from glycoproteins are generally highly branched and composed of only a few different sugars with similar substitution patterns. This could make it difficult to distinguish between the different structures. As the simulated spectum showed a good fit it was possible to identify the correct structure for an octasaccharide containing five α-mannose residues. Since the sensitivity of ¹³C-NMR spectroscopy is low and the spectra of the structures are similar a database approach using ¹H-NMR is to be preferred for this type of structures. It does, however, demonstrate that extensive branching, per se, is not an obstacle.

2.4 The structure of the Klebsiella K52 CPS (Paper II)

A partial structure of the capsular polysaccharide of Klebsiella K52 had previously been determined by methylation analysis and partial acid hydrolysis ²³ but the anomeric configurations of the residues remained unknown.

**Fig 2.1** Structure of *Klebsiella* K52 CPS
→4)-αLRha-(1→3)-βDGal-(1→2)-αLRha-(1→4)-βDGlcA-(1→3)-αDGal(1→ 2 ↑ 1 αDGal

Using the ¹J_CH values of the anomeric carbons it would be easy to distinguish between those that have an equatorial (α, ¹J_CH≈170 Hz) and those with an axial (β, ¹J_CH≈160 Hz) proton.²⁴ It is also possible to use ³J_HH between H1 and H2 which is larger in a β-gluco-linkage (≈8 Hz) than in an α-gluco-linkage (≈4 Hz). ²⁵ The difference between α and β is much smaller in the manno case (both < 2 Hz). To assign α or β configuration to the different residues it is necessary to have the assignment of the NMR resonances. The assignments are also required for sequence determination using inter-residue NOEs or long-range heteronuclear couplings (³J_COCH). Assignments can be obtained by traditional NMR methods, i.e. from ¹H,¹H-COSY and ¹³C,¹H-correlated spectroscopy. If some resonances are absent, as in this case, this is not easily accomplished. Three signals were not readily discernible in the ¹³C-NMR spectrum of the CPS probably because of low intensity or overlap of resonances. The remaining signals were used as input to CASPER together with the results of component and linkage analysis. The previously suggested sequence had the best fit, although the difference between the first two structures was too small to make an unambiguous selection of the correct structure. The highest ranked structure suggestions differed in sequence rather than in anomeric configuration. In order to verify the suggested structure (fig 2.1) HMBC and NOE experiments were performed, giving an independent confirmation of the connectivity between the residues. It was concluded that the original structure was correct and only had to be amended with the anomeric configurations.

2.5 Conclusions

The use of computer programs such as CASPER can speed up structure determination significantly. After the latest additions to the program it should be possible to simulate the spectrum of any oligo- or polysaccharide structure provided that the necessary glycosylation shifts are known. In cases where the experimental data are incomplete it is still possible to obtain meaningful results. The better dispersion of resonances in ¹³C-NMR spectra makes it more suitable for spectrum simulations than ¹H-NMR spectra where most resonances overlap even at very high field. The higher sensitivity of ¹H-NMR spectroscopy makes it ideal for the reporter group approach,²⁶ i.e. the use of structure specific signals, or database approaches. A weakness of CASPER is the database. The number of di- and trisaccharides investigated is not sufficient to cover all the structures of biological interest. The NMR spectra of many compounds, both oligo- and polysaccharides, have been published and a logical next step in the development of the program would be to allow for the inclusion of these and thereby increase both the accuracy and scope of the program.

The structure and conformation of saccharides determined by experiment and simulation