Synthesis, structure and conformation of oligo- and polysaccharides

Carbohydrates are a complex group of biomolecules with a high structural diversity. Their almost omnipresent occurrence has generated a broad field of research in both biology and chemistry. This thesis focuses on three different aspects of carbohydrate chemistry, synthesis, structure elucidation and the conformational analysis of carbohydrates. The first paper describes the synthesis of a penta- and a tetrasaccharide related to the highly branched capsular polysaccharide from Streptococcus pneumoniae type 37. In the second paper, the structure of the O-antigenic repeating unit from the lipopolysaccharide of E. coli 396/C1 was determined along with indications of the structure of the biological repeating unit. In addition, its structural and immunological relationship with E. coli O126 is discussed. In the third paper, partially protected galactopyranosides were examined to clarify the origin of an intriguing 4JHO,H coupling, where a W-mediated coupling pathway was found to operate. In the fourth paper, the conformation of methyl a-cellobioside is studied with a combination of molecular dynamics simulations and NMR spectroscopy. In addition to the expected syn-conformation, detection and quantification of anti-ø and anti-ψ conformers was also possible.

Variance Reduction in Analytical Chemistry : New Numerical Methods in Chemometrics and Molecular Simulation

This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules. Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments. Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV. Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).