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To be able to make informed descicions regarding the research of new drug molecules (ligands), it is crucial to have access to information regarding the chemical interaction between the drug and its biological target (protein). Computer-based methods have a given role in drug research today and, by using methods such as molecular docking, it is possible to investigate the way in which ligands and proteins interact. Despite the acceleration in computer power experienced in the last decades many problems persist in modelling these complicated interactions. The main objective of this thesis was to investigate and improve molecular modelling methods aimed to estimate protein-ligand binding. In order to do so, we have utilised chemometric tools, e.g. design of experiments (DoE) and principal component analysis (PCA), in the field of molecular modelling. More specifically, molecular docking was investigated as a tool for reproduction of ligand poses in protein 3D structures and for virtual screening. Adjustable parameters in two docking software were varied using DoE and parameter settings were identified which lead to improved results. In an additional study, we explored the nature of ligand-binding cavities in proteins since they are important factors in protein-ligand interactions, especially in the prediction of the function of newly found proteins. We developed a strategy, comprising a new set of descriptors and PCA, to map proteins based on their cavity physicochemical properties. Finally, we applied our developed strategies to design a set of glycopeptides which were used to study autoimmune arthritis. A combination of docking and statistical molecular design, synthesis and biological evaluation led to new binders for two different class II MHC proteins and recognition by a panel of T-cell hybridomas. New and interesting SAR conclusions could be drawn and the results will serve as a basis for selection of peptides to include in in vivo studies.

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that leads to degradation of cartilage and bone mainly in peripheral joints. In collagen-induced arthritis (CIA), a mouse model for RA, activation of autoimmune CD4+ T cells depends on a molecular recognition system where T-cell receptors (TCRs) recognize a complex between the class II MHC Aq protein and CII259-273, a glycopeptide epitope from type II collagen (CII). Interestingly, vaccination with the Aq/CII259-273 complex can relieve symptoms and cause disease regression in mice. This thesis describes the use of modified glycopeptides to explore interactions important for binding to the Aq protein and recognition by autoimmune T-cell hybridomas obtained from mice with CIA. The CII259-273 glycopeptide was modified by replacement of backbone amides with different amide bond isosteres, as well as substitution of two residues that anchor the glycopeptide in prominent pockets in the Aq binding site. A three-dimensional structure of the Aq/glycopeptide complex was modeled to provide a structural basis for interpretation of the modified glycopeptide’s immunological activities. Overall, it was found that the amide bond isosteres affected Aq binding more than could be explained by the static model of the Aq/glycopeptide complex. Molecular dynamics (MD) simulations, however, revealed that the introduced amide bond isosteres substantially altered the hydrogen-bonding network formed between the N-terminal 259-265 backbone sequence of CII259-273 and Aq. These results indicated that the N-terminal hydrogen-bonding interactions follow a cooperative model, where the strength and presence of individual hydrogen bonds depended on the neighboring interactions. The two important anchor residues Ile260 and Phe263 were investigated using a designed library of CII259-273 based glycopeptides with substitutions by different (non-)natural amino acids at positions 260 and 263. Evaluation of binding to the Aq protein showed that there was scope for improvement in position 263 while Ile was preferred in position 260. The obtained SAR understanding provided a valuable basis for future development of modified glycopeptides with improved Aq binding. Furthermore, the modified glycopeptides elicited varying T-cell responses that generally could be correlated to their ability to bind to Aq. However, in several cases, there was a lack of correlation between Aq binding and T-cell recognition, which indicated that the interactions with the TCRs were determined by other factors, such as presentation of altered epitopes and changes in the kinetics of the TCR’s interaction with the Aq/glycopeptide complex. Several of the modified glycopeptides were also found to bind well to the human RA-associated DR4 protein and elicit strong responses with T-cell hybridomas obtained from transgenic mice expressing DR4 and the human CD4 co-receptor. This encourages future investigations of modified glycopeptides that can be used to further probe the MHC/glycopeptide/TCR recognition system and that also constitute potential therapeutic vaccines for treatment of RA. As a step towards this goal, three modified glycopeptides presented in this thesis have been identified as candidates for vaccination studies using the CIA mouse model.