Computational Prediction and Analysis of Protein-Carbohydrate and Protein-Protein Interactions

Licentiate thesis, 2010

The structure and energetics of protein-carbohydrate and protein-protein interactions are of great interest due to their importance in many biological phenomena. Two cases of protein-carbohydrate interactions and one case of protein-protein interactions were predicted and analyzed using existing computational methods. Computational methods are shown to provide valuable insights for problems which are difficult to approach with experimental methods. Addressing the absence of crystallographic data, molecular docking methods are used to study the interactions of the enzyme Arylsulfatase A (ASA) with its natural sulfoglycolipid substrates and the activator protein saposin B (Sap B). Some of the predicted interactions of ASA with its natural sulfoglycolipid substrates were verified through mutational studies. The preliminary results of ASA interaction with Sap B were analyzed with existing clinical data on mutations of ASA. These results have implications in designing experiments involving ASA, Sap B and its substrates. The second case concerns binding of norovirus VA387 with a variety of histo-blood group ABO active carbohydrate structures. Using an available crystal structure of the VA387 capsid protein with B-trisaccharide, detailed interactions for 11 carbohydrate structures were predicted using molecular dynamics and binding affinity scoring. The predicted interactions stand in good agreement with the existing mutational data on the binding of VA387 to carbohydrates. The results could be useful in structure-based drug design of adhesion inhibitors for noroviruses. In the scoring functions of current molecular docking methods, it is seen that entropic contributions are neglected. Methodological development for predicting entropic contributions in binding are planned as future studies.