Prediction of Glycerol-Effect on Antigen-Antibody Binding Affinity from Molecular Dynamics Simulations

Abstract

Many biological and biotechnological processes are controlled by protein-protein interactions in solution. In order to understand, predict and optimize such processes, it is valuable to understand how additives such as salts, sugars, polyols and denaturants affect protein-protein interactions. Currently, no methodology to foretell the effect of additives on protein-protein interactions has been established and frequently and extensive empirical screening to identify additives beneficial to the protein process is resorted to. In this work, we developed a methodology enabling the prediction of the additive-effect on the protein reaction equilibrium. The only prerequisite is that the atomic structure of the protein reactants and products are known. The methodology is based on the thermodynamic model for preferential interactions and makes use of molecular dynamics simulations to gauge additive-protein interactions. In order to validate our methodology, the change in binding affinity of the antibody fragment Y32S Fv D1.3 for lysozyme in the presence of varying glycerol concentrations is being calculated and the results will be compared with experimental data from literature. Finally, our methodology will be used to predict the glycerol effect on the binding affinity of wild type Fv D1.3 and various mutants.