Influence of Model Resolution on Antibody Aggregation Simulations

Up to 40% of the world’s population suffer from allergies. A primary mediator for allergies is the aggregation of antigens and IgE antibodies bound to cell-surface receptors FcǫRI. Antibody/antigen aggregate formation causes stimulation of mast cells and basophils, initiating cell degranulation and resulting in the release of immune mediators which produce an allergic or anaphylactic response. Understanding of the shape and structure of aggregates can provide critical insights into allergic response. However, due to the large size and number of molecules involved in aggregation, traditional techniques such as MD and coarse grained energetic models are computationally infeasible. Alternative methods such as ODEs and rule-based models are able to simulate the process of aggregation, however, these methods exclude critical geometric details. In our previous work, we presented methods to geometrically model, simulate and analyze antibody aggregation inspired by rigid body robotic motion simulation. Our polygon-based models of antibody-receptor complexes and antigens capture the 3-D shape of molecular structures while reducing structural complexity. Due to our simulation techniques, the number of polygon interaction comparisons are directly impacted by geometric model complexity. This is similar to collision detection calls in robotic motion planning, a primitive operation that has major implications for run time. Recent advances in polygon reduction techniques allows us to reduce the complexity of the models involved in the simulation. However, reductions could translate into qualitative changes in the molecules being simulated. In this paper we analyze the impact of model resolution on our simulations of antibody aggregation. Our exploration is focused on two antigens, a trivalent man-made antigen and a common shrimp allergen.