Therapeutic antibodies have become increasingly important for the treatment of cancer and other diseases. The fastest process of delivering these formulations has been intravenous administration. However frequent administration requires subcutaneous delivery, which requires high concentration formulations. Developing these formulations has been a challenge due to stability and manufacturing issues. High concentration formulations also lead to very high viscosities of these solutions. One of the major reasons for these high viscosities has been related to the reversible self-association network that the antibodies can form. Studying high concentrations of these antibodies using atomistic methods is highly intractable due to the extremelylarge system sizes and long time scales. In this work, we study this problem of self-association using a coarse-grained model of the Genentech Immunoglobulin (IgG1) molecule. The parameters in the model are calculated using atomistic trajectory data. The model can be used to make predictions on the possible network topologies that can be generated based on experimental observations of the most important interactions in the system.

Coarse-grained modeling of antibody self-association

240th National Meeting (2010)

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