Immunology on the Grid

The binding of peptide fragments from foreign proteins to MHC Class II cell surface molecules is a process that is central to vaccine design, tissue transfer, and the understanding of the immune system [1]. The variability of MHC molecules in the human population, and range of possible peptide fragments, means that the problem is experimentally difficult. We use molecular dynamics simulations to predict peptide binding affinity. The simulations are computationally demanding and produce large amounts of data. Hence, a Grid-based distributed computing approach is ideal. Immunology Background When an individual is infected with a virus or bacterium, an immune response is provoked that recognizes and eliminates the infectious agent [1]. A critical step in the cellular response of the immune system is the binding of short peptide fragments (from broken down foreign proteins) to MHC Class II protein molecules (Figure 1). This complex is then presented to helper T cell receptors for inspection at the cell surface. The key to peptide binding specificity lies in the highly polymorphic nature of the MHC binding groove. Identifying peptides that bind to MHC, and hence trigger a response, may help researchers produce a vaccine. Rheumatoid arthritis and multiple sclerosis are common diseases where MHC molecules play a role. Inappropriate immune response can be equally harmful, for example in the treatment of leukaemia. Figure 1 MHC class II protein binding groove (red/blue ribbons) with bound peptide (grey ribbon).