The immune system normally does a good job of keeping us free from diseases, but sometimes it fails. One approach towards understanding why this happens is to produce advanced simulation models of the immune system and to understand the relationship between hosts and patogens in this manner. Depending on the complexity of these models and the input given, they can be used to simulate what happens when a host gets infected by a pathogen, thereby predicting the co-evolvement of pathogens and immune systems. One aim of the modeling is to identify parts of proteins known as epitopes which are recognized by the immune system, thereby inducing a protective response. This knowledge is very valuable in the development of better vaccines and provides very important insights into the nature of cancer, allergy and autoimmune diseases.
The Immunological Bioinformatics Group at CBS is developing new technologies for epitope discovery that can aid in the search for new vaccines and therapies for HIV, malaria, and tuberculosis, as well as for diseases such as influenza and pox, which may evolve to be a threat naturally or intentional through bioterrorism. The group has built a simulation model of the human immune system and has constructed a database with all human pathogens. Using this database and a database of the human genome the group is working on using the prediction methods to simulate the co-evolvement of pathogens and immune systems, and in particular to identify epitopes from the different arms of immune systems. In most of the projects the predicted epitopes are being validated through experimental collaborations with partners doing wet-lab research.
The group have developed methods for the three main types of epitopes: B cell epitopes which are used to recognize microorganisms outside cells; Helper T lymphocyte (HTL) epitopes which are used to activate cells that have taken up foreign substances; and cytotoxic T lymphocyte (CTL) epitopes, which are used to detect and kill infected cells. Current projects include:
Development of accurate methods for predicting peptide binding to MHC, Class I and Class II HLA molecules
- Prediction of conformational and linear B cell epitopes
- Optimization of plasmids containing multiple epitopes,
- Proteasomal cleavage site predictions and prediction of CTL response
- Epitope/pathogen database construction
- Prediction of pathogenecity
- Prediction of protein structure
Read more at the CBS website: www.cbs.dtu.dk