Modeling the adaptive immune system: predictions and simulations

Lundegaard, Claus; Lund, Ole; Kesmir, Can; Brunak, Søren; Nielsen, Morten

Relatively few methods have been developed to predict the specificity of TAP. Daniel et al. (1998) have developed ANNs using peptide 9mers for which TAP affinity was determined experimentally. Surprisingly, they found that some MHC alleles have ligands with very low TAP affinities, e.g. HLA-A2. However, it has been shown that TAP ligands can be trimmed in ER before binding to MHC molecules (Fruci et al., 2001) , i.e. a TAP ligand might be an epitope precursor and thus does not need to be 9 amino acids long. HLA-A2 might easily have precursors of its optimal ligands, which are also good TAP binders. Peters et al. (2003) used an SMM to predict TAP affinity of peptides. This method has the advantage of not being bound to only 9mers but can also be used for longer peptides. The method assumes that only the first three positions in the N-terminal and the last position at the C-terminal influences the TAP binding. The method is very well evaluated and the accuracy is high. The significance of TAP binding in the epitope presentation pathway is much lower than the MHC binding (see later) and the AUC value when this method is used alone as an epitope predictor of 0.79 is thus significantly lower than most MHC-binding prediction methods. Two methods were published in 2004. Bhasin and Raghava (2004) published a method for which they do only compare to the method of Daniel et al. (1998) and it is not determined how it performs compared to the Peters' method. The method of Doytchinova et al. (2004) is evaluated by comparing the resulting method (matrix) with other matrices. From such a comparison it can only be concluded that this method is closer to Peters' model than to the model of Bhasin and Raghava (2004) but not how it actually performs. Recently a new TAP predictor, PredTAP, have been published . This method does not have an AUC value for the methods performance in epitope prediction making a direct comparison to other models impossible. With increasing numbers of TAP ligands available on the internet (e.g. Jen-Pep database, http://www.jenner.ac.uk) (Blythe et al., 2002) , it will likely soon be possible to obtain more accurate TAP predictions.