Modeling the adaptive immune system: predictions and simulations

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

The simplest way to predict the possible epitopes in a protein of known 3D structure is to use the knowledge of surface accessibility (Novotny et al., 1986; Thornton et al., 1986) . Two newer methods using protein structure and surface exposure for prediction of B-cell epitopes have been developed. The CEP method (Kulkarni-Kale et al., 2005) calculates the relative accessible surface area for each residue in the structure. Then it is determined which parts of the protein that are exposed enough to be antigenic determinants. Regions that are distant in the primary sequence, but close in three-dimensional space are considered as one epitope. The tool was tested on a dataset of 63 antigen-antibody complexes and the algorithm correctly identified 76% of the epitope residues. DiscoTope (Haste et al., 2006) uses a combination of amino acid statistics, spatial information and surface exposure. It is trained on a compiled dataset of discontinuous epitopes from 76 X-ray structures of antibody-antigen protein complexes. This method outperforms methods that predict linear epitopes. Recently a workshop was held on the subject of B-cell epitope predictions attended by a broad range of the current method developers. The workshop resulted in a published review containing conclusions on the present common ground, and suggestions for the future especially concerning coordination and evaluation (Greenbaum et al., 2007) .