title: Towards in silico design of epitope-based vaccines.
abstract: BACKGROUND
  Epitope-based vaccines (EVs) make use of immunogenic peptides (epitopes) to trigger an immune response. Due to their manifold advantages, EVs have recently been attracting growing interest. The success of an EV is determined by the choice of epitopes used as a basis. However, the experimental discovery of candidate epitopes is expensive in terms of time and money. Furthermore, for the final choice of epitopes various immunological requirements have to be considered.
  
  
  METHODS
  Numerous in silico approaches exist that can guide the design of EVs. In particular, computational methods for MHC binding prediction have already become standard tools in immunology. Apart from binding prediction and prediction of antigen processing, methods for epitope design and selection have been suggested. We review these in silico approaches for epitope discovery and selection along with their strengths and weaknesses. Finally, we discuss some of the obvious problems in the design of EVs.
  
  
  CONCLUSIONS
  State-of-the-art in silico approaches to MHC binding prediction yield high accuracies. However, a more thorough understanding of the underlying biological processes and significant amounts of experimental data will be required for the validation and improvement of in silico approaches to the remaining aspects of EV design.
authors.affiliation: Eberhard Karls University, Center for Bioinformatics Tübingen, Division for Simulation of Biological Systems, 72076 Tübingen, Germany +49 7071 2970458 ; +49 7071 295152 ; oliver.kohlbacher@uni-tuebingen.de.
authors.forename: Nora C
authors.initials: NC
authors.lastname: Toussaint
authors.forename: Oliver
authors.initials: O
authors.lastname: Kohlbacher