Combining computer algorithms with experimental approaches permits the rapid and accurate identification of T cell epitopes from defined antigens

The identification of T cell epitopes from immunologically relevant antigen s remains a critical step in the development of vaccines and methods for mo nitoring of T cell responses. This review presents an overview of strategie s that employ computer algorithms for the selection of candidate peptides f ront defined proteins and subsequent verification of their in vivo relevanc e by experimental approaches. Several computer algorithms are currently being used for epitope prediction of various major histocompatibility complex WHO class I and II molecules, based either on the analysis of natural MHC ligands or on the binding prope rties of synthetic peptides. Moreover, the analysis of proteasomal digests of peptides and whole proteins has led to the development of algorithms for the prediction of proteasomal cleavages, In order to verify the generation of the predicted peptides during antigen processing in vivo as well as the ir immunogenic potential, several experimental approaches have been pursued in the recent past, Mass spectrometry-based bioanalytical approaches have been used specifically to detect predicted peptides among isolated natural ligands. Other strategies employ various methods for the stimulation of pri mary T cell responses against the predicted peptides and subsequent testing of the recognition pattern towards target cells that express the antigen. (C) 2001 Elsevier Science B.V. All rights reserved.