HLA-A2 is the most frequent HLA molecule in Caucasians with HLA-A*0201 representing the most frequent allele; it was also the first human HLA allele for which peptide binding prediction was developed. The Bioinformatics and Molecular Analysis Section of the National Institutes of Health (BIMAS) and the University of Tübingen (Syfpeithi) provide the most popular prediction algorithms of peptide/MHC interaction on the World Wide Web. To test these predictions, HLA-A*0201-binding nine-amino acid peptides were searched by both algorithms in 19 structural CMV proteins. According to Syfpeithi, the top 2% of predicted peptides should contain the naturally presented epitopes in 80% of predictions (www.syfpeithi.de). Because of the high number of predicted peptides, the analysis was limited to 10 randomly chosen proteins. The top 2% of peptides predicted by both algorithms were synthesized corresponding to 261 peptides in total. PBMC from 10 HLA-A*0201-positive and CMV-seropositive healthy blood donors were tested by ex vivo stimulation with all 261 peptides using crossover peptide pools. IFN-gamma production in T cells measured by CFC was used as readout. However, only one peptide was found to be stimulating in one single donor. As a result of this work, we report a potential new T cell target protein, one previously unknown CD8-T cell-stimulating peptide, and an extensive list of CMV-derived potentially strong HLA-A*0201-binding peptides that are not recognized by T cells of HLA-A*0201-positive CMV-seropositive donors. We conclude that MHC/peptide binding predictions are helpful for locating epitopes in known target proteins but not necessarily for screening epitopes in proteins not known to be T cell targets.