An alternative approach to solve the problem of identifying peptides that support folding of MHC-I molecules of so far unknown specificity is to use our recently developed panspecific predictor, NetMHCpan. The successful use of this predictor to initiate peptide-binding studies was recently Fig. 7 Specificity tree clustering of the SLA-1*0401 molecule compared to prevalent representatives of the 12 common HLA supertypes ). The distance between any two MHC molecules and the consensus tree is calculated as described in "Materials and methods". All branch points in the tree have bootstrap values of 100%. Sequence logos of the predicted binding specificity are shown for each molecule. In the logo, acidic amino acids [DE] are shown in red, basic amino acids [HKR] in blue, hydrophobic amino acids [ACFILMPVW] in black, and neutral amino acids [GNQSTY] in green. The axis of the LOGOs indicates in all case positions one through nine of the motif, and the y-axis the information content (see Materials and methods) demonstrated for HLA-A*3001 . Although originally developed to cover all HLA-A and HLA-B molecules, it has also been shown to extend to MHC-I molecules of other species (Hoof et al. 2009 ). Here, we demonstrate that the NetMHCpan predictor is capable of extracting MHC-I sequence information across species and correctly relate this to peptide binding even in the absence of any available data for the specific query MHC-I molecule, i.e., the SLA-1*0401 as well as the chimeric HPP (hα 1 pα 2 pα 3 ) and PHP (pα 1 hα 2 pα 3 ) molecules. It is not clear why binding of the PHP chimera was more efficiently predicted than binding of the HPP chimera. One could speculate that NetMHCpan has not captured the effect of the different positions of the pseudo-sequence equally well and not all positions and pockets (and by inference-not all chimeric molecules) are therefore predicted equally well.