Identification of promiscuous or multideterminant T cell epitopes is e
ssential for HIV vaccine development, however, current methods for T c
ell epitope identification are both cost intensive and labor intensive
, We have developed a computer-driven algorithm, named EpiMer, which s
earches protein amino acid sequences for putative MHC class I- and/or
class II-restricted T cell epitopes. This algorithm identifies peptide
s that contain multiple MHC-binding motifs from protein sequences, To
evaluate the predictive power of EpiMer, the amino acid sequences of t
he HIV-1 proteins nef, gp160, gag p55, and tat were searched for regio
ns of MHC-binding motif clustering, We assessed the algorithm's predic
tive power by comparing the EpiMer-predicted peptide epitopes to T cel
l epitopes that have been published in the literature, The EpiMer meth
od of T cell epitope identification was compared to the standard metho
d of synthesizing short, overlapping peptides and testing them for imm
unogenicity (overlapping peptide method), and to an alternate algorith
m that has been used to identify putative T cell epitopes from primary
structure (AMPHI). For the four HIV-1 proteins analyzed, the in vitro
testing of EpiMer peptides for immunogenicity would have required the
synthesis of fewer total peptides than either AMPHI or the overlappin
g peptide method, The EpiMer algorithm proved to be more efficient and
more sensitive per amino acid than both the overlapping peptide metho
d and AMPHI, The EpiMer predictions for these four HIV proteins are de
scribed, Since EpiMer-predicted peptides have the potential to bind to
multiple MHC alleles, they are strong candidates for inclusion in a s
ynthetic HIV vaccine.