Efficient discovery of immune response targets by cyclical refinement of QSAR models of peptide binding.
Peptides that induce and recall T-cell responses are called T-cell epitopes. T-cell epitopes may be useful in a subunit vaccine against malaria. Computer models that simulate peptide binding to MHC are useful for selecting candidate T-cell epitopes since they minimize the number of experiments required for their identification. We applied a combination of computational and immunological strategies to select candidate T-cell epitopes. A total of 86 experimental binding assays were performed in three rounds of identification of HLA-A11 binding peptides from the six preerythrocytic malaria antigens. Thirty-six peptides were experimentally confirmed as binders. We show that the cyclical refinement of the ANN models results in a significant improvement of the efficiency of identifying potential T-cell epitopes.
Brusic
V
V
BIC-KRDL, Kent Ridge Digital Labs, 21 Heng Mui Keng Terrace, Singapore 119613. vladimir@krdl.org.sg
Bucci
K
K
Schönbach
C
C
Petrovsky
N
N
Zeleznikow
J
J
Kazura
J W
JW
D000818:Animals; D000953:Antigens, Protozoan / Q000276:immunology*; D003198:Computer Simulation; D018604:Epitope Mapping; D018984:Epitopes, T-Lymphocyte / Q000276:immunology*; D015234:HLA-A Antigens / Q000276:immunology*; D059870:HLA-A11 Antigen; D006801:Humans; D016571:Neural Networks, Computer; D010455:Peptides / Q000138:chemical synthesis / Q000276:immunology*; D010963:Plasmodium falciparum / Q000276:immunology*; D011485:Protein Binding
D000953:Antigens, Protozoan; D018984:Epitopes, T-Lymphocyte; D015234:HLA-A Antigens; D059870:HLA-A11 Antigen; D010455:Peptides