Computational binding assays of antigenic peptides |
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Authors: | Vladimir Brusic and John Zeleznikow |
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Affiliation: | (1) Kent Ridge Digital Labs, 21 Heng Mui Keng Terrace, Singapore, 119613;(2) La Trobe University, Bundoora, Vic, Australia |
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Abstract: | Computer models can be combined with laboratory experiments for the efficient determination of (i) peptides that bind MHC molecules and (ii) T-cell epitopes. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures. This requires the definition of standards and experimental protocols for model application. We describe the requirements for validation and assessment of computer models. The utility of combining accurate predictions with a limited number of laboratory experiments is illustrated by practical examples. These include the identification of T-cell epitopes from IDDM-, melanoma- and malaria-related antigens by combining computational and conventional laboratory assays. The success rate in determining antigenic peptides, each in the context of a specific HLA molecule, ranged from 27 to 71%, while the natural prevalence of MHC-binding peptides is 0.1–5%. |
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Keywords: | antigenic peptides computer models HLA MHC prediction T-cell epitopes |
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