5) Prediction of class I T-cell epitopes: evidence of presence of immunological hotspots inside antigens.
Srinivasan KN, Zhang GL, Khan AM, August JT, Brusic V.
Bioinformatics. 2004 Aug 4;20 Suppl 1:I297-I302.
PUBMED PMID: 15262812
Out link: Full-text
Impact Factor Year 2009: 4.926
No. of citations: 30 (total): 14 (non-self) & 16 (self)
ABSTRACT:
MOTIVATION: Processing and presentation of major histocompatibility complex class I antigens to cytotoxic T-lymphocytes is crucial for immune surveillance against intracellular bacteria, parasites, viruses and tumors. Identification of antigenic regions on pathogen proteins will play a pivotal role in designer vaccine immunotherapy. We have developed a system that not only identifies high binding T-cell antigenic epitopes, but also class I T-cell antigenic clusters termed immunological hot spots.
METHODS: MULTIPRED, a computational system for promiscuous prediction of HLA class I binders, uses artificial neural networks (ANN) and hidden Markov models (HMM) as predictive engines. The models were rigorously trained, tested and validated using experimentally identified HLA class I T-cell epitopes from human melanoma related proteins and human papillomavirus proteins E6 and E7. We have developed a scoring scheme for identification of immunological hot spots for HLA class I molecules, which is the sum of the highest four predictions within a window of 30 amino acids.
RESULTS: Our predictions against experimental data from four melanoma-related proteins showed that MULTIPRED ANN and HMM models could predict T-cell epitopes with high accuracy. The analysis of proteins E6 and E7 showed that ANN models appear to be more accurate for prediction of HLA-A3 hot spots and HMM models for HLA-A2 predictions. For illustration of its utility we applied MULTIPRED for prediction of promiscuous T-cell epitopes in all four SARS coronavirus structural proteins. MULTIPRED predicted HLA-A2 and HLA-A3 hot spots in each of these proteins.
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25) Zhu S, Udaka K, Sidney J, Sette A, Aoki-Kinoshita KF, Mamitsuka H.
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