TY  - THES
T1  - Computational immunology : analyses of viral escape, epitope binding and T cell receptor recognition
A1  - Rump,Kirsten
Y1  - 2011/08/10
N2  - It has been shown repeatedly that infectious diseases in humans have strong associations with the human leukocyte antigen system, but an understanding of the basis of these associations remains elusive. Adaptive immune responses involving CD4 and CD8 T lymphocytes are dependent on (1) the appropriate and effective processing of a peptide from a protein source, (2) the stable binding of the peptide to the HLA molecule and (3) the recognition of this complex by the T cell receptor. In this thesis, we present work helping to better define such host-virus dynamics, examining aspects relating to each of the described steps. We examined two large patient cohorts, the first infected with HIV-1 and the second with HCV. We identified viral escape mutations and thus potential immune epitopes. Also, we examined the possible effects of HLA genotypes on the development of drug resistance mutations (HIV-1) and the success of antiviral therapy (HCV). To better understand the stable binding of peptides to HLA molecules, we evaluated the performance of diverse HLA class I prediction methods on large datasets, showing that all leading methods are capable of good to excellent performance. Finally, we developed the first algorithms, based on the interactions found in actual experimental structures, which allow for the prediction of interactions between residues in the T cell receptor's CDR loops and residues in the HLA-peptide antigen. The algorithms had good performance under cross-validation.
KW  - Epitop
KW  - HIV
KW  - Hepatitis-C-Virus
KW  - T-Lymphozyten-Rezeptor
CY  - Saarbrücken
PB  - Universitäts- und Landesbibliothek
AD  - Postfach 151141, 66041 Saarbrücken
UR  - http://scidok.sulb.uni-saarland.de/volltexte/2011/4233
ER  -