MHC-epitope binding plays a key role in the cellular immune response. Accurate prediction of MHC-epitope binding affinity can greatly expedite epitope screening by reducing costs and experimental effort. In this paper, 13 T descriptors, which derived from 544 physicochemical properties
of the natural amino acids, were used to characterize 4 MHC class I alleles epitope peptide sequences, the optimal QSAR models were constructed by using stepwise regression combines with multiple linear regression (STR-MLR). For HLA-A*0201, HLA-A*0203, HLA-A*0206 and HLAA*1101
alleles, the leave one out cross validation values (Q2 train) were 0.581, 0.553, 0.525 and 0.588, the correlation coefficients (R2 train) of training datasets were 0.607, 0.582, 0.556 and 0.606, the correlation coefficients (R2 test) of test datasets were 0.533, 0.506, 0.501 and 0.502, respectively.
The results showed that all models can obtain good performance for prediction and explain the mechanism of interaction between MHC and epitope. The descriptors will be useful in structure characterization and activity prediction of peptide sequences.
No Supplementary Data
MHC class I allele;
Major Histocompatibility Complex (MHC);
amino acids descriptors;
hydrophobic, stereo and physicochemical properties;
quantitative structure-activity relationship (QSAR);
stepwise regression-multiple linear regression (STR-MLR)
Document Type: Research Article
Publication date: 2011-09-01
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Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.