Abstract
A proteochemometrics approach was applied to a set of 2666 peptides binding to 12 HLA-DRB1 proteins. Sequences of both peptide and protein were described using three z-descriptors. Cross terms accounting for adjacent positions and for every second position in the peptides were included in the models, as well as cross terms for peptide/protein interactions. Models were derived based on combinations of different blocks of variables. These models had moderate goodness of fit, as expressed by r2, which ranged from 0.685 to 0.732; and good cross-validated predictive ability, as expressed by q2, which varied from 0.678 to 0.719. The external predictive ability was tested using a set of 356 HLA-DRB1 binders, which showed an r2(pred) in the range 0.364-0.530. Peptide and protein positions involved in the interactions were analyzed in terms of hydrophobicity, steric bulk and polarity.
Original language | English |
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Pages (from-to) | 236-243 |
Number of pages | 8 |
Journal | European Journal of Medicinal Chemistry |
Volume | 45 |
Issue number | 1 |
Early online date | 13 Oct 2009 |
DOIs | |
Publication status | Published - Jan 2010 |
Keywords
- amino acid sequence
- computational biology
- HLA-DR antigens
- HLA-DRB1 chains
- least-squares analysis
- ligands
- molecular models
- molecular sequence data
- peptides
- protein conformation
- proteomics
- quantitative structure-activity relationship
- substrate specificity