title: Static energy analysis of MHC class I and class II peptide-binding affinity.
abstract: Antigenic peptide is presented to a T-cell receptor (TCR) through the formation of a stable complex with a major histocompatibility complex (MHC) molecule. Various predictive algorithms have been developed to estimate a peptide's capacity to form a stable complex with a given MHC class II allele, a technique integral to the strategy of vaccine design. These have previously incorporated such computational techniques as quantitative matrices and neural networks. A novel predictive technique is described, which uses molecular modeling of predetermined crystal structures to estimate the stability of an MHC class II-peptide complex. The structures are remodeled, energy minimized, and annealed before the energetic interaction is calculated.
authors.affiliation: The Jenner Institute, University of Oxford, Berkshire, UK.
authors.forename: Matthew N
authors.initials: MN
authors.lastname: Davies
authors.forename: Darren R
authors.initials: DR
authors.lastname: Flower
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D015395:Histocompatibility Antigens Class I / Q000737:chemistry* / Q000378:metabolism*; D000949:Histocompatibility Antigens Class II / Q000737:chemistry* / Q000378:metabolism*; D006801:Humans; D007125:Immunogenetics; D008285:Major Histocompatibility Complex; D010455:Peptides / Q000737:chemistry / Q000276:immunology / Q000378:metabolism; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D012984:Software; D013816:Thermodynamics
chemical_list: D015395:Histocompatibility Antigens Class I; D000949:Histocompatibility Antigens Class II; D010455:Peptides