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Computer Modelling in Molecular BiologyEdited by Julia M. GoodfellowOVCH Verlagsgesellschaft mbH, 19957 Molecular Modelling and Simulationsof Major Histocompatibility ComplexClass I Protein-Peptide InteractionsChristopher .I Thorpe and David S. MossLaboratory of Molecular Biology, Department of Crystallography,Birkbeck College, Malet Street, London WClE 7HX, EnglandContents7.1 Introduction ...................................................... 1727.2 The Structure of the MHC Molecule.. ............................... 1787.3The Structure of the Peptide in the Groove ...........................1857.4Rationale Used for the Modelling and Simulation of MHC Class IMolecules ........................................................ 1887.5 General Principles of Modelling MHC Class I-Peptide Interactions ...... 1897.6 Modelling and Simulation of an Influenza Virus Peptide with theHuman MHC Class I Molecule HLA-Aw68.. ......................... 1937.7 Modelling of an Epstein Barr Virus Nuclear Antigen Peptide withHLA-B27 Sub-Qpe Molecules ....................................... 1987.8 Conclusions.. ..................................................... 210References ........................................................ 21 1
172 Christopher J Thorpe and David S. Moss7.1 IntroductionThe Major Histocompatibility Complex (MHC) is a gene cluster, which is to datethe most polymorphic section of the genome to have been encountered. The classI and class I1 molecules of the MHC perform a pivotal role in the cellular or T-cellmediated immune response. The function of any immune system is selfhon-selfrecognition to defeat invasion by pathogens. The immune systems of vertebrates aredivided into two branches, humoral and cellular. The humoral arm of the immunesystem involves antibody response to pathogens in the extracellular space and thecellular arm encompasses the response to intracellular pathogens by T-cells andMHC molecules. The function of the MHC molecules in the cellular immune systemis to present antigen in the form of a processed peptide to T-lymphocytes restrictedfor the combination of MHC molecule and peptide [l].The MHC was discovered in 1936 by Peter Gorer during early research into thephenomenon of tumor rejection in mice [2, 31. As a consequence of the nature ofits discovery MHC is somewhat anachronistically named by the term Histocompatibility,as it was considered to be the factor that determined tissue type compatibility.Tissue incompatibility is however merely an extreme case of selfhon-selfrecognition, and one for which the MHC was not naturally intended. However MHCevolution has produced a highly specific system that may precisely recognise an antigenwhen complexed to a specific MHC molecule. Thus if the donor is not of theexact tissue haplotype of the recipient, the T-cell receptors, whose specificity is solelyfor the MHC molecules of the host, will recognise the MHC molecules of the donoras non-self and start an immune response against any tissues bearing them. Thisphenomenon is termed allorecognition. Graft rejection is common due to twofeatures that make the cellular immune system highly efficient; the class I moleculesare highly ubiquitous in their tissue distribution, and are highly allelic within apopulation. Thus the chance of finding an exact haplotype match apart from siblingsis unlikely.Since structural data for the class I1 molecule has only recently been published[4], the focus of this review will be upon the class I molecule and its interaction withpeptide. Recent crystallographic data on the structure of the class I1 moleculedemonstrates that it has a high structural similarity to the class I molecule, butcrystals of a class I1 complex with a single antigenic peptide show that the class I1molecule has an entirely different mode of peptide chelation to that of class I (LarryStern, personal communication). The interaction between peptides and MHC classI molecules has been well characterised by X-ray crystallography [5-71, but the vastdiversity of MHC class I molecules and the universe of peptides of different lengthand sequence that may be bound by any one MHC class I allele [8] allows great scopefor modelling and simulations.
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Computer Modellingin Molecular Biol
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Professor Julia M. GoodfellowDepart
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ContentsColour Illustrations ......
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XContributorsBenoit RouxGroupe de R
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Colour IllustrationsXI11Figure 4-4.
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XVIColour IllustrationsFigure 7-18.
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2 Julia M. Goodfellow and Mark A. W
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Computer Modelling in Molecular Bio
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2 Modellinn Protein Structures 11su
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2.3.3 Available Modelling Programs2
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2 Modelling Protein Structures 35[8
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38 D. J Osmthorue and I? K. C Paul3
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4 Molecular Dynamics and Free Energ
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4 Molecular Dvnamics and Free Enera
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5 Modelling Nucleic Acids 105and it
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5 Modelling Nucleic Acids 107of the
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5 Modellinn Nucleic Acids 1135.7 Ch
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5 Modelling Nucleic Acids 115With i
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5 Modellinn Nucleic Acids 117Figure
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Page 144 and 145: 134 Benoft Roux6.1 IntroductionThe
Page 146 and 147: 136 Benoit Roux[18-201. The gramici
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Page 154 and 155: 144 Benoit RouxFigure 6-2. Solvated
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Page 162 and 163: 152 Benoit RouxOne advantage of thi
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Page 166 and 167: 156 Benoft Rouxwhere x and v are th
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Page 174 and 175: 164 Benoft RouxTable 6-3. Pre-expon
Page 176 and 177: 166 Benoft RouxThis chapter demonst
Page 178 and 179: 168 Benoft Rouxproximately one Kf c
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Page 224 and 225: 216 Oliver S. Smart8.1 Introduction
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222 Oliver S. Smart(8-2)and applyin
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224 Oliver S. SmartThe repulsion te
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226 Oliver S. Smart8.4 Applications
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228 Oliver S. Smartrigid-body penal
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230 Oliver S. Smart216 252 200 324
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232 Oliver S. SmartrbFigure 8-5. A
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234 Oliver S. Smartlink the eoc and
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236 Oliver S. Smarttermediates mark
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238 Oliver S. Smartmoving conformat
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240 Oliver S. Smart[39] Halgren, T.
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242 IndexGGramicidin A 134- NMR dat
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