Major Histocompatibility Complex

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Major Histocompatibility Complex

• Kung-yen Chang
• System Biology, 2003

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Principles of Immune Response

• Highly specific recognition of foreign antigens
• Mechanisms for elimination of microbes bearing
  such antigens
• A vast universe of distinct antigenic specifies
• Immunologic memory
• Tolerance of self-antigens

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Distinct Cells in Immune System

• Lymphocytes (B cells, T cells)
• - Determining specificity of immunity
• Monocyte/macrophage, dendritic cells, natual
  killer cells and other members of myeloid cells
• - Antigen presentation
• - Mediation of immunologic functions
• Specialized epithelial and stromal cells
• - Providing anatomic environment

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T Lymphocytes

• Helper (CD4) and Cytotoxic (CD8) T cells
• Help B cells develop into antibody-producing
  cells (HTL)
• Directly killing of target cells (CTL)
• Enhance the capacity of monocytes and macrophage
• Secretion of cytokines

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Major Histocompatibility Complex (MHC)

• Transfer of information about proteins within a
  cell to the cell surface
• MHC I are expressed on the great majority of
  cells and recognized by CD8 T cells
• MHC II are expressed on B cells, macrophages,
  dendritic cells and recognized by CD4 T cells
• Responsible for graft rejection
• Found on chromosome 6 in human and 17 in mouse

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Antigen Presentation Pathway MHC I

• Intracellular antigens
• Viruses

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Antigen Presentation Pathway MHC II

• Extracellular antigens
• Bacteria and Parasites

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Antigen Presentation Pathways
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TCR/peptide-MHC Complex
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T Cell Activation
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One Receptors, Two Kinds of Signals
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X-ray Crystal Structures
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Peptides Binding to MHC Molecules

• MHC I molecules bind short peptides, usually
  between 8 and 10 residues.
• The typical length of a class I ligand comprises
  9 amino acids.
• Class II ligands consist of 12 to 25 amino acids.
• A core of nine amino acids is essential for
  peptide/MHC binding.

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MHC peptide prediction

• Understanding the basis of immunity
• Development of peptide vaccines
• Immunotherapeutics for cancer and autoimmune
  disease
• Several mathematical approaches for MHC peptide
  binding prediction

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Binding Motifs

• Hammer et al., 1993 Hammer, 1995 Rammensee et
  al., 1995 Sette et al., 1989
• Specify which residues at given positions within
  the peptide are necessary or favorable for
  binding to a specific MHC molecule.

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Quantitative Matrices (QM)

• Parker et al., 1994
• Dominant anchor residues
• - Leu or Met at P2, and Val or Leu at P9
• Auxiliary anchor residues
• Assumed the stability contributed by a given
  residue at a given position is independent of the
  sequence of the peptide

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QM Error Function

• Data set 154 peptides binding to HLA-A2
• For a peptide, GILGFVFTL
• ERR In(t1/2)
• In(G1 I2 L3 G4 F5 V6 F7 T8
  L9 Constant)
• t1/2 half-life of dissociation in minutes at
  37"C
• Construct coefficients table (20 aa x 9
  positions) that minimizing the sum of error
  functions
• Calculate theoretical dissociation rate

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QM Coefficients Table
aa Coeff Freq aa Coeff
Freq aa Coeff
Freq
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Neural Networks (NN)

• Gulukota et al., 1997
• 463 nonapeptides binding to HLA-A2.1 with IC50
• A feedforward architecture

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NN - Model
The output state of any neuron i, Xi, is computed
as
Wij is the weight of the connection from neuron j
to neuron i. g is the sigmoidal function, g(x)
1/(1 e-x). Desired (target) output of the net
for a peptide is
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NN Performance

• Training set 146 peptides
• Test set 317 peptides
• Border is defined as 500 nM

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NN Performance

• Sensitivity
• TP/(TPFN)
• Specificity
• TN/(TNFP)
• Positive Prediction Value
• TP/(TPFP)
• Negative Prediction Value
• TN/(TNFN)

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Support Vector Machines (SVM)

• Dönnes and Elofsson, 2002
• Input Vector
• - amino acid sequence,
• - binder/non-binder,
• Constructing the hyperplane with the maximum
  distance to the nearest data points of each class
  in the feature space.
• Linear, polynomial and radial basis kernel
  functions were tested for prediction

,
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SVM - Hyperplane

• Decision function can be written

• Maximize

subject to
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MHC Peptide DB - MHCPEP

• Brusic et al. 1998
• Comprising over 13000 peptide sequences known to
  bind MHC molecules
• Entries are compiled from published reports as
  well as from direct submissions of experimental
  data.
• Containing peptides that have been reported to
  bind to MHC in the absence of any functional data

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MHC Peptide DB - SYFPEITHI

• Rammensee et al., 1999
• Naming First MHC-eluted peptide that was
  directly sequenced (Falk et al. 1991).
• Restricted to published data
• Only contain sequences that are natural ligands
  to T-cell epitopes
• Comprising more than 4000 entries

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SVMHC - Performance

• Prediction for 6 MHC types using SYFPEITHI data
  for SVM training
• Prediction for 26 MHC types using MHCPEP data for
  SVM training

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MHC Peptide DB - SYFPEITHI

• 10 frequently occur in anchor positions
• 8 a significant number of ligands
• 6 rarely occurring residues
• 4 less frequent residues of the same set
• 1-4 preferred, according to the strength
• -1 to -3 unfavorable for binding

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Servers for peptide-MHC binding