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2 Οκτ 2013 (πριν από 3 χρόνια και 6 μήνες)

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Bioinformatics in

Vaccine Design

Vaccination


Administration of a substance to a person with the purpose
of preventing a disease


Vaccination works by creating a type of immune response
that enables the memory cells to later respond to a similar
organism before it can cause disease


Vaccines traditionally composed of attenuated or killed
micro
-
organisms


More recently, parts of micro
-
organisms have been used
(subunit vaccines)


e.g. a single purified protein, or a mixture of such
proteins

Vaccines work by preparing the immune system for attack



Classical Approaches


Killed Vaccines (e.g. typhoid)


Live Attenuated Strains (e.g. BCG)


Subunit Vaccines (e.g. tetanus
)




Modern Approaches


Genetically modified attenuated strains


“Naked” and recombinant DNA vaccines


Subunit vaccines: a bioinformatics approach



Vaccine Design Strategies

Antigen Processing

MHC class I

Peptide Binding

Proteasomal

Cleavage

T cell Binding

Cathepsin

Cleavage

TAP Transporter


Binding

MHC class II

Peptide Binding



TAP is a member of the ATP
-
binding cassette transporter family.





It delivers cytosolic peptides into the endoplasmic reticulum (ER),
where they bind to nascent MHC class I molecules.




The TAP structure is formed of two proteins: TAP
-
1 and TAP
-
2,
which have one hydrophobic region and one ATP
-
binding region each.
They assemble into a heterodimer, which results in a four
-
domain
transporter.

Transporter associated with antigen processing (TAP)

Subunit Vaccine Characteristics

A protein that is a good subunit vaccine candidate…


readily visible to the host immune system


cleaved into peptide


bind to MHC molecules


transport to the cell surface


form stable complexes with T
-
cell receptors


and elicit a T
-
cell immune response


conserved between bacterial / viral strains

Software for Signal Prediction

PROGRAM

FUNCTION


METHOD

SignalP


Predicts the presence
and location of signal
peptide cleavage sites

Neural network /

Hidden Markov
model

SPScan


Scans protein for the
presence of secretary
signal peptides

Weight Matrix

SigCleave

Reports protein signal
cleavage sites

Matrix

Predicting Inner Membrane Proteins


Proteins span cytoplasmic membranes with helical
sequences


Transmembrane helices are segments of about 20
predominantly hydrophobic amino acids


There are many accurate programs for predicting
transmembrane helices


e.g. TMpred


The first transmembrane segment is the
signal sequence


Proteins with more than one “helical
segment” will stay in the inner
membrane


These proteins will only be readily
accessible to the immune system in
Gram positive bacteria

TMpred plot:

Bovine rhodopsin

TMpred can rule out

inner membrane proteins

Predicting Proteasomal Cleavage


Relevant in Class I pathway only


~20% of all peptide bonds are cleaved



Average peptide length 6
-
8 amino acids



Not all peptide bonds are equally likely cleaved



Cleavage more likely after hydrophobic than after
hydrophilic amino acids


NetChop is one program for predicting cleavage points


It uses neural network methods


Peptide Binding to the MHC


Class I MHC
:


Binds peptides from the cytosol
or nuclear compartment


Most often from viruses


Some bacterial peptides
(e.g. from
Mycobacterium
tuberculosis
)


Complexes bind CD8 receptors
on “killer” T cells



Class II MHC
:


Binds peptides from
intracellular vesicles


The most important
pathway for most
bacterial peptides


Complexes bind CD4
receptors on “helper” T
cells


This stimulates
antibody production by
B cells

The MHC locus is
POLYGENIC
:

Each individual’s immune system has 8 different MHC class II
molecules.

The MHC locus is also highly
POLYMORPHIC
:

These 8 MHC class II molecules vary between members of a
given population.

DO

Predicting MHC Binding


Many programs predict binding from sequence patterns


Most use “matrix” type methods, assuming amino acid
binding pockets are independent



MHC Class I binding is easier to predict


Less interaction between binding pockets


More amino acid specificity



But the class II pathway is the more important for bacterial
infection


The

portions

of

the

antigen

molecules

which

are

responsible

for

specificity

of

the

antigens

in

antigen
-
antibody

(Ag
-
Ab)

reactions

Epitopes/ Antigenic determinants



Sequential / Continuous epitopes
:



recognized by Th cells



linear peptide fragments



amphipathic helical 9
-
12 mer



Conformational / Discontinuous epitopes
:



recognized by both Th & B cells



non
-
linear discrete amino acid sequences, come together due to
folding



exposed 15
-
22 mer

Types of Epitopes

Properties of Epitopes


They occur on the surface of the protein and are more
flexible than the rest of the protein



They have high degree of exposure to the solvent



They have beta
-
turns in the secondary structure



The amino acids making the epitope are usually charged
and hydrophilic

B cell:


Hopp and Woods

1981


Welling et al

1985


Parker & Hodges
-

1986


Kolaskar & Tongaonkar


1990


Kolaskar & Urmila Kulkarni
-

1999


T cell:


Margalit, Spouge et al
-

1987


Rothbard & Taylor


1988


Stille et al

1987


Tepitope
-
1999

Epitope prediction algorithms

Hopp & Woods method


Pioneering work


Based on the fact that only the hydrophilic nature of amino
acids is essential for an sequence to be an antigenic
determinant


Local hydrophilicity values are assigned to each amino
acid by the method of repetitive averaging using a window
of six


Not very accurate



Welling’s method


Based

on

the

percentage

of

each

amino

acid

present

in

known

epitopes

compared

with

the

percentage

of

amino

acid

in

the

average

composition

of

a

protein
.


Assigns

an

antigenicity

value

for

each

amino

acid

from

the

relative

occurrence

of

the

amino

acid

in

an

antigenic

determinant

site
.



Regions

of

7

amino

acid

with

relatively

high

antigenicity

are

extended

to

11
-
13

amino

acid

depending

on

the

antigenicity

values

of

neighboring

residues
.




Utilizes 3 parameters :


Hydrophilicity


Accessibility


Flexibility


Hydrophilicity parameter was calculated using HPLC from
retention co
-
efficients of model synthetic peptides.


Surface profile was determined by summing the
parameters for each residue of a seven
-
residue segment
and assigning the sum to the fourth residue.


One of the most useful prediction algorithms

Parker & Hodges method

Kolaskar & Tongaonkar’s method


Semi
-
empirical method which uses physiological properties
of amino acid residues.



Frequencies of occurrence of amino acids in experimentally
known epitopes.



Data of 169 epitopes from 34 different proteins was
collected of which 156 which have less than 20 aa per
determinant were used.

T
-
cell epitope prediction algorithms


Considers

amphipathic

helix

segments,

tetramer

and

pentamer

motifs

(charged

residues

or

glycine)

followed

by

2
-
3

hydrophobic

residues

and

then

a

polar

residue
.



Sequence

motifs

of

immunodominant

secondary

structure

capable

of

binding

to

MHC

with

high

affinity
.



Virtual

matrices

which

are

used

for

predicting

MHC

polymorphism

and

anchor

residues
.


Ab
-
binding sites:

Sequential & Conformational Epitopes!

Sequential

Conformational


Ab
-
binding sites



Paratope

VAXIPRED: A software package for predicting subunit vaccine targets

Immune epitope tools