Transcript B cell epitopes and predictions - CBS

Pernille Haste Andersen,
Ph.d. student
Immunological
Bioinformatics
CBS, DTU
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
B cell epitopes and predictions
• What is a B-cell epitope?
• How can you predict B-cell epitopes?
• B-cell epitopes in rational vaccine
design.
– Case story: Using B-cell epitopes in
rational vaccine design against HIV.
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Outline
B-cell epitopes


Antibody Fab
fragment
Accessible structural
feature of a pathogen
molecule.
Antibodies are
developed to bind the
epitope specifically using
the complementary
determining regions
(CDRs).
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
What is a B-cell epitope?
Binding strength




Salt bridges
Hydrogen bonds
Hydrophobic interactions
Van der Waals forces
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
The binding interactions
 Many of the charged groups and hydrogen
bonding partners are present on highly flexible
amino acid side chains.
 Most crystal structures of epitopes and
antibodies in free and complexed forms have
shown conformational rearrangements upon
binding.
 “Induced fit” model of interactions.
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
B-cell epitopes are dynamic
B-cell epitope – structural feature of a molecule or
pathogen, accessible and recognizable by B-cells
Linear epitopes
One segment of the
amino acid chain
Discontinuous epitope
(with linear
determinant)
Discontinuous epitope
Several small segments brought
into proximity by the protein
fold
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
B-cell epitope classification
Antibody FAB fragment
complexed with Guinea
Fowl Lysozyme (1FBI).
Black: Light chain, Blue:
Heavy chain, Yellow:
Residues with atoms
distanced < 5Å from FAB
antibody fragments.
Guinea Fowl Lysozyme
KVFGRCELAAAMKRHGLDNYRGYSLGNWVCAAKFESNFNSQNRNTDGS
DYGVLNSRWWCNDGRTPGSRNLCNIPCSALQSSDITATANCAKKIVSDG
GMNAWVAWRKCKGTDVRVWIKGCRL
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Binding of a discontinuous epitope
• Linear epitopes:
– Chop sequence into small pieces and measure
binding to antibody
• Discontinuous epitopes:
– Measure binding of whole protein to antibody
• The best annotation method : X-ray crystal
structure of the antibody-epitope complex
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
B-cell epitope annotation
• Databases: AntiJen, IEDB, BciPep,
Los Alamos HIV database, Protein
Data Bank
• Large amount of data available for
linear epitopes
• Few data available for discontinuous
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
B-cell epitope data bases
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
B cell epitope prediction
 Protein hydrophobicity – hydrophilicity algorithms
Parker, Fauchere, Janin, Kyte and Doolittle, Manavalan
Sweet and Eisenberg, Goldman, Engelman and Steitz (GES), von
Heijne
 Protein flexibility prediction algorithm
Karplus and Schulz
 Protein secondary structure prediction algorithms
GOR II method (Garnier and Robson), Chou and Fasman, Pellequer
 Protein “antigenicity” prediction :
Hopp and Woods, Welling
TSQDLSVFPLASCCKDNIASTSVTLGCLVTG
YLPMSTTVTWDTGSLNKNVTTFPTTFHETY
GLHSIVSQVTASGKWAKQRFTCSVAHAES
TAINKTFSACALNFIPPTVKLFHSSCNPVGD
THTTIQLLCLISGYVPGDMEVIWLVDGQKA
TNIFPYTAPGTKEGNVTSTHSELNITQGEW
VSQKTYTCQVTYQGFTFKDEARKCSESDPR
GVTSYLSPPSPL
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Sequence-based methods for
prediction of linear epitopes
• The Parker
hydrophilicity scale
• Derived from
experimental data
D
E
N
S
Q
G
K
T
R
P
H
C
A
Y
V
M
I
F
L
W
2.46
1.86
1.64
1.50
1.37
1.28
1.26
1.15
0.87
0.30
0.30
0.11
0.03
-0.78
-1.27
-1.41
-2.45
-2.78
-2.87
-3.00
Hydrophilicity
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Propensity scales: The principle
….LISTFVDEKRPGSDIVEDLILKDENKTTVI….
(-2.78 + -1.27 + 2.46 +1.86 + 1.26 + 0.87 +
0.3)/7 = 0.39
Prediction scores:
0.38 0.1 0.6 0.9 1.0 1.2 2.6 1.0 0.9 0.5 -0.5
Epitope
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Propensity scales: The principle
• A Receiver
Operator Curve
(ROC) is useful
for finding a
good threshold
and rank methods
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Evaluation of performance
• Pellequer found that 50% of the epitopes
in a data set of 11 proteins were located in
turns
•Turn propensity
scales for each
position in the turn
were used for
epitope prediction.
Pellequer et al.,
Immunology letters, 1993
1
4
2
3
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Turn prediction and B-cell epitopes
• Extensive evaluation of propensity
scales for epitope prediction
• Conclusion:
– Basically all the classical scales perform
close to random!
– Other methods must be used for epitope
prediction
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Blythe and Flower 2005
• Parker hydrophilicity scale
• Hidden Markow model
• Markow model based on linear epitopes
extracted from the AntiJen database
• Combination of the Parker prediction
scores and Markow model leads to
prediction score
• Tested on the Pellequer dataset and
epitopes in the HIV Los Alamos database
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
BepiPred: CBS in-house tool
A
Pos 1
7.28
Pos 2
9.39
C
D
………… G
S T V W
Pos 3 0.3
Pos 4 5.2
Pos 5 7.9
….LISTFVDEKRPGSDIVEDLILKDENKTTVI….
2.46+1.86+1.26+0.87+0.3 = 6.75 Prediction value
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Hidden Markow Model
Evaluation
on HIV Los
Alamos data
set
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
ROC evaluation
• Pellequer data set:
– Levitt
– Parker
– BepiPred
AROC = 0.66
AROC = 0.65
AROC = 0.68
– Levitt
– Parker
– BepiPred
AROC = 0.57
AROC = 0.59
AROC = 0.60
• HIV Los Alamos data set
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
BepiPred performance
• BepiPred conclusion:
– On both of the evaluation data sets,
Bepipred was shown to perform better
– Still the AROC value is low compared to
T-cell epitope prediction tools!
– Bepipred is available as a webserver:
www.cbs.dtu.dk/services/BepiPred
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
BepiPred
•
•
•
•
•
Pro
easily predicted
computationally
easily identified
experimentally
immunodominant epitopes in
many cases
do not need 3D structural
information
easy to produce and check
binding activity experimentally
•
•
•
•
Con
only ~10% of epitopes can
be classified as “linear”
weakly immunogenic in
most cases
most epitope peptides do
not provide antigenneutralizing immunity
in many cases represent
hypervariable regions
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Prediction of linear
epitopes
 Linear methods for prediction of B cell epitopes have low
performances
 The problem is analogous to the problems of representing
the surface of the earth on a two-dimensional map
 Reduction of the dimensions leads to distortions of scales,
directions, distances
 The world of B-cell epitopes is 3 dimensional and therefore
more sophisticated methods must be developed
Regenmortel 1996,
Meth. of Enzym. 9.
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Sequence based prediction
methods
• Use of the three dimensional structure of
the pathogen protein
• Analyze the structure to find surface
exposed regions
• Additional use of information about
conformational changes, glycosylation and
trans-membrane helices
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
So what is more sophisticated?
Structural
determination
• X-ray
crystallography
• NMR spectroscopy
Both methods are
time consuming and
not easily done in a
larger scale
Structure prediction
• Homology modeling
• Fold recognition
Less time consuming,
but there is a
possibility of
incorrect
predictions, specially
in loop regions
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
How can we get information about
the three-dimensional structure?
• Homology/comparative modeling
>25% sequence identity (seq 2 seq alignment)
• Fold-recognition/threading
<25% sequence identity (Psi-blast search/ seq2str
alignment)
• Ab initio structure prediction
0% sequence identity
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Protein structure prediction methods
•Look at the surface of
your protein
•Analyse for turns and
loops
•Analyse for amino acid
composition
•Find exposed Bepipred
epitopes
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Annotation of protein surface
probe
Antibody Fab
fragment
Protrusion index
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Q: What can antibodies recognize in a
protein?
A: Everything accessible to a 10 Å probe on a protein surface
Novotny J. A static accessibility model of protein antigenicity.
Int Rev Immunol 1987 Jul;2(4):379-89
• CBS server for prediction of
discontinuous epitopes
– http://www.cbs.dtu.dk/services/DiscoTope/
• Uses protein structure as input
• Combines propensity scale values of
amino acids in discontinuous epitopes
with surface exposure
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Use the DiscoTope server
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Green: Predicted
epitopes
Black: Experimental
epitopes
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Malaria protein AMA1.
>PATHOGEN PROTEIN
KVFGRCELAAAMKRHGLDNYRG
YSLGNWVCAAKFESNF
Rational Vaccine
Design
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Rational vaccine design
• Protein target choice
• Structural analysis of antigen

Model



CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Rational B-cell epitope design
Known structure or homology model
Precise domain structure
Physical annotation (flexibility,
electrostatics, hydrophobicity)
Functional annotation (sequence
variations, active sites, binding sites,
glycosylation sites, etc.)
Known 3D structure
• Protein target choice
• Structural annotation
• Epitope prediction and ranking




Surface accessibility
Protrusion index
Conserved sequence
Glycosylation status
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Rational B-cell epitope
design
•
•
•
•
Protein target choice
Structural annotation
Epitope prediction and ranking
Optimal Epitope presentation




Fold minimization, or
Design of structural mimics
Choice of carrier (conjugates, DNA
plasmids, virus like particles)
Multiple chain protein engineering
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Rational B-cell epitope design
epitope
T-cell
epitope
Rational optimization of
epitope-VLP chimeric
proteins:



Design a library of possible
linkers (<10 aa)
Perform global energy
optimization in VLP (virus-like
particle) context
Rank according to estimated
energy strain
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Multi-epitope protein
design
B-cell
Using B-cell epitopes in the rational
vaccine design against HIV
The gp120-CD4 epitope
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Case story
Binding of CD4 receptor
Conformational changes in
gp120
Opens chemokinereceptor binding site
New highly conserved
epitopes
Kwong et al.(1998) Nature 393, 648-658
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
HIV gp120-CD4 epitope
SIV gp120 no ligands
Human gp120 complex with CD4
and 17b antibody
Chen et al. Nature 2005
Kwong et al. Nature 1998
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Conformational changes in gp120
Efforts to design a epitope fusion protein




Elicit broadly crossreactive neutralizing
antibodies in rhesus
macaques.
This conjugate is too
large(~400 aa) and
still contains a
number of irrelevant
loops
Fouts et al. (2000) Journal
ofVirology, 74, 11427-11436
Fouts et al. (2002) Proc Natl Acad
Sci U S A. 99, 11842-7.
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
HIV gp120-CD4 epitope
Further optimization of the epitope:


reduce to minimal
stable fold (iterative)
find alternative
scaffold to present
epitope (miniprotein
mimic)
Martin & Vita, Current Prot. An Pept.
Science, 1: 403-430.
Vita et al.(1999) PNAS 96:13091-6
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
HIV gp120-CD4 epitope
• Rational vaccines can be designed to induce strong
and epitope-specific B-cell responses
• Selection of protective B-cell epitopes involves
structural, functional and immunogenic analysis of
the pathogenic proteins
• When you can: Use protein structure for prediction
• Structural modeling tools are helpful in prediction
of epitopes, design of epitope mimics and optimal
epitope presentation
CENTER FOR BIOLOGICAL SEQUENCE ANALYSIS TECHNICAL UNIVERSITY OF DENMARK DTU
Conclusions