Download Epitope prediction algorithms

Epitope prediction algorithms
Urmila Kulkarni-Kale
Bioinformatics Centre
University of Pune
Vaccine development
In Post-genomic era:
Reverse Vaccinology
Approach.
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October 2K5
Rappuoli R. (2000). Reverse
vaccinology.
Curr
Opin
Microbiol. 3:445-450.
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Genome Sequence
Proteomics
Technologies
In silico
analysis
DNA
microarrays
High throughput
Cloning and expression
In vitro and in vivo assays for
Vaccine candidate identification
Global
approach
to identify
new vaccine candidates
Octobergenomic
2K5
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Centre, UoP
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In Silico Analysis
Peptide
Multiepitope
vaccines
VACCINOME
Candidate Epitope DB
Epitope prediction
Disease related protein DB
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© Bioinformatics
Centre, Database
UoP
Gene/Protein
Sequence
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What Are Epitopes?
Antigenic determinants or Epitopes are the
portions of the antigen molecules which are
responsible for specificity of the antigens in
antigen-antibody (Ag-Ab) reactions and
that combine with the antigen binding site
of Ab, to which they are complementary.
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Types of Epitopes
• 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
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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.
• The amino acids making the epitope are
usually charged and hydrophilic.
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Methods to identify epitopes
1. Immunochemical methods
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ELISA : Enzyme linked immunosorbent assay
Immunoflurorescence
Radioimmunoassay
2. X-ray crystallography: Ag-Ab complex is
crystallized and the structure is scanned for
contact residues between Ag and Ab. The contact
residues on the Ag are considered as the epitope.
3. Prediction methods: Based on the X-ray crystal
data available for Ag-Ab complexes, the
propensity of an amino acid to lie in an epitope is
calculated.
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Antigen-Antibody (Ag-Ab) complexes
• Non-obligatory heterocomplexes that are made
and broken according to the environment
• Involve proteins (Ag & Ab) that must also exist
independently
• Remarkable feature:
– high affinity and strict specificity of antibodies for their
antigens.
• Ab recognize the unique conformations and spatial
locations on the surface of Ag
• Epitopes & paratopes are relational entities
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Antigen-Antibody complex
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Ab-binding sites:
Sequential & Conformational Epitopes!
Paratope
Sequential Conformational
Ab-binding sites
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B cell epitope prediction algorithms :
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Hopp and Woods –1981
Welling et al –1985
Parker & Hodges - 1986
Kolaskar & Tongaonkar – 1990
Kolaskar & Urmila Kulkarni - 1999
T cell epitope prediction algorithms :
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Margalit, Spouge et al - 1987
Rothbard & Taylor – 1988
Stille et al –1987
Tepitope -1999
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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
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Welling’s method
• Based on the % of each aa present in
known epitopes compared with the % of
aa in the avg. 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 aa with relatively high
antigenicity are extended to 11-13 aa
depending on the antigenicity values of
neighboring residues.
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Parker & Hodges method
• Utilizes 3 parameters :
– Hydrophilicity : HPLC
– Accessibility : Janin’s scale
– Flexibility : Karplus & Schultz
• 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
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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.
• Antigen: EMBOSS
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CEP Server
• Predicts the conformational epitopes from
X-ray crystals of Ag-Ab complexes.
• uses percent accessible surface area and
distance as criteria
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An algorithm to map sequential and conformational
epitopes of protein antigens of known structure
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CE: Beyond validation
• High accuracy:
– Limited data set to evaluate the algorithm
– Non-availability of true negative data sets
• Prediction of false positives?
– Are they really false positives?
• Limitation:
Different Abs
(HyHEL10 & D1.3)
have over-lapping
binding sites
– Limited by the availability of 3D structure data of
antigens
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CE: Features
• The first algorithm for the prediction of
conformational epitopes or antibody
binding sites of protein antigens
• Maps both: sequential & conformational
epitopes
• Prerequisite: 3D structure of an antigen
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CEP: Conformational Epitope Prediction Server
http://bioinfo.ernet.in/cep.htm
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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.
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• Case study: Design & development of
peptide vaccine against Japanese
encephalitis virus
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We Have Chosen JE Virus,
Because
 JE virus is endemic in South-east Asia
including India.
 JE virus causes encephalitis in children
between 5-15 years of age with fatality rates
between 21-44%.
 Man is a "DEAD END" host.
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We Have Chosen JE Virus,
Because
• Killed virus vaccine purified from mouse brain
is used presently which requires storage at
specific temperatures and hence not cost
effective in tropical countries.
• Protective prophylactic immunity is induced
only after administration of 2-3 doses.
• Cost
of
vaccination,
transportation is high.
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storage
and
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Predicted structure of JEVS
Mutations: JEVN/JEVS
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CE of JEVN Egp
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Species and Strain specific properties:
TBEV/ JEVN/JEVS
• Loop1 in TBEV:
• Loop1 in JEVN:
• Loop1 in JEVS:
LA EEH QGGT
HN EKR ADSS
HN KKR ADSS
Antibodies recognising TBEV and JEVN would require
exactly opposite pattern of charges in their CDR regions.
Further, modification in CDR is required to recognise
strain-specific region of JEVS.
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Multiple alignment of Predicted TH-cell epitope in the JE_Egp
with corresponding epitopes in Egps of other Flaviviruses
426
457
JE
DFGSIGGVFNSIGKAVHQVFGGAFRTLFGGMS
MVE DFGSVGGVFNSIGKAVHQVFGGAFRTLFGGMS
WNE DFGSVGGVFTSVGKAIHQVFGGAFRSLFGGMS
KUN DFGSVGGVFTSVGKAVHQVFGGAFRSLFGGMS
SLE DFGSIGGVFNSIGKAVHQVFGGAFRTLFGGMS
DEN2 DFGSLGGVFTSIGKALHQVFGAIYGAAFSGVS
YF
DFSSAGGFFTSVGKGIHTVFGSAFQGLFGGLN
TBE DFGSAGGFLSSIGKAVHTVLGGAFNSIFGGVG
COMM DF S GG
S GK H V G
F G
Multiple alignment of JE_Egp with Egps of other Flaviviruses in
the YSAQVGASQ region.
151
183
JE
SENHGNYSAQVGASQAAKFTITPNAPSITLKLG
MVE STSHGNYSTQIGANQAVRFTISPNAPAITAKMG
WNE VESHG----KIGATQAGRFSITPSAPSYTLKLG
KUN VESHGNYFTQTGAAQAGRFSITPAAPSYTLKLG
SLE STSHGNYSEQIGKNQAARFTISPQAPSFTANMG
DEN2 HAVGNDTG-----KHGKEIKITPQSSTTEAELT
YF
QENWN--------TDIKTLKFDALSGSQEVEFI
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TBE VAANETHS----GRKTASFTIS--SEKTILTMG
Peptide Modeling
Initial random conformation
Force field: Amber
Distance dependent dielectric constant 4rij
Geometry optimization: Steepest descents & Conjugate gradients
Molecular dynamics at 400 K for 1ns
Peptides are:
SENHGNYSAQVGASQ
NHGNYSAQVGASQ
YSAQVGASQ
YSAQVGASQAAKFT
NHGNYSAQVGASQAAKFT
SENHGNYSAQVGASQAAKFT
149
168
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Relevant Publications & Patent
• Urmila Kulkarni-Kale, Shriram Bhosale, G. Sunitha Manjari, Ashok
Kolaskar, (2004). VirGen: A comprehensive viral genome resource.
Nucleic Acids Research 32:289-292.
• Urmila Kulkarni-Kale & A. S. Kolaskar (2003). Prediction of 3D
structure of envelope glycoprotein of Sri Lanka strain of Japanese
encephalitis virus. In Yi-Ping Phoebe Chen (ed.), Conferences in
research and practice in information technology. 19:87-96.
• A. S. Kolaskar & Urmila Kulkarni-Kale (1999) Prediction of threedimensional structure and mapping of conformational antigenic
determinants of envelope glycoprotein of Japanese encephalitis virus.
Virology. 261:31-42.
Patent: Chimeric T helper-B cell peptide as a vaccine for Flaviviruses.
Dr. M. M. Gore, Dr. S.S. Dewasthaly, Prof. A.S. Kolaskar, Urmila Kulkarni-Kale
Sangeeta Sawant WO 02/053182 A1
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Important references
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Hopp, Woods, 1981, Prediction of protein antigenic determinants from
amino acid sequences, PNAS U.S.A 78, 3824-3828
Parker, Hodges et al, 1986, New hydrophilicity scale derived from high
performance liquid chromatography peptide retention data: Correlation
of predicted surface residues with antigenicity and X-ray derived
accessible sites, Biochemistry:25, 5425-32
Kolaskar, Tongaonkar, 1990, A semi empirical method for prediction of
antigenic determinants on protein antigens, FEBS 276, 172-174
Men‚ndez-Arias, L. & Rodriguez, R. (1990), A BASIC microcomputer
program forprediction of B and T cell epitopes in proteins, CABIOS, 6,
101-105
Peter S. Stern (1991), Predicting antigenic sites on proteins, TIBTECH, 9,
163-169
A.S. Kolaskar and Urmila Kulkarni-Kale, 1999 - Prediction of threedimensional structure and mapping of conformational epitopes of
envelope glycoprotein of Japanese encephalitis virus,Virology, 261, 31-42
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