In-silico: Screening and Modeling of CTL Binding Epitopes of Crimean Congo Hemorrhagic Fever Virus
Sitansu Kumar Verma
Crimean-Congo Hemorrhagic Fever (CCHF) is a zoonotic viral disease that is asymptomatic in infected livestock but a serious threat to humans. This study is aimed at conducting the modeling of putative peptides which are suggested for vaccine development that is meant for evaluating epidemiological, clinical and laboratory characteristics of the patients diagnosed with Crimean-Congo hemorrhagic fever. In the present study, more reliable prediction of Major Histocompatibility Complex (MHC) peptide binding is based on the accurate determination of T-cell epitopes and hence the successful design of peptide and protein based vaccines. The importance of existing computational tools was used for prediction of peptide binding to Major Histocompatibility Complex (MHC) Class-I and Major Histocompatibility Complex (MHC) Class-II. With the availability of large sequence databases and computer aided design of peptide based vaccine, screening among billions of possible immune active peptides to find those likely to provoke an immune response was done. These peptides were selected by using different algorithms as Artificial Neuronal Network (ANN) and Support Vector Machine (SVM) for the T-cell epitope prediction and further characterized on the basis of binding affinity of peptide to HLA-alleles which can be finally used for the potential vaccine candidate development. A vaccine with specificity for a target population i.e., peptide based vaccine, in which small peptides derived from target proteins are used to provoke an immune reaction. Two nonameric epitopes (LRFGMLAGL) and (LLGIKCSFV) which exhibit good binding with MHC molecules and low energy minimization values providing stability to the peptide-MHC complex are reported here. These predicted peptides dont have similarity with human proteome. These peptide could be used in designing a chimeric/subunit vaccine, however, these will further be tested by wet lab studies for a targeted vaccine design against Crimean-Congo hemorrhagic fever.
Received: May 27, 2011;
Accepted: July 06, 2011;
Published: May 21, 2012
Crimean-Congo Hemorrhagic Fever (CCHF) virus is the member of family Bunyaviridae
(genus Nairovirus). In 1940s this virus was first described when many
cases of severe hemorrhagic fever arose among agricultural workers in the Crimean
peninsula but this virus was firstly reported in the former Soviet Union in
1944 (Jain et al., 2011). After some years,
a virus with similar pathogenesis was isolated in 1956 from patient in Congo,
Africa and the virus was subsequently named as Crimean-Congo Hemorrhagic Fever
(CCHF) virus (Jain et al., 2011). Crimean-Congo
Hemorrhagic Fever (CCHF) has the most extensive geographic range of the medically
significant tick-borne viruses, occurring in parts of sub-Saharan Africa, Asia,
eastern Europe and the Middle East (Whitehouse, 2004).
The countries widely affected in these areas include: Arabian Peninsula, Iraq,
Pakistan and Xinjiang Province in northwest China (Ergonul,
2006). CCHF is a severe hemorrhagic fever in humans with a high fatality
rate up to 30% (Ergonul, 2006; Vatansever
et al., 2007). During the 21st century, recent outbreaks of CCHF
virus were also reported in Gujarat, India.
The geographic distribution of CCHF virus cases corresponds most closely with
the distribution of Hyalomma ticks, hosted on the migratory birds suggesting
their principle vector role (Vatansever et al., 2007;
Whitehouse, 2004). Some others species of Dermacentor
and Rhipicephalus genera have also been shown to be capable of transovarial
transmission. CCHFV is a member of large family of negative stranded RNA viruses
denoted by Bunyaviridae. The family consists of more than 300 viral species
and is subdivided into five genera: Orthobunyavirus, Hantavirus,
Phlebovirus, Tospovirus and finally Nairovirus (Nichol
et al., 2005). CCHFV has three segments of negative sense RNA viz.
S, M and L which minimally encode the virus nucleocapsid, glycoproteins and
polymerase proteins, respectively. M-RNA segment of CCHFV plays a major role
in the immune response. In addition, members of the genera Bunyavirus,
Phlebovirus and Tospovirus also encode a nonstructural glycoprotein
referred to as NSM (Honig et al., 2004;
Kinsella et al., 2004; Meissner
et al., 2006). But, the complete information about the M RNA fragment
is not available. The M gene is responsible for immunity and pathogenicity as
well as for vaccine development. The nucleotide sequences of the M RNA genome
segment of CCHFV strains isolated from Xinjiang province was determined to define
the molecular variability among CCHFV strains, in China. Examination of their
expected amino acid sequences with the respective sequences of the orientated
protein was also carried out (Meissner et al., 2006).
Epitope based vaccine provide a new strategy for the prophylactic and therapeutic
application of pathogen specific immunity (Zinkernagel and
Hengartner, 2004). This strategy requires the identification and selection
of promiscuous T-cell epitopes important for cytolytic and regulatory response
to pathogens that helps to the vaccine development (Esser
et al., 2003; Brusic and Agust, 2004; Pulendran
and Ahmed, 2006).
The progression of Congo Hemorrhagic Fever is very rapid with clinical features
as flu like symptoms appears during primary 3 days of infection. After one week
symptoms get resolved, 75% cases which have sign of hemorrhage, thrombosis of
vessels to extremities and leading to death within 5 to 7 days. No procurement
found for this viral infection. Researches for the development of effective
vaccine against CCHF virus require understanding of immune response. Viral immune
response is associated with MHC protein and T-lymphocytes. MHC is of two types:
MHC Class I and MHC Class II (Rammensee et al., 1999).
MHC initially recognizes the viral antigenic epitopes present on T-cells for
neutralization. MHC Class I present the antigenic epitopes to CD8+
T-cells and MHC Class II present to CD4+ T-cells for viral antigen
degradation (Adams and Koziol, 1995; Berman
et al., 2000). CD8 T-cells also known as cytotoxic T-cells (CTL),
maximum viral infections by initially recognizing and their subsequent killing
infected cells and secreting cytokines. CD4 T-cells known as helper cells that
play very important role in growth factor releasing and signaling for generation
and maintenance of CD8 T-cells (Zielkiewicz, 2005).
T-cells recognize the antigens only when they are associated with MHC surface
glycoproteins exposed on surface of all vertebrate cells. In this communication,
online bioinformatics tools were used and the targeted protein of CCHFV was
analyzed, to identify the putative T-cell epitopes for the formation of peptide
based vaccine. The vaccine of Congo virus is not yet available. The CCHF vaccine
development is very difficult because it requires the known pathogenic human
host and it is also difficult to grow the virus in culture medium. The significance
of this modern approach is, it reduces the time and risk of pathogenesis; in
order to overcome the problems of attenuated vaccine development. Epitope based
vaccine consists of short peptide sequence which is derived from small part
of virulence protein. Antigenic determinants are present in certain part of
the vaccine peptide sequence. This vaccine should cover the Human Leukocyte
Antigen (HLA) haplotypes of the target population, be effective against a wider
spectrum of Congo virus strains and not have any self-effective epitopes and
produce effective immune response (Eswar et al., 2007).
A No. of computational tools are now available for prediction of T-cell epitopes
(Parida et al., 2007; Shakyawar
et al., 2011), all overlapping nonamers of CCHFV to Human HLA Class
I molecules have been analysed. The selected peptides have been modeled on corresponding
HLA to validate the binding prediction. Some peptide identified from Bioinformatics
and Molecular Analysis Section (BIMAS) and SYFPEITHI that binds to Class I HLA
are also revealed. A No. of peptides were chosen for structural modeling on
the bases of their binding affinity to Class I alleles by multiple analytical
tools, since, the putative peptide is predicted to form stable complex with
HLA allele through molecular modeling and it have not any identical peptide
of Human proteome cross checked by HLApred (Berman et
al., 2000). The aim of the study is to suggest these peptides as potential
vaccine candidate development.
MATERIAL AND METHODS
The in silico study was conducted at Department of Biotechnology, Mangalayatan University, Aligarh from Nov, 2010 to May, 2011.
Virus and protein: RNA-dependent RNA polymerase (ACM78472.1), nucleocapsid protein (ABB30042.1) and nucleoprotein (BAE80107.1) are the protein of Crimean-Congo Hemorrhagic Fever Virus (CCHFV) strain isolated from Xinjiang province available in the NCBI Protein data base and hence it is used for this analysis.
Physical properties of the selected proteins: Bioinformatics tools were
used for the analysis of proteome of CCHF virus. The protein sequences of were
retrieved from www.ncbi.nlm.nih.gov.
The expected molecular weight, highly repeated amino acids (%) of repetition,
least repeated amino acid and isoelectric point (pI) values were calculated
using ExPaSy (http://www.expasy.org/)
(Kyte and Doolittle, 1982; Shehzadi
et al., 2011).
MHC-Class I binding epitope prediction: All of these targeted proteins
of the CCHF virus strain found in Xinjiang namely RNA-dependent RNA polymerase,
nucleocapsid protein and nucleoprotein were analyzed for the Cytotoxic T-lymphocytes
(CTL) epitopes using several algorithms. BIMAS online tool was used to analyze
binding of all consensus peptides with 33 human HLA allele that which helps
to identify those peptides in the targeted proteins with high affinity promiscuous
epitopes that binds to HLA (Parker et al., 1994).
The binding affinity (T1/2) value is based on the half time (min)
of dissociation of β2 microglobulin from HLA. The T1/2 value
was set at cutoff T1/2 ≥100 for peptide selection, other several
algorithms based tools viz. Propred1, SYFPEITHI and Propred are also used for
prediction of putative T-cell epitopes (Singh and Raghava,
Propred1 is matrix-based method that allows prediction of MHC binders for various
alleles based on the multiplication and additional matrices, proteosome cleavage
site, simultaneously. This is based on the observations made in previous studies
which demonstrate that MHC binders having proteosome cleavage site at their
C terminus have high potency to become T-cell epitopes. (Singh
and Raghava, 2001). Endogenously synthesized peptides of 9-11 amino acids
of HLA class I molecules get interacted with T-cell receptor of T-cells on the
surface of infected cells. The presence of allele-specific amino acid motifs
has been demonstrated by sequencing of peptides eluted from MHC molecules (Lund
et al., 2002).
Structure-based modeling of T-cell epitope: Molecular modeling and structural
analysis (Chaitra et al., 2005) were performed
for the detection of binding peptides to their respective class I HLA alleles.
Sample peptides of high affinity binders for a few alleles where structures
are known (A 0201, A2, A 2402, B 1501, B 2705, B 2709, B 3501, B 4403, B 4405,
B 5101, B 5301) were modeled employing their respective structural templates
(1AO7, 1AKJ, 2BCK, 1XR8, 1HSA, 1UXW, 1A1M, 1SYS, 1SYV, 1A1O, 1EFX, 1IM9 and
1QQD). Two peptides viz. LLGIKCSFV and LRFGMLAGL were selected with the help
of scoring based algorithms of BIMAS (Parker et al.,
1994; Parida et al., 2007). These peptides
have higher binding affinity. These selected peptides with highest and lowest
T(1/2) were modeled on to their respective structural templates and
the complexes were subjected to energy minimizations (Vani
et al., 2006). The binding of the peptides was estimated by analyzing
the intra-molecular hydrogen bonds, electrostatic, van der Waals and hydrophobic
interactions with the protein residues in the vicinity.
The Modeller (Eswar et al., 2007) was used for
the designing of the structures of those alleles whose structures were not available
in the PDB server while the CPH model server (Nielsen et
al., 2010) was used to design the structures of the predicted binding
peptides. After designing the structures docking of selected alleles and peptides
was performed with the help of Autodock. This was done to out the energy minimization
(Morris et al., 1998; Namasivayam
and Gunther, 2007; Amir et al., 2010) and
then PMV (Python Molecular Viewer) was used for the visualization of Binding,
position, H-bonding between the selected peptides and alleles.
In this present study, three putative proteins of CCHF virus were used for
the physicochemical analysis (Stevenson et al., 2007)
such as molecular weight, isoelectric point (pI value) and antigenic nature.
The RNA-Dependent RNA Polymerase protein has the highest molecular weight of
about 447836.7 KDa which consists of Leucine (L) a neutral nonpolar amino acid
residue has the highest percentage of repetition (12.4%). The least repeated
residue of L-segmented protein of CCHFV is a nonpolar Tryptophan (W) (0.9%).
The M-segment viral peptide encoded by nucleocapsid protein is NCM (53955.5
KDa molecular weight) comprising 482 amino acid residues. Lysine (K) has highest
percentage and Cysteine (C) is the least repetitive amino acid residues(1.2%)
of this protein; another targeted protein has the lowest molecular weight of
about 8223.4 KDa (i.e., S-segment encoded the nucleoprotein), Lysine(K) has
the highest percentage of repetition (13.7%), Histidine (H) and Proline (P)
are the least repeated amino acid residues (1.4%) of nucleoprotein. The physicochemical
properties of putative proteins were given in Table 1. The
pI value of any protein indicates the stability of protein in that particular
isoelectric point. Isoelectric points of these proteins were ranged between
7.14 to 9.48.
Binding specificity of promiscuous T-cell epitopes to HLA class-I molecules:
The prediction of epitopes with their position and corresponding promiscuous
HLA alleles by using different tools has been summarized in Table
||It comprises the data of CCHFV proteins, molecular weight
and percentage of highly repeated and least repeated amino acid residues
in individual protein. The percentage of amino acid residues gives an outlook
for their pI value and their probability of incidence in the antigenic epitopes
|L*(Lucine) and W# (Tryptophan) are non-polar anchor
residue for HLA predicted epitopes. K**(Lysine) is an anchor residue and
also for HLA predicted epitopes. H/P***(Histidine/Proline) are least repeated
||The predicted peptides from target protein binds to different
HLA class I alleles (BIMAS T(1/2)≥100 and SYFPEITHI value≥15)
The promiscuity of binding of a peptide to HLA alleles is important since
inclusion of such peptides in the vaccine construct provides a greater population
coverage which helps to short out the promiscuous peptide that needs to be in
vaccine developments (Herrera et al., 2010) .
||This conservation plot represents the number of peptides of
all three protein of CCHFV that binds to 33 Class I HLA alleles at cutoff
T(1/2) ≥100. B_2705, B_5101, B_5102, A_0201, B_60, A_68.1
are some strong binding alleles which bind to most of the peptides and also
shown by the tallest bar. HLA alleles A3, A24, B14, B62, B7, B_2702, B_4403,
B_5103, B_5201, B_5801 and Cw_0301, Cw_0401 bind to the less No. of predicted
BIMAS is the immunoinformatics tool freely available to be used for prediction
of the antigenic epitopes in the complete protein with more effective and accurate
prediction of MHC binding affinity (i.e., T (1/2) value). The binding
analysis of all conserved nonamers of all three consensus CCHFV proteins to
33 HLA class I alleles at different binding affinities.
Total 71 epitopes were predicted against 33 alleles of MHC Class I by using the tool BIMAS. The maximum number of epitopes were represented by RNA dependent-RNA polymerase protein comprising 65% of all MHC Class I predicted epitopes, 29.5% of MHC Class I predicted epitopes from nucleocapsid protein and minimum number of epitopes from nucleoprotein 5.6% (Table 2). LLGIKCSFV, LRFGMLAGL, EPSLFNPNI and SQFLFELGK are the promiscuous binders of MHC Class I alleles. In case of nucleocapsid protein RRRNLLLNR and CAWVSSTGI are the best binders in terms of quantitative scores of HLA alleles (MHC Class I) coverage. For the nucleoprotein not also have the epitope of good quantity covering HLA alleles available in BIMAS. Out of these 33 HLA alleles B_2705 is capable for binding to the highest number of predicted promiscuous epitopes all proteins show the tallest bar in Fig. 1. Other HLA alleles binding to the less number of promiscuous epitopes are also shown in same figure.
Conserved epitope of CCHF virus protein: It is important to identify those peptides which are conserved across the various strains of CCHF virus and in this study that has been shown for the conserved peptides present in the constituent proteins of CCHF virus.
The analysis reveals that there are number of suitable peptides from RNA dependent-RNA
polymerase which may be included in the construction of poly epitopes T-cell
vaccine (Parida et al., 2007). Some of the conserved
peptides (LLGIKCSFV, EPSLFNPNI, LRFGMLAGL and SQFLFELGK) with class I presentation
potential along with their interaction energies are, -29.31, -26.85, -35.05
and -23.97 (in kcal mol-1), respectively given in Table
3. High T(1/2) and interaction energy indicate high HLA binding
affinity. These peptides are promiscuous HLA binders. It will be useful to include
these peptides in a chimeric constructs containing both cytotoxic and helper
epitopes. It is expected that though this T-cell vaccine would not prevent CCHF
virus infection, it would aid in quick clearance of the virus and prevent the
severe infection (Parida et al., 2007).
||The peptide binding to the HLA class I molecule. The peptides
(shown in green colour) predicted to a have very high affinity for the allele
A_0201 and B_2705 modeled on to the crystal structure (1AO7 and 1 HAS) based
on the position of the peptide. Potential hydrogen bonds are shown. The
high binder peptide (a) LLGIKCSFV and (b) LRFGMLAGL are derived from the
||The conformational properties of the peptides with efficient
binding energy and present on the variable regions of predicted peptide
as investigated by molecular dynamics simulation using Autodock tool v3.0
It is reported that, the primary function of T-Cell vaccine is to generate
CTLs to degrade the virus infected cells. The viral antigens released when get
lysed are capable of stimulating antibody response against these antigens get
leading to neutralization of reinfecting and residual viruses in the system.
Since these events take place in during the incubation phase of the virus infection,
if any. It is likely to be very mild. Beside the idiotype and anti-idiotypic
antibody cascades generated by T-Cell epitopes would reinforce T-Cell memory
(Lal et al., 2006; Nayak
et al., 2001, 2005; Mohabatkar
and Mohammadzadegan, 2007).
The characterization of putative peptides on the basis of antigenic variability
depends on the surface exposed regions of target CCHFV protein revealed that
6 of the total 71 predicted epitopes were present. Out of six short listed peptides,
four peptides were chosen here for their further characterization on the basis
of their energy minimization value. Moreover with the SYFPEITHI, it scored high
with a value of 27 and 23 for the binding to HLA alleles like B_2705 and A_0201
corresponding to their short listed peptides LRFGMLAGL and LLGIKCSFV, respectively.
Figure 2a and b illustrates the interaction
of these two peptides with their respective alleles (Kavita
et al., 2010). The resulting peptides LRFGMLAGL, of RNA polymerase
protein binds to HLA B_2705. It is seen to make two hydrogen bonds from its
arginine in the 2nd position to asparagine at position 223 of the B_2705 and
leucine in the 1st position to a glutamine at position 226 of this allele. Similarly
the peptide LLGIKCSFV, of same protein binds to HLA A_0201. It also makes two
hydrogen bonds from its lysine in the 5th position to a arginine at position
48 of the allele A_0201 and glycine in the 3rd position to a arginine at position
12th of this allele with its high affinity (Parida et
al., 2007; Tambunan and Parikesit, 2010).
It must be noted that MHC class I a peptides have preference for hydrophobic
or positively charged amino acid residues at carboxyl end for proper biding
in pockets (Brusic et al., 2002). The screening
in this work also listed two more peptides TPLNEVHSI and GEVMSLRQL that were
presented on class I allele of RNA dependent-RNA polymerase and scored 1320
and 352 with BIMAS. These epitopes were, however, not included for simulation
analysis. Simulation studies of the epitope LRFGMLAGL and LLGIKCSFV formed stable
MHC-peptide complexes with the energy minimization of -35.05 and -29.31 (kcal
mol-1), respectively. The other two peptides EPSLFNPNI and SQFLFELGK
identified in the present study were found to be antigenically variable with
energy minimization value of -26.85 and -23.97 (kcal mol-1), respectively
(Kavita et al., 2010). This can possibly be targeted
for designing of vaccine against CCHF virus strains of Xinjiang province.
The screening of putative epitopes using bioinformatics tools thus suggests that protein RNA dependent-RNA polymerase of CCHFV could be used for preparation of immunological constructs. Molecular simulation and binding tests also suggest that the two nonameric epitopes LRFGMLAGL and LLGIKCSFV predicted and reported for the first time have considerable binding with MHC molecules and low energy minimization values providing stability to the peptide-MHC complex. These peptide construct will further undergo wet lab studies, for the development of targeted vaccine against CCHF virus strains. Using a similar approach the short listed candidate epitopes for vaccine design using other proteins can also be targeted that would reduce time and experimental expense.
The authors are grateful to Prof. Ashok Kumar (Dean, I.B.M.E.R, Mangalayatan University Aligarh, U.P., India) for providing necessary facilities and encouragement. The authors are also thankful to all faculty members of the Institute of Biomedical Education and Research, Mangalayatan University Aligarh, U.P., India for their generous help and suggestions during the course of experimental work and manuscript preparation.
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