Content uploaded by Modhusudon Shaha
Author content
All content in this area was uploaded by Modhusudon Shaha on Nov 01, 2015
Content may be subject to copyright.
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 99
INTERNATIONAL JOURNAL OF CURRENT RESEARCH IN
CHEMISTRY AND PHARMACEUTICAL SCIENCES
(p-ISSN: 2348-5213: e-ISSN: 2348-5221)
www.ijcrcps.com
Research Article
PREDICTION OF NEW CONSERVED EPITOPES IN PROTEIN 3D MODEL TO NEUTRALIZE
INFLUENZA A VIRUS STRAIN H3N2 CIRCULATING IN BANGLADESH
MODHUSUDON SHAHA1, MOHAMMAD ARIFUL ISLAM1, ABUL BMMK ISLAM2, MD. FIROZ AHMED3,
MD. MAJIBUR RAHMAN1, SABITA REZWANA RAHMAN1*
1Department of Microbiology, University of Dhaka, Dhaka-1000, Bangladesh.
2Department of Genetic Engineering and Biotechnology, University of Dhaka, Dhaka-1000, Bangladesh.
3Department of Microbiology, Jahangirnagar University, Savar, Dhaka, Bangladesh.
Corresponding Author: sabita.rahman223@gmail.com
Abstract
Influenza A virus H3N2 strain are simultaneously prevalent among human and bird population sometimes causing epidemic
besides seasonal infections. This virus causes a substantial amount of morbidity and mortality in different parts of the worl d
especially in the developing countries like Bangladesh. Although vaccine was developed against this virus strain, the activity of
vaccine fails frequently due to accumulation of mutations in hemagglutinin (HA) gene. Here, we suggested an effective protein
model with conserved epitope-based vaccine design which might be capable to neutralize that strain. After partial sequencing of
HA gene of H3N2 isolated from Bangladeshi patients, we observed several mutations at different positions, some of which lies in
existing epitopes or active sites which indicates possible resistance to existing vaccines, although experimental confirmation is
needed. However, multiple sequence alignment with previously reported Bangladeshi and vaccine strains we have identified
several conserved regions and some of these also fall in predicted and experimentally determined epitopes which may be useful
for a new and potential vaccine development. We predicted a protein 3D model with the sequenced Bangladeshi H3N2 strain and
identified conserved highly immunogenic epitopes and active sites in it which may be further evaluated experimentally for
developing vaccine against it.
Keywords: Conserved epitopes, H3N2 strain, Hemagglutinin, Influenza A virus, Mutations.
Introduction
Influenza virus causes seasonal epidemics as well as
occasional pandemics with substantial morbidity and
mortality where seasonal influenza infections have been
trying to be prevented by vaccination but not pandemic
viruses (Xu et al., 2013). Different studies reported that
Influenza A viruses (IAV) are responsible for millions of
deaths causing acute respiratory illness (Chow et al.,
2006; Mallia and Johnston, 2007; Tate et al., 2014).
Being a negative stranded RNA virus, influenza A virus
infects approximately one-fifth of human population per
annum (Xiu et al., 2008). Treatment or vaccination
against IAV is difficult for frequent changes of its
genome through antigenic drift and shift. The two
membrane bound surface glycoproteins, the
neuraminidase (NA) and the hemagglutinin (HA) are
expressed by IAV which are responsible for the variation
of genome and helps to escape from the existing
antiviral drugs and vaccines (Shen et al., 2013; Tate et
al., 2014). Currently, the strategies against IAV in
development include broadly neutralizing antiviral
therapy, universal influenza vaccine and small-molecule
inhibitors (Du et al., 2012; Ekiert and Wilson, 2012;
Gilbert, 2012). Antigenic drift and shift occur in both NA
and HA genes (Plotkin and Dushoff, 2003). As NA is less
prevalent on virion surface and possess limited
interaction with neutralizing antibodies, it is considered
less relevant (Plotkin and Dushoff, 2003). Hence, HA
proteins are mostly concentrated for the study of
antigenic variability (Bush et al., 1999a; Bush et al.,
1999b; Lee and Chen, 2004; Smith et al., 2004).
HA plays important functions in viral cell cycles like
attachment of virus to sialic acid receptor of host cell
membrane and internalization into the late endosome,
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 100
thus determining the host specificity (Skehel and Wiley,
2000; Webster et al., 1992; Wiley and Skehel, 1987). Of
about 16 subtypes 3 (H1, H2 and H3) of viruses are
known to be responsible for humans pandemics (Sahini
et al., 2010). Some regions of HA are frequently drifted
that may be responsible to evolve for some other
reasons like to enhance post-translational modifications,
facilitate protein folding or regulation of secondary as
well as tertiary structures. HA of IAV contains different
glycosylation sites where glycan can bind and thought to
be important part which can contribute to antigenic drift.
Number of glycosylation sites has a strong impact on the
activity of HA, whether this will activated or deregulated
(Wiley et al., 1981). Addition of glycan in HA protein
sometime have selective advantage like hindering the
binding of neutralizing antibody (Ab) to the epitopes of
antigen. Epitopes, the conserved regions in different
strains of influenza viruses which are recognized by
neutralizing antibodies are elementary part to develop a
proper treatment against influenza viruses (Iba et al.,
2014). The globular head of HA contains epitopes which
are well characterized and clustered in A, B, C, D and E
sites of HA in H3 viruses (Underwood, 1982; Wiley et
al., 1981). HA gene of influenza virus can acquire
mutation readily and therefore make themselves
resistance to these antibodies. Thus, preventive
vaccination is the most preventive measure to control
influenza A viruses and to remain effective, the strain
selected for vaccine development need to be changed
almost every year (Salzberg, 2008).
Herein, we determined the phylogenic relationship of
IAV HA gene and amino acid variation comparing with
native and foreign strains. We analyzed the conserved
regions found in HA of IAV and checked its rate of
mutation in these regions compared to others. We also
develop a putative protein model which could be a target
for designing a potential vaccine to prevent not only the
strains of Bangladesh but also related all strains.
Materials and Methods
Sample collection and processing
To perform this study 400 nasopharyngeal swab
samples were collected from the patients who were
suffering from influenza like symptoms maintaining
aseptic condition. The samples were transferred to the
clinical laboratory using VTM and kept at -80oC until use.
This study was performed in the Clinical Laboratory of
the Department of Microbiology, University of Dhaka and
samples were collected after containing an informed
written consent from the participants of this experiment.
The study protocol was approved by the ethical
committee of Dhaka Medical College, Dhaka-1000,
Bangladesh (reference number: DMC-
MEU/ECC/214/17).
Preparation of viral DNA and sequencing
Viral RNA was extracted from sample fluids by pathogen
kit (Stratec molecular, Berlin, Germany) according to
manufacturer’s instruction. The extracted RNA was
subjected to one step real-time reverse transcriptase
PCR (rRT-PCR) using primers, forward: GAC CRA TCC
TGT CAC CTC TGA C, reverse: AGG GCA TTY TGG
ACA AAK CGT CTA and probe: TGC AGT CCT CGC
TCA CTG GGC ACG. Amplification of HA gene by the
above primers was done using a 20µl reaction mixture
containing buffer (2x) 12.5µl, enzyme reverse
transcriptase (25µM) 1µl, forward primer (40µM) 0.5µl,
reverse primer (40µM) 0.5µl, probe (5µM) 0.5µl,
enhancer 1µl and dH2O. The thermal conditions, used
for this amplification was 30 minutes reverse
transcription at 50oC, 15 min initial PCR activation step
at 95oC, 29 cycles of reaction containing denaturation 15
seconds, annealing 30 sec, extension 1 min 15 sec at
94oC, 50oC and 72oC respectively along with a final
extension of 10 min at 72oC. Then the positive products
of RT-PCR were purified using ExoSAP-IT (CA, USA)
according to the manufacturer’s instruction. Sequencing
of HA gene was performed using a primer
TGTAAAACGACGGCCAGT by BigDye®Terminator v3.1
Cycle Sequencing Kit (California) according to the
instruction of manufacturer.
Phylogenetic analysis using HA gene of IAV
The obtained sequences were aligned by Clustal Omega
method (Larkin et al., 2007). The reference sequences
for this alignment were local and vaccine HA sequences
collected from NCBI GenBank and Influenza Virus
Database (IVR) (Bao et al., 2008) (Supplementary Table
S1. Phylogenetic tree was formed by the bootstrap,
distance and Neighbor-Joining (NJ) method to carry out
phylogenetic analysis.
Comparison of experimental sequences with
different conserved regions and epitopes
Different conserved regions and epitopes against B cell,
T cell and MHC types in HA gene products were
compared with the experiment sequences using MEGA
5 tool (Tamura et al., 2011) with Clustal algorithm. The
epitopes and sequences required for this study were
collected from Influenza Research Database (IRD)
(Squires et al., 2012) and Influenza Virus Resource
Database (IVR) (Bao et al., 2008) respectively.
Prediction of protein model
We used I-Tasser tool (Zhang, 2008) to model protein
using first some 229 amino acid from our sequence and
rest from closely matched sequence (accession no.
ACZ05788.1). Protein 3D structure is visualized and
epitopes are marked using UCSF Chimera (Pettersen et
al., 2004). Epitopes present in our sequences along with
surface accessibility were predicted using IEDB server
(Kim et al., 2012).
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 101
Active sites or pockets of the protein were determined
by using fPocket online tool (Schmidtke et al., 2010).
Different binding sites, solvent accessibility and
disulphide bridges were analyzed by PredictProtein
server (Rost et al., 2004).
Sequence deposition
Partial CDS of HA sequences is deposited in GenBank
under accession numbers: KP222533 (IAV_542),
KP222534 (IAV_541), KP222535 (IAV_550),
KP222536 (IAV_558) and KP238097 (IAV_473).
Results
Subtyping and sequencing of HA gene
HA gene, the antigenic determinant of IAV, was
sequenced and BLAST searched to find the subtypes
of that sequences. Of 400 samples, 48 (12%) was
found positive to influenza A virus (IAV) by real time
reverse transcriptase PCR (rRT-PCR). Of them, 5
samples (IAV_473, IAV_541, IAV_542, IAV_550 and
IAV_558) were subjected to hemagglutinin (HA) gene
sequencing and all of them were found to contain
identical nucleotides although differ in length due to
partial coding sequence (CDS) (data not shown). As
all of the sequences were identical, IAV_542 (NCBI
accession no: KP222533) – the largest partial CD was
selected for further bioinformatics analysis. NCBI-
BLAST search with IAV_542 revealed the subtype
H3N2 (data not shown).
Evolutionary relationship of our IAV with other
circulating IAVs of Bangladesh
The nucleotide sequence of IAV_542 was subjected to
nucleotide BLAST search against NCBI database to
observe the sequence similarity with the existing
sequences in the NCBI GenBank and found that
accession number KF598719 as the most closely
matched sequence with 99.85% identity
(Supplemental Table S1). The NCBI-BLAST result
showed that only one nucleotide at position 209
(G209A) was mutated in our sequence.
Table 1: Observed mutations in IAV_542 comparing to existing epitopes collected from Influenza Virus Resource
database.
Epitopes from IVR database
Observed Sequence in IAV_542
Mutation position
ALNVTMPNNEKFDKLYI
ALNVTMPNNEQFDKLYI
K189Q
ASGRVTVSTKRSQQTV
SSGRITVSTKRSQQTV
A214S, V218I
ATELVQSSSTGRICDS
ATELVQSSSTGEICDN
R66E, S70N
CKRRSNNSFFSRLNWLT
CIRRSNSSFFSRLNWLT
K156I, N161S
CYPYDVPDYASLRSLVASSGTLEFINE
DFNWT
CYPYDVPDYASLRSLVASSGTLEFNNE
SFNWT
I137N, D140S
DQIEVTNATELVQSSSTGGI
DQIEVTNATELVQSSSTGGI
G66E
DYASLRSLVASSGTLEFINEGFNWTGV
TQNGGSSAC
DYASLRSLVASSGTLEFNNESFNWTGV
TQNGGSSAC
I137N, G140S
ELVQSSSTGRICDSPHQILD
ELVQSSSTGEICDNPHQILD
R66E, S70N
GTLVKTITNDQIE
GTIVKTITNDQIE
L41I
HHAVPNGTL
HHAVPNGTI
L41I
HHAVSNGTLVKTITNDQIEV
HHAVSNGTIVKTITNDQIEV
L41I
KSEYKYPALNVTMPNN
HLNFKYPALNVTMPNN
K72H, S73L, E74N,
Y75F
KSFFSRLNWLTHLK
SSFFSRLNWLTHLN
K161S, K174N
LVKTITNDQIEVTNATELVQSSSTGRIC
DSPHRIL
IVKTITNDQIEVTNATELVQSSSTGEICD
NPHQIL
L41I, R66E, S70N,
R73Q
NFDKLYIWG
NFDKLYIWG
N189Q
NVTMPNNEKFDKLYIWGV
NVTMPNNEKFDKLYIWGV
N189Q
QIEVTNATELVQSSSTGRIC
QIEVTNATELVQSSSTGEIC
R66E
QKLPGNDNSTATLCLGHHAVPNGTLV
KTITNDQIE
QKLPGNDNSTATLCLGHHAVPNGTIVK
TITNDQIE
L41I
RLNWLTHLK
RLNWLTHLK
K174N
SACKRRSNKSFFSRLNWLTH
SACIRRSNSSFFSRLNWLTH
K156I, K161S
SFFSRLNWLHKSEYKY
SFFSRLNWLTHLNFKY
H171T, K172H, S173L,
E174N, Y175F
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 102
SLYAQASGRITVSTKRS
FLYAQSSGRITVSTKRS
S209F, A214S
SSCKRRSNNSFFSRLNWLTH
SACIRRSNSSFFSRLNWLTH
S154A, K156I, N161S
VPNGTLVKTITNDQIE
VPNGTIVKTITNDQIE
L41I
VPNGTLVKTITNDQIEVTNAT
VPNGTIVKTITNDQIEVTNAT
L41I
VQSSSTGGICDSPHQIL
VQSSSTGEICDNPHQIL
G66E, S70N
YPALNVTMPNNGKFDKLYIWGVHHPS
TDRDQTS
YPALNVTMPNNEQFDKLYIWGVHHPG
TDKDQIF
G188E, K189Q, S202G,
R205K, T208I, S209F
The sequence of IAV_542 was analyzed using
EMBOSS Transeq tool of EMBL-EBI server
(McWilliam et al., 2013) to find all six frames of in silico
translation of proteins and subjected to protein BLAST
(PSI) against NCBI protein database to find the correct
frame (ORF) of the protein translation. The IAV_542
translated protein sequence was then aligned with HA
protein of H3N2 of previously reported different
Bangladeshi sequences (Supplementary Table S2)
collected from Virus Resources Database (IVR) (Bao
et al., 2008). We observed similarities of our partial HA
protein sequence with other Bangladeshi sequences,
however, there are several amino acid mutations like
G66E (amino acid E at 66 position of HA protein
instead of G), S70N, K156I, N/K161S, K174N,
K/E189Q, S/N205K, S209F and A214S (Figure 1a).
The above mutations were thought to have possible
effect on structural and functional activity of HA protein
which may be a significant cause of resistance to
different drugs. Phylogenetic tree of above alignment
revealed that our sequence was most closely related
with ACC67740 with a similarity of 71% (Figure 1b).
Figure 1a: Alignment IAV_542 (KP222533) with different Bangladeshi strains. Matched amino acids were presented
as dot and mismatched were shown in symbols. Alignment was done by MEGA 5 software and visualized using
Jalview software.
Figure 1b: Phylogenetic analysis of IAV_542 (KP222533) with different existing Bangladeshi strains collected from
IVR database.
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 103
Mutations are observed in protein sequences of
our IAV and current vaccine sequences
Multiple sequence alignment of our sequence
(IAV_542) with different vaccine strains
(Supplementary Table S2) used for developing
existing vaccines are collected from IVR (Bao et al.,
2008) database revealed several mutations, but the
important one is at position 70 (S70N) (Figure 2a).
This mutation position lies on 4 existing epitopes,
which are ELVQSSSTGRICDSPHQILD,
LVKTITNDQIEVTNATELVQSSSTGRICDSPHRIL,ATE
LVQ SSSTGRICDSand VQSSSTGGICDSPHQIL
(Table 1). So, mutation S70N might cause those
epitopes to be ineffective and might not be recognized
by antibody or vaccine against that strain of IAV and
thus may lead to vaccine resistance. This demands
detail experimentation on the possible vaccine
resistance due to our identification of such mutation.
Vaccine strain ACS71642 is highly related (with 0.01
evolutionary distance) but not identical with our
sequence that was confirmed by phylogenetic tree
analysis (Figure 2b). As we did not find any vaccine
strain which is totally matched with our sequences, it
may be required to consider developing a new protein
model which could be effective to decrease the burden
of IAV, especially in slums of Dhaka city, Bangladesh.
Figure 2a: Alignment IAV_542 (KP222533) with
vaccine strains. Amino acids were shown as dot and
mismatched are presented in symbols. Alignment was
done by MEGA 5 software and visualized using
Jalview software.
Figure 2b: Phylogenetic analysis of IAV_542 (KP222533) with different vaccine strains collected from IVR database.
Figure 3: Protein 3D model of IAV_542 showing the predicted epitopes common among the conserved regions in
sequence alignment with other Bangladeshi and vaccine strain (Supplementary Table S2). The highlighted regions
with Green color demonstrates the predicted epitopes marked using UCSF Chimera software.
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 104
Multiple mutations are possible in known epitopes
of IAVs in our sequence
Epitopes are the vital part of an organism to be
identified by drugs and vaccines. More than 200
existing experimentally validated epitopes were
collected from IRD (Squires et al., 2012) to be
compared with our HA sequence. Analysis of our
sequence with these existing epitopes revealed that
27 epitopes that may sighted in our sequence were
mutated somehow (Table 1). These mutations in
epitopes, which is the determinant of vaccine efficacy,
might made the responsible virus resistant to different
existing vaccine, and thus, demanding to design a new
protein model that will be able to neutralize IAV
(H3N2) circulating in Bangladesh.
Table S1: NCBI BLAST (BLASTn) search result of IAV_542. (Result shown only till one substitution).
Accession
Identity (%)
Coverage (%)
Substitution
E-value
KF598719.1
99.85
100
1
0
KF598718.1
99.85
100
1
0
KF598713.1
99.85
100
1
0
KF598714.1
99.85
100
1
0
KF598712.1
99.85
100
1
0
KF598708.1
99.85
100
1
0
KF598703.1
99.85
100
1
0
KF598705.1
99.85
100
1
0
KF598702.1
99.85
100
1
0
KF586764.1
99.85
100
1
0
KF586763.1
99.85
100
1
0
KF586760.1
99.85
100
1
0
KF586742.1
99.85
100
1
0
KF586740.1
99.85
100
1
0
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 105
KF586729.1
99.85
100
1
0
KC893081.1
99.85
100
1
0
KC892616.1
99.85
100
1
0
KC892303.1
99.85
100
1
0
CY120861.1
99.85
100
1
0
Table S2: Bangladeshi and “vaccine” IAV HA sequence information that were extracted from NCBI’s Influenza Virus
Resources (IVR) database.
Sequence type
Accession no.
Country
Year
Non-vaccine strain
ACC67740
Bangladesh
2006
ACC67338
Bangladesh
2005
ACC67339
Bangladesh
2005
ABA61037
Bangladesh
2003
ABA61031
Bangladesh
2003
ABA61040
Bangladesh
2003
ABA61045
Bangladesh
2003
ACC67337
Bangladesh
2003
ABA61041
Bangladesh
2003
ABA61024
Bangladesh
2002
Vaccine strain
ABF21268
Bangkok
1979
ABF21269
Beijing
1989
ABF21271
Leningrad
1986
ABE73115
Moscow
1999
ACS71642
Perth
2009
AGL06219
Texas
2012
Conserved locations among our and other strains
could be targeted for epitope based vaccine
development
Multiple sequence alignment of our experiment
sequence with previously described Bangladeshi
sequences and vaccine strain sequences revealed
some conserved regions which could be the targets for
designing vaccine. The observed conserved regions in
both existing Bangladeshi strains, available vaccine
strains and our experiment sequence are amino acid
number 26 to 36 (STATLCLGHHAV), 51 to 61
(IEVTNATELVQ), 80 to 91 (NCTLIDALLGDP), 112 to
122 (SNCYPYDVPDY), 124 to 137
(SLRSLVASSGTLEF), 164 to 171 (FFSRLNWL), 191
to 202 (FDKLYIWGVHHP) (Supplementary Figure
S1). Some of these conserved sites are potential
immunogenic epitopes (shown in bold format) as
predicted by IEDB server (Kim et al., 2012).
Figure S1: Evaluation of conserved regions in
IAV_542 by aligning both Bangladeshi and Vaccine
strains (Supplementary Table S2). Amino acids were
shown as dot and mismatched are in symbols.
Alignment was done by MEGA 5 software and
visualized using Jalview software.
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 106
Predicted 3D model of the HA sequence with
epitopes and active sites
Protein model of the compiled sequence (our partial
HA sequence and rest from closely matched NCBI
sequence ACZ05788.1) by I-TASSER bioinformatics
server (Zhang, 2008) revealed a 3D structure in which
we delineated the conserved predicted epitopes
conformations (Figure 3). Analysis of our partial HA
protein sequence by fPocket online tool (Schmidtke et
al., 2010) revealed 11 pockets in predicted tertiary
protein structure (Supplementary Figure S2). The
antigenicity and surface accessibility of the protein has
been delineated in supplementary Figure S3. The
developed protein by our sequence revealed that the
partial protein contains 61.67% loop, 16.74% helix and
21.59% strand. It also analyzed the solvent
accessibility where 54.19% were exposed, 39.65%
were buried and the rest were intermediate. The
disulphide bridges were found between amino acid 30
and 80, 68 and 92, 113 and 155 regions. It also
revealed different binding sites at 21-23, 72, 78, 96,
98, 110-112, 117, 149, 156-159, 166, 186, 188, 213,
217 and 225 amino acid positions (Supplementary
Figure S4). Figure S2: Presence of pockets in
IAV_542 predicted using fPocket server. Figure A, B,
C, D, E, F indicate the pockets of same sequence in
different views. Different colors shows eleven pockets
in the experiment sequence with a blackish
background.
Figure S3: Prediction of (a) antigenicity and (b) surface accessibility of IAV_542 by IEDB server. The red line is the
cut-off value; yellow and green color portion indicate above antigenicity (A), surface accessibility (B) cut-off and below
antigenicity (A), surface accessibility (B) cut-off respectively.
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 107
Figure S4: Protein binding sites and disulphide bridges of IAV_542 delineated by PredictProtein server. The scale on
the top indicates amino acid numbers, the red color boxes are binding sites, the bridges between two points indicate
disulphide bridge, the horizontal rectangular box contains different blue lines showing the alignment with other NCBI
sequences.
Discussion
Seasonal influenza virus appears frequently with a
significant reassortment of genome where existing
drugs and vaccine are sometimes ineffective (Ghedin
et al., 2005). Sometimes these reassortments by
antigenic drift and shift make the virus to be epidemic
although the virus origin is same to one previously
determined. The mentioned antigenic drift and shift
may be also initiated by frequent mutations which
together can cause significant change in the common
epitopes existing in the genome normally, abnormality
in the conserved regions that were previously selected
for vaccine development (Nicholls, 2006). Thus, we
attempted to analyze phylogenetic analysis with native
(Bangladeshi) and vaccine strains circulating in
Bangladesh to observe the genetic and functional
variability which were thought to have resistance to
existing drugs and vaccine. In this study, above 200
experimental epitopes of IAV-H3N2 were collected
from IVR (Bao et al., 2008) and compared with our
sequences for mutations and developed a protein
model that could be effective to neutralize IAV-H3N2
circulating in Bangladesh.
In this study, the prevalence of IAV-H3N2 was 12%
which is higher than those of previous year 2012, 7%
documented by Fally (Fally et al., 2012). The reason
behind it may be the antigenic drift in the genome of
IAV-H3N2 circulating in Bangladesh which have
exposed to frequent mutations (Matrosovich et al.,
2000; Shil et al., 2011). Our experiment sequences
were found mutated compared to that of other existing
Bangladeshi sequences those were documented
before 2006. Mutations at different positions like
G64E, S68N, K156I, K/N161S, K174N, K/E189Q,
S/N205K and S209F when comparing with different
Bangladeshi IAV-H3N2 sequences may affect the
sequence likely to be distorted from the close
phylogenetic relationship. Among above mutations,
K/E189Q and S209F are responsible for changing the
hydrophilic characteristics to hydroneutral and
hydrophobic respectively which enable the protein to
be insoluble (Phillips, 2013). The above mutations
might have possible effect on structural and functional
activity of HA protein which may be a significant cause
of resistance to different drugs.
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 108
Comparison analysis with different vaccine strains of
IAV-H3N2 revealed the phylogenetic analysis that our
sequence was closely matched with ACS71642 strain
isolated from Texas with an evolutionary distance of
0.0111859, which suggests the origin of the
experiment sequence may be Texas and carried
somehow in Bangladesh. The alignment with the
vaccine strains showed one amino acid mutation at 70
no. position S70N, which may cause a change in HA
protein and might lead to vaccine resistance.
Aligning and comparing with more than 200 epitopes
of IAV-H3N2 strain revealed as high as 40 epitopes
variations which contains mutations of 1 to 7 per
epitope as shown in Figure 3. These mutations in
epitopes, which is the determinant of vaccine efficacy,
might make the responsible virus resistant to different
existing vaccine, thus demand to design a new protein
model that will be able to neutralize IAV (H3N2)
circulating in Bangladesh (Munoz and Deem, 2005).
Comparing with both existing Bangladeshi sequences
and vaccine strain sequences showed many
conserved regions in our sequences, some of which
contain potential epitopes as predicted by IEDB server
(Kim et al., 2012) which could be targeted to develop a
new and effective vaccine against IAV-H3N2.
The designed protein model by I-Tasser (Zhang, 2008)
and visualized by UCSF Chimera software (Pettersen
et al., 2004) (Figure 3) showed a 3D structure which
delineated the loop, helix and sheet structure along
with the highlighting of predicted epitopes.
Predictprotein server (Rost et al., 2004) demonstrated
solvent accessibility, protein disorder and flexibility,
and different protein-protein and protein-nucleotide
binding sites. These active sites can be tested for
drug/small molecule binding capacity.
In conclusion, we have provided the importance of
developing new vaccine targeting HA protein that
would prevent influenza A virus H3N2 strain. As
mutations in this region frequently generating vaccine
resistance within a short interval, our identification of
some antigentic conserved regions not only in existing
Bangladeshi strains but also in current vaccine strains
offers a potential target for new vaccine.
Acknowledgments
This study was funded by Higher Education Quality
Enhancement Project (HEQEP) and University Grant
Commission (UGC), People’s Republic of Bangladesh.
Conflict of interest
Authors have declared no conflict of interest.
References
Bao, Y., P. Bolotov, D. Dernovoy, B. Kiryutin, L.
Zaslavsky, T. Tatusova, J. Ostell, and D. Lipman.
2008. “The influenza virus resource at the National
Center for Biotechnology Information.” J Virol
82(2): 596-601.
Bush, R. M., C. A. Bender, K. Subbarao, N. J. Cox,
and W. M. Fitch. 1999a. “Predicting the evolution of
human influenza A.” Science 286(5446): 1921-5.
Bush, R. M., W. M. Fitch, C. A. Bender, and N. J. Cox.
1999b. “Positive selection on the H3 hemagglutinin
gene of human influenza virus A.” Mol Biol Evol
16(11): 1457-65.
Chow, A., S. Ma, A. E. Ling, and S. K. Chew. 2006.
“Influenza-associated deaths in tropical Singapore.”
Emerg Infect Dis 12(1): 114-21.
Du, J., T. A. Cross, and H. X. Zhou. 2012. “Recent
progress in structure-based anti-influenza drug
design.” Drug Discov Today 17(19-20): 1111-20.
Ekiert, D. C. and I. A. Wilson. 2012. “Broadly
neutralizing antibodies against influenza virus and
prospects for universal therapies.” Curr Opin Virol
2(2): 134-41.
Fally, M. A., M. Redlberger-Fritz, P. Starzengruber, P.
Swoboda, H. P. Fuehrer, E. B. Yunus, W. A. Khan,
and H. Noedl. 2012. “Characterization and
epidemiology of influenza viruses in patients
seeking treatment for influenza-like illnesses in
rural Bangladesh.” J Postgrad Med 58(4): 242-5.
Ghedin, E., N. A. Sengamalay, M. Shumway, J.
Zaborsky, T. Feldblyum, V. Subbu, D. J. Spiro, J.
Sitz, H. Koo, P. Bolotov, D. Dernovoy, T. Tatusova,
Y. Bao, K. St George, J. Taylor, D. J. Lipman, C.
M. Fraser, J. K. Taubenberger, and S. L. Salzberg.
2005. “Large-scale sequencing of human influenza
reveals the dynamic nature of viral genome
evolution.” Nature 437(7062): 1162-6.
Gilbert, S. C. 2012. “Advances in the development of
universal influenza vaccines.” Influenza Other
Respir Viruses 7(5): 750-8.
Iba, Y., Y. Fujii, N. Ohshima, T. Sumida, R. Kubota-
Koketsu, M. Ikeda, M. Wakiyama, M. Shirouzu, J.
Okada, Y. Okuno, Y. Kurosawa, and S. Yokoyama.
2014. “Conserved neutralizing epitope at globular
head of hemagglutinin in H3N2 influenza viruses.”
J Virol 88(13): 7130-44.
Kim, Y., J. Ponomarenko, Z. Zhu, D. Tamang, P.
Wang, J. Greenbaum, C. Lundegaard, A. Sette, O.
Lund, P. E. Bourne, M. Nielsen, and B. Peters.
2012. “Immune epitope database analysis
resource.” Nucleic Acids Res 40(Web Server
issue): W525-30.
Larkin, M. A., G. Blackshields, N. P. Brown, R.
Chenna, P. A. McGettigan, H. McWilliam, F.
Valentin, I. M. Wallace, A. Wilm, R. Lopez, J. D.
Thompson, T. J. Gibson, and D. G. Higgins. 2007.
“Clustal W and Clustal X version 2.0.”
Bioinformatics 23(21): 2947-8.
Int. J. Curr.Res.Chem.Pharma.Sci. 2(3): (2015):99–109
© 2015, IJCRCPS. All Rights Reserved 109
Lee, M. S. and J. S. Chen. 2004. “Predicting antigenic
variants of influenza A/H3N2 viruses.” Emerg Infect
Dis 10(8): 1385-90.
Mallia, P. and S. L. Johnston. 2007. “Influenza
infection and COPD.” Int J Chron Obstruct Pulmon
Dis 2(1): 55-64.
Matrosovich, M., A. Tuzikov, N. Bovin, A. Gambaryan,
A. Klimov, M. R. Castrucci, I. Donatelli, and Y.
Kawaoka. 2000. “Early alterations of the receptor-
binding properties of H1, H2, and H3 avian
influenza virus hemagglutinins after their
introduction into mammals.” J Virol 74(18): 8502-
12.
McWilliam, H., W. Li, M. Uludag, S. Squizzato, Y. M.
Park, N. Buso, A. P. Cowley, and R. Lopez. 2013.
“Analysis Tool Web Services from the EMBL-EBI.”
Nucleic Acids Res 41(Web Server issue): W597-
600.
Munoz, E. T. and M. W. Deem. 2005. “Epitope
analysis for influenza vaccine design.” Vaccine
23(9): 1144-8.
Nicholls, H. 2006. “Pandemic influenza: the inside
story.” PLoS Biol 4(2): e50.
Pettersen, E. F., T. D. Goddard, C. C. Huang, G. S.
Couch, D. M. Greenblatt, E. C. Meng, and T. E.
Ferrin. 2004. “UCSF Chimera--a visualization
system for exploratory research and analysis.” J
Comput Chem 25(13): 1605-12.
Phillips, J. C. 2013. “Hierarchical hydropathic evolution
of influenza glycoproteins (N2, H3, A/H3N2) under
relentless vaccination pressure.” Cornell University
Library (arXiv:1303.4383v1): 1-19.
Plotkin, J. B. and J. Dushoff. 2003. “Codon bias and
frequency-dependent selection on the
hemagglutinin epitopes of influenza A virus.” Proc
Natl Acad Sci U S A 100(12): 7152-7.
Rost, B., G. Yachdav, and J. Liu. 2004. “The
PredictProtein server.” Nucleic Acids Res 32(Web
Server issue): W321-6.
Sahini, L., A. Tempczyk-Russell, and R. Agarwal.
2010. “Large-scale sequence analysis of
hemagglutinin of influenza A virus identifies
conserved regions suitable for targeting an anti-
viral response.” PLoS One 5(2): e9268.
Salzberg, S. 2008. “The contents of the syringe.”
Nature 454(7201): 160-1.
Schmidtke, P., V. Le Guilloux, J. Maupetit, and P.
Tuffery. 2010. “fpocket: online tools for protein
ensemble pocket detection and tracking.” Nucleic
Acids Res 38(Web Server issue): W582-9.
Shen, X., X. Zhang, and S. Liu. 2013. “Novel
hemagglutinin-based influenza virus inhibitors.” J
Thorac Dis 5 Suppl 2: S149-59.
Shil, P., S. Chavan, and S. Cherian. 2011. “Molecular
basis of antigenic drift in Influenza A/H3N2 strains
(1968-2007) in the light of antigenantibody
interactions.” Bioinformation 6(7): 266-70.
Skehel, J. J. and D. C. Wiley. 2000. “Receptor binding
and membrane fusion in virus entry: the influenza
hemagglutinin.” Annu Rev Biochem 69: 531-69.
Smith, D. J., A. S. Lapedes, J. C. de Jong, T. M.
Bestebroer, G. F. Rimmelzwaan, A. D. Osterhaus,
and R. A. Fouchier. 2004. “Mapping the antigenic
and genetic evolution of influenza virus.” Science
305(5682): 371-6.
Squires, R. B., J. Noronha, V. Hunt, A. Garcia-Sastre,
C. Macken, N. Baumgarth, D. Suarez, B. E. Pickett,
Y. Zhang, C. N. Larsen, A. Ramsey, L. Zhou, S.
Zaremba, S. Kumar, J. Deitrich, E. Klem, and R. H.
Scheuermann. 2012. “Influenza research database:
an integrated bioinformatics resource for influenza
research and surveillance.” Influenza Other Respir
Viruses 6(6): 404-16.
Tamura, K., D. Peterson, N. Peterson, G. Stecher, M.
Nei, and S. Kumar. 2011. “MEGA5: molecular
evolutionary genetics analysis using maximum
likelihood, evolutionary distance, and maximum
parsimony methods.” Mol Biol Evol 28(10): 2731-9.
Tate, M. D., E. R. Job, Y. M. Deng, V. Gunalan, S.
Maurer-Stroh, and P. C. Reading. 2014. “Playing
hide and seek: how glycosylation of the influenza
virus hemagglutinin can modulate the immune
response to infection.” Viruses 6(3): 1294-316.
Underwood, P. A. 1982. “Mapping of antigenic
changes in the haemagglutinin of Hong Kong
influenza (H3N2) strains using a large panel of
monoclonal antibodies.” J Gen Virol 62 (Pt 1): 153-
69.
Webster, R. G., W. J. Bean, O. T. Gorman, T. M.
Chambers, and Y. Kawaoka. 1992. “Evolution and
ecology of influenza A viruses.” Microbiol Rev
56(1): 152-79.
Wiley, D. C. and J. J. Skehel. 1987. “The structure and
function of the hemagglutinin membrane
glycoprotein of influenza virus.” Annu Rev Biochem
56: 365-94.
Wiley, D. C., I. A. Wilson, and J. J. Skehel. 1981.
“Structural identification of the antibody-binding
sites of Hong Kong influenza haemagglutinin and
their involvement in antigenic variation.” Nature
289(5796): 373-8.
Xiu, W., Y. Wen, X. Shen, J. Xie, S. Yang, B. Wu, and
M. Wang. 2008. “Molecular evolution of influenza A
(H3N2) viruses circulated in Fujian Province, China
during the 1996-2004 period.” Sci China C Life Sci
51(4): 373-80.
Xu, R., J. C. Krause, R. McBride, J. C. Paulson, J. E.
Crowe, Jr., and I. A. Wilson. 2013. “A recurring
motif for antibody recognition of the receptor-
binding site of influenza hemagglutinin.” Nat Struct
Mol Biol 20(3): 363-70.
Zhang, Y. 2008. “I-TASSER server for protein 3D
structure prediction.” BMC Bioinformatics 9: 40.