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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Structural basis of development of multi-epitope vaccine against Middle East
respiratory syndrome using in silico approach</title><author><name sortKey="Srivastava, Sukrit" sort="Srivastava, Sukrit" uniqKey="Srivastava S" first="Sukrit" last="Srivastava">Sukrit Srivastava</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation><affiliation><nlm:aff id="af2-idr-11-2377">Molecular Medicine Lab, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Kamthania, Mohit" sort="Kamthania, Mohit" uniqKey="Kamthania M" first="Mohit" last="Kamthania">Mohit Kamthania</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation><affiliation><nlm:aff id="af3-idr-11-2377">Department of Biotechnology, Faculty of Life Sciences, Institute of Applied Medicines and Research, Ghaziabad, Uttar Pradesh, India</nlm:aff></affiliation></author><author><name sortKey="Singh, Soni" sort="Singh, Soni" uniqKey="Singh S" first="Soni" last="Singh">Soni Singh</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Saxena, Ajay K" sort="Saxena, Ajay K" uniqKey="Saxena A" first="Ajay K" last="Saxena">Ajay K. Saxena</name><affiliation><nlm:aff id="af2-idr-11-2377">Molecular Medicine Lab, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Sharma, Nishi" sort="Sharma, Nishi" uniqKey="Sharma N" first="Nishi" last="Sharma">Nishi Sharma</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30538505</idno><idno type="pmc">6254671</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6254671</idno><idno type="RBID">PMC:6254671</idno><idno type="doi">10.2147/IDR.S175114</idno><date when="2018">2018</date><idno type="wicri:Area/Pmc/Corpus">000D22</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000D22</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Structural basis of development of multi-epitope vaccine against Middle East
respiratory syndrome using in silico approach</title><author><name sortKey="Srivastava, Sukrit" sort="Srivastava, Sukrit" uniqKey="Srivastava S" first="Sukrit" last="Srivastava">Sukrit Srivastava</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation><affiliation><nlm:aff id="af2-idr-11-2377">Molecular Medicine Lab, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Kamthania, Mohit" sort="Kamthania, Mohit" uniqKey="Kamthania M" first="Mohit" last="Kamthania">Mohit Kamthania</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation><affiliation><nlm:aff id="af3-idr-11-2377">Department of Biotechnology, Faculty of Life Sciences, Institute of Applied Medicines and Research, Ghaziabad, Uttar Pradesh, India</nlm:aff></affiliation></author><author><name sortKey="Singh, Soni" sort="Singh, Soni" uniqKey="Singh S" first="Soni" last="Singh">Soni Singh</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Saxena, Ajay K" sort="Saxena, Ajay K" uniqKey="Saxena A" first="Ajay K" last="Saxena">Ajay K. Saxena</name><affiliation><nlm:aff id="af2-idr-11-2377">Molecular Medicine Lab, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author><author><name sortKey="Sharma, Nishi" sort="Sharma, Nishi" uniqKey="Sharma N" first="Nishi" last="Sharma">Nishi Sharma</name><affiliation><nlm:aff id="af1-idr-11-2377">Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></nlm:aff></affiliation></author></analytic><series><title level="j">Infection and Drug Resistance</title><idno type="eISSN">1178-6973</idno><imprint><date when="2018">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Middle East respiratory syndrome (MERS) is caused by MERS coronavirus (MERS-CoV). Thus
far, MERS outbreaks have been reported from Saudi Arabia (2013 and 2014) and South Korea
(2015). No specific vaccine has yet been reported against MERS.</p></sec><sec><title>Purpose</title><p>To address the urgent need for an MERS vaccine, in the present study, we have designed
two multi-epitope vaccines (MEVs) against MERS utilizing several in silico methods and
tools.</p></sec><sec><title>Methods</title><p>The design of both the multi-epitope vaccines (MEVs) are composed of cytotoxic T
lymphocyte (CTL) and helper T lymphocyte (HTL) epitopes, screened form thirteen
different proteins of MERS-CoV. Both the MEVs also carry potential B-cell linear epitope
regions, B-cell discontinuous epitopes as well as interferon-γ-inducing
epitopes. Human β-defensin-2 and β-defensin-3 were used as adjuvants to
enhance the immune response of MEVs. To design the MEVs, short peptide molecular linkers
were utilized to link screened most potential CTL epitopes, HTL epitopes and the
adjuvants. Tertiary models for both the MEVs were generated, refined, and further
studied for their molecular interaction with toll-like receptor 3. The cDNAs of both
MEVs were generated and analyzed in silico for their expression in a mammalian host cell
line (human).</p></sec><sec><title>Results</title><p>Screened CTL and HTL epitopes were found to have high propensity for stable molecular
interaction with HLA alleles molecules. CTL epitopes were also found to have favorable
molecular interaction within the cavity of transporter associated with antigen
processing. The selected CTL and HTL epitopes jointly cover upto 94.0% of worldwide
human population. Both the CTL and HTL MEVs molecular models have shown to have stable
binding and complex formation propensity with toll-like receptor 3. The cDNA analysis of
both the MEVs have shown high expression tendency in mammalian host cell line
(human).</p></sec><sec><title>Conclusion</title><p>After multistage in silico analysis, both the MEVs are predicted to elicit humoral as
well as cell mediated immune response. Epitopes of the designed MEVs are predicted to
cover large human population worldwide. Hence both the designed MEVs could be tried in
vivo as potential vaccine candidates against MERS.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Assiri, A" uniqKey="Assiri A">A Assiri</name></author><author><name sortKey="Mcgeer, A" uniqKey="Mcgeer A">A McGeer</name></author><author><name sortKey="Perl, Tm" uniqKey="Perl T">TM Perl</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Oboho, Ik" uniqKey="Oboho I">IK Oboho</name></author><author><name sortKey="Tomczyk, Sm" uniqKey="Tomczyk S">SM Tomczyk</name></author><author><name sortKey="Al Asmari, Am" uniqKey="Al Asmari A">AM Al-Asmari</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Park, Jw" uniqKey="Park J">JW Park</name></author><author><name sortKey="Lee, Kj" uniqKey="Lee K">KJ Lee</name></author><author><name sortKey="Lee, Kh" uniqKey="Lee K">KH Lee</name></author></analytic></biblStruct><biblStruct><analytic><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Infect Drug Resist</journal-id><journal-id journal-id-type="iso-abbrev">Infect Drug Resist</journal-id><journal-id journal-id-type="publisher-id">Infection and Drug Resistance</journal-id><journal-title-group><journal-title>Infection and Drug Resistance</journal-title></journal-title-group><issn pub-type="epub">1178-6973</issn><publisher><publisher-name>Dove Medical Press</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">30538505</article-id><article-id pub-id-type="pmc">6254671</article-id><article-id pub-id-type="doi">10.2147/IDR.S175114</article-id><article-id pub-id-type="publisher-id">idr-11-2377</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Research</subject></subj-group></article-categories><title-group><article-title>Structural basis of development of multi-epitope vaccine against Middle East
respiratory syndrome using in silico approach</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Srivastava</surname><given-names>Sukrit</given-names></name><xref ref-type="aff" rid="af1-idr-11-2377">1</xref><xref ref-type="aff" rid="af2-idr-11-2377">2</xref><xref ref-type="corresp" rid="c1-idr-11-2377"></xref></contrib><contrib contrib-type="author"><name><surname>Kamthania</surname><given-names>Mohit</given-names></name><xref ref-type="aff" rid="af1-idr-11-2377">1</xref><xref ref-type="aff" rid="af3-idr-11-2377">3</xref></contrib><contrib contrib-type="author"><name><surname>Singh</surname><given-names>Soni</given-names></name><xref ref-type="aff" rid="af1-idr-11-2377">1</xref></contrib><contrib contrib-type="author"><name><surname>Saxena</surname><given-names>Ajay K</given-names></name><xref ref-type="aff" rid="af2-idr-11-2377">2</xref></contrib><contrib contrib-type="author"><name><surname>Sharma</surname><given-names>Nishi</given-names></name><xref ref-type="aff" rid="af1-idr-11-2377">1</xref></contrib></contrib-group><aff id="af1-idr-11-2377"><label>1</label>Department of Biotechnology, Mangalayatan University, Aligarh, India,<email>srivastav.sukrit@gmail.com</email></aff><aff id="af2-idr-11-2377"><label>2</label>Molecular Medicine Lab, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India,<email>srivastav.sukrit@gmail.com</email></aff><aff id="af3-idr-11-2377"><label>3</label>Department of Biotechnology, Faculty of Life Sciences, Institute of Applied Medicines and Research, Ghaziabad, Uttar Pradesh, India</aff><author-notes><corresp id="c1-idr-11-2377">Correspondence: Sukrit Srivastava, Department of Biotechnology,
Mangalayatan University, Aligarh, Uttar Pradesh 202146, India, Email
<email>srivastav.sukrit@gmail.com</email></corresp></author-notes><pub-date pub-type="collection"><year>2018</year></pub-date><pub-date pub-type="epub"><day>21</day><month>11</month><year>2018</year></pub-date><volume>11</volume><fpage>2377</fpage><lpage>2391</lpage><permissions><copyright-statement>© 2018 Srivastava et al. This work is published and licensed by
Dove Medical Press Limited</copyright-statement><copyright-year>2018</copyright-year><license><license-p>The full terms of this license are available at <ext-link ext-link-type="uri" xlink:href="https://www.dovepress.com/terms.php">https://www.dovepress.com/terms.php</ext-link> and incorporate the Creative Commons
Attribution – Non Commercial (unported, v3.0) License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/3.0/">http://creativecommons.org/licenses/by-nc/3.0/</ext-link>). By accessing the work you
hereby accept the Terms. Non-commercial uses of the work are permitted without any further
permission from Dove Medical Press Limited, provided the work is properly attributed.</license-p></license></permissions><abstract><sec><title>Background</title><p>Middle East respiratory syndrome (MERS) is caused by MERS coronavirus (MERS-CoV). Thus
far, MERS outbreaks have been reported from Saudi Arabia (2013 and 2014) and South Korea
(2015). No specific vaccine has yet been reported against MERS.</p></sec><sec><title>Purpose</title><p>To address the urgent need for an MERS vaccine, in the present study, we have designed
two multi-epitope vaccines (MEVs) against MERS utilizing several in silico methods and
tools.</p></sec><sec><title>Methods</title><p>The design of both the multi-epitope vaccines (MEVs) are composed of cytotoxic T
lymphocyte (CTL) and helper T lymphocyte (HTL) epitopes, screened form thirteen
different proteins of MERS-CoV. Both the MEVs also carry potential B-cell linear epitope
regions, B-cell discontinuous epitopes as well as interferon-γ-inducing
epitopes. Human β-defensin-2 and β-defensin-3 were used as adjuvants to
enhance the immune response of MEVs. To design the MEVs, short peptide molecular linkers
were utilized to link screened most potential CTL epitopes, HTL epitopes and the
adjuvants. Tertiary models for both the MEVs were generated, refined, and further
studied for their molecular interaction with toll-like receptor 3. The cDNAs of both
MEVs were generated and analyzed in silico for their expression in a mammalian host cell
line (human).</p></sec><sec><title>Results</title><p>Screened CTL and HTL epitopes were found to have high propensity for stable molecular
interaction with HLA alleles molecules. CTL epitopes were also found to have favorable
molecular interaction within the cavity of transporter associated with antigen
processing. The selected CTL and HTL epitopes jointly cover upto 94.0% of worldwide
human population. Both the CTL and HTL MEVs molecular models have shown to have stable
binding and complex formation propensity with toll-like receptor 3. The cDNA analysis of
both the MEVs have shown high expression tendency in mammalian host cell line
(human).</p></sec><sec><title>Conclusion</title><p>After multistage in silico analysis, both the MEVs are predicted to elicit humoral as
well as cell mediated immune response. Epitopes of the designed MEVs are predicted to
cover large human population worldwide. Hence both the designed MEVs could be tried in
vivo as potential vaccine candidates against MERS.</p></sec></abstract><kwd-group><title>Keywords</title><kwd>Middle East respiratory syndrome</kwd><kwd>MERS</kwd><kwd>Middle East respiratory syndrome coronavirus</kwd><kwd>MERS-CoV</kwd><kwd>human transporter associated with antigen processing</kwd><kwd>TAP</kwd><kwd>toll-like receptor 3</kwd><kwd>TLR-3</kwd><kwd>epitope</kwd><kwd>immunoinformatics</kwd><kwd>molecular docking</kwd><kwd>molecular dynamics simulation</kwd><kwd>MD simulation</kwd><kwd>multi-epitope vaccine</kwd></kwd-group></article-meta></front><body><sec sec-type="intro"><title>Introduction</title><p>Middle East respiratory syndrome (MERS) is a respiratory disease caused by Middle East
respiratory syndrome coro-navirus (MERS-CoV). MERS involves high fever, cough, difficulty in
breathing, chills, chest pain, body aches, sore throat, diarrhea, nausea/vomiting, running
nose, renal failure, and pneumonia. The first case of MERS in humans was reported in Saudi
Arabia in 2012. After 2012, within a span of only 4 years, MERS-CoV infection was reported
from 27 countries.<xref rid="b1-idr-11-2377" ref-type="bibr">1</xref> Three MERS outbreaks
have already occurred in Saudi Arabia (2013 and 2014) and South Korea (2015).<xref rid="b2-idr-11-2377" ref-type="bibr">2</xref>–<xref rid="b4-idr-11-2377" ref-type="bibr">4</xref> The outbreak reported in South Korea also involved spread of
MERS through hospital-to-hospital transit of patients and had the fatality rate as high as
40%. High attack rate and easy spread of MERS indicate an epidemic risk.<xref rid="b5-idr-11-2377" ref-type="bibr">5</xref>–<xref rid="b7-idr-11-2377" ref-type="bibr">7</xref> To date, no specific vaccine is available for MERS. The
steep increase in MERS cases and its high mortality rate demand an urgent need for specific
and safe MERS vaccine. Thus far, only little information is known about the pathogenesis of
MERS-CoV. Hence, an immunoinformatics approach to thoroughly study and screen immunogenic
proteins from the available proteome sequence data of MERS-CoV is essential for vaccine
design.</p><p>The proteome of MERS-CoV consists of several important vaccine candidate and drug target
proteins. These proteins are involved in infection and pathogenesis of MERS-CoV to human
host cells. Spike (S) glycoprotein, in particular, its receptor-binding domain, is involved
in virus and host cell interaction.<xref rid="b8-idr-11-2377" ref-type="bibr">8</xref>Envelope (E) protein plays an important role in host cell recognition.<xref rid="b9-idr-11-2377" ref-type="bibr">9</xref> Nucleocapsid (N) protein is involved in RNA binding during
ribonucleocapsid formation by MERS-CoV.<xref rid="b10-idr-11-2377" ref-type="bibr">10</xref>Membrane (M) protein has interferon (IFN)-antagonizing properties, thus reducing IFN levels
in infected patients.<xref rid="b11-idr-11-2377" ref-type="bibr">11</xref> Open reading
frame (ORF) proteins also play critical roles in viral infection and pathogenesis. A
mutation study of ORFs (ORF3, ORF4a, ORF4b, and ORF5) indicated that ORFs have major
implications in viral infection involving disruption of host cell processes, dysregulated
IFN pathway activation, and abrupt inflammation.<xref rid="b12-idr-11-2377" ref-type="bibr">12</xref> Proteins ORF1a (4P16) and ORF1ab (4WUR) are papain-like proteases (PL(pro))
involved in viral infection and are potential targets for the development of antiviral
drugs.<xref rid="b13-idr-11-2377" ref-type="bibr">13</xref> PL(pro) facilitate infection
by their proteolytic, deubiquitinating, and deISGylating activities suppressing innate
immune response from the host cell. Protein ORF1a (4RSP), a protease (3CLpro), facilitates
proteolytic activity during viral infection and replication.<xref rid="b14-idr-11-2377" ref-type="bibr">14</xref>,<xref rid="b15-idr-11-2377" ref-type="bibr">15</xref>Protein ORF1ab (5WWP) is a helicase protein of MERS-CoV, and it is one of the most conserved
proteins among nidoviruses. Protein ORF8b is a highly conserved protein, and during
infection, it induces various immune responses.<xref rid="b16-idr-11-2377" ref-type="bibr">16</xref></p><p>In the present study, we propose two multi-epitope vaccine (MEV) designs for MERS. The
proposed MEVs are composed of cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL)
epitopes. Both CTL and HTL MEVs contain overlapping regions of linear B-cell epitopes. Both
MEVs also contain human β-defensin-2 (hBD-2) and human β-defensin-3 (hBD-3)
as adjuvants to enhance the immunogenic response.<xref rid="b17-idr-11-2377" ref-type="bibr">17</xref>,<xref rid="b18-idr-11-2377" ref-type="bibr">18</xref></p></sec><sec><title>Methodology</title><p>To design the MEVs, different in silico tools were used to screen potential CTL, HTL, and
B-cell epitopes from 13 MERS-CoV proteins that are involved in virus–host
interaction and viral proliferation. All three types of epitopes were studied for
overlapping consensus regions. CTL and HTL epitopes showing partial or complete overlapping
regions with all or any of the three kinds of epitopes and the epitopes with the highest
number of human leukocyte antigen (HLA) allele binders were selected for detailed analysis.
The selected CTL and HTL epitopes were further validated for their molecular interaction
with their HLA allele binders. Furthermore, the selected CTL epitopes were validated for
their molecular interaction with cavity of transporter associated with antigen processing
(TAP) to analyze their smooth passage from the cytoplasm to the endoplasmic reticulum (ER)
lumen.<xref rid="b19-idr-11-2377" ref-type="bibr">19</xref> Three-dimensional (3D)
structure model for both MEVs was generated, refined, validated, and analyzed for different
physiochemical properties. Both CTL and HTL MEV models were further screened to have several
B-cell discontinuous epitopes and IFN-γ-inducing epitopes. Because the immune system
broadly recognizes pathogens partially due to the involvement of toll-like receptor 3
(TLR-3) and its signaling cascade, both CTL and HTL MEVs were further studied for their
molecular interaction with TLR-3.<xref rid="b20-idr-11-2377" ref-type="bibr">20</xref>,<xref rid="b21-idr-11-2377" ref-type="bibr">21</xref> Moreover, the cDNAs of both MEVs were
analyzed and were predicted to be highly expressing in a mammalian host cell line (human)
(<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Figure S1</ext-link>).</p><sec><title>MERS-CoV proteins chosen for MEV preparation</title><p>For vaccine development, proteins critically involved in virus–host cell
interaction, viral proliferation, and host cell disruption were chosen. Thirteen proteins
of MERS-CoV proteome chosen for epitope screening included the following: S glycoprotein;
E protein; N protein; M protein; ORFs (ORF3, ORF4a, ORF4b, and ORF5); ORF1a (4P16), a
papain-like protease (PL(pro)); ORF1a (4RSP), a protease (3CLpro); ORF1ab (4WUR), a
PL(pro); ORF1ab (5WWP); and ORF8b. For sequence-based epitope screening, full-length
protein sequences of the abovementioned MERS-CoV proteins were retrieved from the NCBI
database (National Center for Biotechnology Information, <ext-link ext-link-type="uri" xlink:href="https://www.ncbi.nlm.nih.gov/protein">https://www.ncbi.nlm.nih.gov/protein</ext-link>). A total of 2,499 amino acid sequences
belonging to different proteins of MERS-CoV of different strains and origins were
retrieved. For structure-based epitope screening, available 3D structures of MERS-CoV
proteins were retrieved from Protein Data Bank (PDB, <ext-link ext-link-type="uri" xlink:href="http://www.rcsb.org/pdb/home/home.do">http://www.rcsb.org/pdb/home/home.do</ext-link>). For the proteins with no structure
available in PDB, homology modeling was performed using the Swiss-model, (<ext-link ext-link-type="uri" xlink:href="http://swissmodel.expasy.org/">http://swissmodel.expasy.org/</ext-link>) (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S1</ext-link>).<xref rid="b22-idr-11-2377" ref-type="bibr">22</xref></p></sec></sec><sec><title>Screening of potential epitopes</title><sec><title>T-cell epitope prediction</title><sec><title>Screening of CTL epitope</title><p>To screen CTL epitopes, the Immune Epitope Database (IEDB) tool “Proteasomal
cleavage/TAP transport/MHC class I combined predictor” (<ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/processing/">http://tools.iedb.org/processing/</ext-link>) was used.<xref rid="b23-idr-11-2377" ref-type="bibr">23</xref>–<xref rid="b25-idr-11-2377" ref-type="bibr">25</xref> The total score generated by the tool is a combined score of proteasome,
TAP (N-terminal interaction), major histocompatibility complex (MHC), and processing
analysis scores. The score is generated using the combination of six methods, namely,
Consensus, NN-align, SMM-align, Combinatorial Library, Sturniolo, and NetMHCIIpan. The
IC50 (nM) value was also obtained using this IEDB tool. Epitopes with high,
intermediate, and least affinity of binding to an HLA allele have IC50 values
<50 nM, <500 nM, and <5,000 nM, respectively. Immunogenicity of
the screened CTL epitopes was also obtained by the “MHC I
Immunogenicity” tool of IEDB (<ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/immunogenicity/">http://tools.iedb.org/immunogenicity/</ext-link>) with all parameters set to default
(first, second, and C-terminus amino acids).<xref rid="b26-idr-11-2377" ref-type="bibr">26</xref> The tool predicts immunogenicity of a peptide MHC complex on the basis of
physiochemical properties of amino acids and their position within the short peptide
sequence.</p></sec><sec><title>Screening of HTL epitopes</title><p>To screen HTL epitopes, the IEDB tool “MHC-II Binding Predictions”
(<ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/mhcii/">http://tools.iedb.org/mhcii/</ext-link>) was used. The percentile rank for each
peptide is generated by the combination of three methods (Combinatorial Library,
SMM-align, and Sturniolo) by comparing the score of peptide against the scores of other
random five million 15-mer peptides from the SwissProt database.<xref rid="b27-idr-11-2377" ref-type="bibr">27</xref>–<xref rid="b30-idr-11-2377" ref-type="bibr">30</xref> The rank for the Consensus method was generated by the median percentile
rank of the three methods.</p></sec><sec><title>Population coverage by CTL and HTL epitopes</title><p>The “Population Coverage” tool of IEDB (<ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/population/">http://tools.iedb.org/population/</ext-link>) was used to analyze the world human
population coverage by the shortlisted 28 CTL and 28 HTL epitopes.<xref rid="b31-idr-11-2377" ref-type="bibr">31</xref> Use of multi-epitopes involving both CTL and HTL
epitopes would have the higher probability of larger human population coverage
worldwide.</p></sec><sec><title>B-cell epitope prediction</title><sec><title>Sequence-based B-cell epitope prediction</title><p>Protein sequence-based linear B-cell epitopes were predicted by six different
prediction methods available at “B Cell Epitope Prediction Tools” tool
of IEDB server (<ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/bcell/">http://tools.iedb.org/bcell/</ext-link>); these tools are based
on the propensity scale method and physicochemical properties of the antigenic
sequence. These methods include “BepiPred Linear Epitope Prediction”
(propensity scale method such as hidden Markov model), “Chou & Fasman
Beta-Turn Prediction”, “Emini Surface Accessibility
Prediction”, “Karplus & Schulz Flexibility
Prediction”, “Kolaskar & Tongaonkar Antigenicity”, and
“Parker Hydrophilicity Prediction”.<xref rid="b32-idr-11-2377" ref-type="bibr">32</xref>–<xref rid="b37-idr-11-2377" ref-type="bibr">37</xref></p></sec><sec><title>Structure-based B-cell epitope prediction</title><p>Two structure-based B-cell epitope prediction methods, namely, DiscoTope 2.0
(Structure-based Antibody Prediction tool; <ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/discotope/">http://tools.iedb.org/discotope/</ext-link>) and Ellipro (Antibody Epitope
Prediction tool; <ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/ellipro/">http://tools.iedb.org/ellipro/</ext-link>), available in IEDB,
were used for linear and discontinuous B-cell epitope prediction.<xref rid="b38-idr-11-2377" ref-type="bibr">38</xref>,<xref rid="b39-idr-11-2377" ref-type="bibr">39</xref> The ElliPro method is based on the location of the residue in the
protein’s 3D structure. The residues lying outside of the ellipsoid covering
90% of the inner core residues of the protein score highest protrusion index (PI) of
0.9 and so on. Discontinuous epitopes predicted by ElliPro are clustered on the basis
of distance R in Å between two residues’ centers of mass lying outside
the largest possible ellipsoid. The larger the value of R, the larger will be the
number of discontinuous epitopes clustered. DiscoTope 2.0 is based on the number of
contacts of the residues’ Cα carbon atom with other Cα carbon
atoms in the 3D structure within the 10 Å distance and the propensity of a
residue to be a part of an epitope.</p></sec></sec></sec><sec><title>Characterization of potential epitopes</title><sec sec-type="methods"><title>Epitope conservation analysis</title><p>Shortlisted CTL, HTL, and B-cell epitopes were subjected to conservancy analysis by the
“Epitope Conservancy Analysis” tool (<ext-link ext-link-type="uri" xlink:href="http://tools.iedb.org/conservancy/">http://tools.iedb.org/conservancy/</ext-link>) of IEDB among all their respective
source protein sequences of MERS-CoV retrieved from the NCBI protein database.<xref rid="b40-idr-11-2377" ref-type="bibr">40</xref></p></sec><sec><title>Epitope toxicity prediction</title><p>Toxicity assessment of CTL and HTL epitopes and B-cell epitopes was performed by
ToxinPred (<ext-link ext-link-type="uri" xlink:href="http://crdd.osdd.net/raghava/toxinpred/multi_submit.php">http://crdd.osdd.net/raghava/toxinpred/multi_submit.php</ext-link>) analysis. This
analysis allows to identify highly toxic or nontoxic peptides. The analysis was
performed by the “support vector machine (SVM) (SwissProt)-based” method
with all the parameters set to default.<xref rid="b41-idr-11-2377" ref-type="bibr">41</xref></p></sec><sec sec-type="methods"><title>Overlapping residue analysis</title><p>Multiple Sequence Alignment (MSA) analysis using the Clustal Omega tool (<ext-link ext-link-type="uri" xlink:href="https://www.ebi.ac.uk/Tools/msa/clustalo/">https://www.ebi.ac.uk/Tools/msa/clustalo/</ext-link>) of European Bioinformatics
Institute was performed for all the shortlisted CTL, HTL, and B-cell epitopes from 13
MERS-CoV proteins.<xref rid="b42-idr-11-2377" ref-type="bibr">42</xref> MSA by Clustal
Omega virtually aligns any number of protein sequences and delivers accurate
alignments.</p></sec><sec sec-type="methods"><title>Epitope selected for molecular interaction study with HLA allele and TAP</title><p>CTL and HTL epitopes were shortlisted for further in silico analysis on the basis of
their overlapping sequence regions among all three types of epitopes (CTL, HTL, and
B-cell) or complete overlap among any two types of epitopes or the highest number of HLA
allele binders.</p></sec></sec><sec sec-type="methods"><title>Molecular interaction analysis of the selected epitopes with HLA alleles</title><sec><title>Tertiary structure modeling of HLA alleles and selected T-cell epitopes</title><p>Template-based homology modeling for HLA class I and II allele binders of the
shortlisted epitopes was performed by the Swiss-model.<xref rid="b22-idr-11-2377" ref-type="bibr">22</xref> Protein sequences of HLA class I and II alleles were
retrieved from Immuno Polymorphism Database (IPD-IMGT/HLA) (<ext-link ext-link-type="uri" xlink:href="https://www.ebi.ac.uk/ipd/imgt/hla/allele.html">https://www.ebi.ac.uk/ipd/imgt/hla/allele.html</ext-link>).<xref rid="b69-idr-11-2377" ref-type="bibr">69</xref> Template with high sequence identity was chosen for
modeling, and the models thus generated were validated for quality by the Qualitative
Model Energy ANalysis (QMEAN) analysis. The QMEAN value is a composite (both global and
local [ie, per residue] structure) quality estimate of the generated
model.<xref rid="b43-idr-11-2377" ref-type="bibr">43</xref> Models with an acceptable
QMEAN value with a cutoff of −4.0 were chosen for further studies (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S2</ext-link>).</p><p>“Natural Peptides Module for Beginners” module of the PEPstrMOD tool
(<ext-link ext-link-type="uri" xlink:href="http://osddlinux.osdd.net/raghava/pepstrmod/nat_ss.php">http://osddlinux.osdd.net/raghava/pepstrmod/nat_ss.php</ext-link>)
was used to generate tertiary structures of the selected epitopes.<xref rid="b44-idr-11-2377" ref-type="bibr">44</xref> Prediction was carried out with a simulation time
window of 100 ps, and the peptide environment was set to vacuum.</p></sec><sec sec-type="methods"><title>Molecular docking and molecular dynamics (MD) simulation study of the selected
epitopes with HLA alleles</title><p>AutoDock Tool 4.2 and AutoDock Vina were used for molecular docking study of the
selected epitopes and their respective HLA allele binders.<xref rid="b45-idr-11-2377" ref-type="bibr">45</xref>,<xref rid="b46-idr-11-2377" ref-type="bibr">46</xref>Further, the docked complexes were subjected to MD simulation study by Gromacs 5.1.4
using Optimized Potentials for Liquid Simulations – all atom (OPLS-AA) force
field.<xref rid="b47-idr-11-2377" ref-type="bibr">47</xref>,<xref rid="b48-idr-11-2377" ref-type="bibr">48</xref></p></sec><sec sec-type="methods"><title>Molecular interaction analysis (docking) of the selected CTL epitopes with
TAP</title><p>Molecular docking study of the shortlisted CTL epitopes with TAP receptor was performed
by AutoDock Vina.<xref rid="b45-idr-11-2377" ref-type="bibr">45</xref>,<xref rid="b46-idr-11-2377" ref-type="bibr">46</xref> For more accurate prediction, instead
of homology modeling, the cryo-EM structure of TAP (PDB ID: 5u1d) was used.<xref rid="b49-idr-11-2377" ref-type="bibr">49</xref> For docking, the antigen from the TAP
cavity of the original structure was removed.</p></sec></sec><sec sec-type="methods"><title>Design, characterization, and interaction analysis of MEVs with TLR-3</title><sec sec-type="methods"><title>Design of MEVs</title><p>From the screened and shortlisted CTL and HTL epitopes, two MEVs were designed using
EAAAK and GGGGS as short peptide rigid and flexible linkers, respectively (<xref ref-type="fig" rid="f1-idr-11-2377">Figure 1A and B</xref>). To enhance the immune
response, hBD-2 (PDB ID: 1FD3, sequence: GIGDPVTCLKSGAICHPVFCPRRYKQIGTCG LPGTKCCKKP) and
hBD-3 (PDB ID: 1KJ6, sequence: GII NTLQKYYCRVRGGRCAVLSCLPKEEQIGKCSTRGRK CCRRKK) were
used as adjuvants for both MEVs at N and C terminals, respectively.<xref rid="b17-idr-11-2377" ref-type="bibr">17</xref>,<xref rid="b18-idr-11-2377" ref-type="bibr">18</xref>,<xref rid="b50-idr-11-2377" ref-type="bibr">50</xref>–<xref rid="b53-idr-11-2377" ref-type="bibr">53</xref> Upon lung infection, the expression of
hBD-2 and hBD-3 was found to be increased. β-Defensins are involved in
chemotactic activity for memory T cells, monocytes, and immature dendritic cells as well
as in degranulation of mast cells. Thus, hBDs enhance innate and adaptive immunity and
therefore were chosen here as adjuvants for the design of MEVs.</p></sec><sec><title>IFN-γ-inducing epitope prediction</title><p>IFN-γ epitopes with potential to induce the release of IFN-γ from CD4+
T cells from both MEVs were predicted by “IFNepitope” server (<ext-link ext-link-type="uri" xlink:href="http://crdd.osdd.net/raghava/ifnepitope/scan.php">http://crdd.osdd.net/raghava/ifnepitope/scan.php</ext-link>) using the “Motif
and SVM hybrid” (MERCI: Motif-EmeRging and with Classes-Identification, and SVM)
approach. The tool generates overlapping sequences from the query protein/antigen and
uses it for IFN-γ-inducing epitope prediction. The prediction is based on a
dataset of IFN-γ-inducing and IFN-γ-noninducing MHC class II
binders.<xref rid="b54-idr-11-2377" ref-type="bibr">54</xref>,<xref rid="b55-idr-11-2377" ref-type="bibr">55</xref></p></sec><sec><title>Allergenicity and antigenicity prediction of MEVs</title><p>For both MEVs, AlgPred was used for allergenicity prediction (<ext-link ext-link-type="uri" xlink:href="http://crdd.osdd.net/raghava/algpred/submission.html">http://crdd.osdd.net/raghava/algpred/submission.html</ext-link>).<xref rid="b56-idr-11-2377" ref-type="bibr">56</xref> The AlgPred prediction of allergens is
based on similarity of the known epitope with any region of the submitted protein.
VaxiJen (<ext-link ext-link-type="uri" xlink:href="http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html">http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html</ext-link>) was used to
analyze the probability of antigenicity of both MEVs.<xref rid="b57-idr-11-2377" ref-type="bibr">57</xref> The VaxiJen analysis applies an alignment-free
approach that is solely based on the physicochemical properties of the sequences of the
submitted proteins.</p></sec><sec sec-type="methods"><title>Physicochemical analysis of MEVs</title><p>To analyze the physiochemical properties of CTL and HTL MEVs, ProtParam (<ext-link ext-link-type="uri" xlink:href="https://web.expasy.org/protparam/">https://web.expasy.org/protparam/</ext-link>) was used.<xref rid="b58-idr-11-2377" ref-type="bibr">58</xref> ProtParam analysis performs empirical investigation
for a given protein amino acid sequence.</p></sec><sec><title>3D structure modeling and refinement of MEVs</title><p>Both the CTL and HTL MEVs were further subjected to 3D structure modeling by RaptorX
structure prediction server (<ext-link ext-link-type="uri" xlink:href="http://raptorx.uchicago.edu/StructurePrediction/predict/">http://raptorx.uchicago.edu/StructurePrediction/predict/</ext-link>).<xref rid="b59-idr-11-2377" ref-type="bibr">59</xref> The quality of the generated model is
indicated by its <italic>P</italic>-value. The <italic>P</italic>-value is the
probability of a predicted model being worse than the best. It indicates relative
quality in terms of modeling error by combining global distance test (GDT) and
un-normalized GDT, that is, error at each residue. The smaller the
<italic>P</italic>-value, the higher is the quality of the predicted model.</p><p>The generated MEV models were further refined by ModRefiner and GalaxyRefin.<xref rid="b60-idr-11-2377" ref-type="bibr">60</xref>,<xref rid="b70-idr-11-2377" ref-type="bibr">70</xref> GalaxyRefine performs repeated structure perturbation
along with subsequent structural relaxation by dynamics simulation to refine a protein
structure. To avoid breaks in model structures, GalaxyRefine uses the triaxial loop
closure method.</p></sec><sec><title>In silico validation of refined MEV models</title><p>The refined 3D models of both MEVs were then subjected to RAMPAGE analysis for
generating a Ramachandran plot (<ext-link ext-link-type="uri" xlink:href="http://mordred.bioc.cam.ac.uk/~rapper/rampage.php">http://mordred.bioc.cam.ac.uk/~rapper/rampage.php</ext-link>).<xref rid="b61-idr-11-2377" ref-type="bibr">61</xref> The Ramachandran plot shows the residues that form
energetically allowed and disallowed dihedral angles psi (ψ) and phi
(ϕ), which are calculated on the basis of van der Waal radius of the amino acid
side chain.</p></sec><sec><title>Discontinuous B-cell epitope prediction from MEVs</title><p>Both the designed CTL and HTL MEVs were subjected to discontinuous B-cell epitope
prediction to analyze structure-based humoral immunogenic potential of both MEVs using
the ElliPro tool.<xref rid="b39-idr-11-2377" ref-type="bibr">39</xref></p></sec><sec sec-type="methods"><title>Molecular docking and MD simulation study of MEVs and the immunological receptor
TLR-3</title><p>To study the molecular interaction, the refined models of CTL and HTL MEVs were docked
with TLR-3 by PatchDock server (<ext-link ext-link-type="uri" xlink:href="http://bioinfo3d.cs.tau.ac.il/PatchDock/">http://bioinfo3d.cs.tau.ac.il/PatchDock/</ext-link>).<xref rid="b62-idr-11-2377" ref-type="bibr">62</xref>–<xref rid="b64-idr-11-2377" ref-type="bibr">64</xref> The 3D structure of human TLR-3 ectodomain (ECD) was retrieved from PDB
databank (PDB ID: 2A0Z). To analyze the stable complex formation, both complexes were
subjected to MD simulation by Gromacs 5.1.4 using OPLS-AA.<xref rid="b47-idr-11-2377" ref-type="bibr">47</xref>,<xref rid="b48-idr-11-2377" ref-type="bibr">48</xref></p></sec><sec sec-type="methods"><title>Analysis of cDNAs of both MEVs for cloning and expression</title><p>Optimized cDNAs for both MEVs were generated by the Codon Usage Wrangler Tool with the
option of a mammalian host cell line (human) as the expression system (<ext-link ext-link-type="uri" xlink:href="http://www.mrc-lmb.cam.ac.uk/ms/methods/codon.html">http://www.mrc-lmb.cam.ac.uk/ms/methods/codon.html</ext-link>). Further, the
GenScript Rare Codon Analysis Tool (<ext-link ext-link-type="uri" xlink:href="https://www.genscript.com/tools/rare-codon-analysis">https://www.genscript.com/tools/rare-codon-analysis</ext-link>) was used to analyze
the cDNAs of both MEVs. The tool provides GC content, codon adaptation index (CAI), and
tandem rare codon frequency for cDNA.<xref rid="b65-idr-11-2377" ref-type="bibr">65</xref>–<xref rid="b67-idr-11-2377" ref-type="bibr">67</xref></p></sec></sec></sec><sec sec-type="results|discussion"><title>Results and discussion</title><sec><title>Screening of potential epitopes</title><sec><title>T-cell epitope prediction</title><sec><title>Screening of CTL epitope</title><p>On the basis of “total score” and acceptably low IC50 (nM) value of
epitope-HLA class I allele pairs, 75 CD8+ CTL epitopes were chosen. Later, 28 epitopes
were shortlisted with high scoring and larger number of HLA class I allele binders for
further studies. Immunogenicity of the screened CTL epitopes was also determined. The
higher the immunogenicity score, the greater is the immunogenicity of the epitope
(<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Tables S3</ext-link> and <ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">S4</ext-link>).</p></sec><sec><title>Screening of HTL epitopes</title><p>Screening of HTL epitopes was performed on the basis of “percentile
rank”. Small percentile rank shows the high affinity of the peptide for its
respective HLA allele. Initially, from the 13 MERS-CoV proteins, 70 CD4+ T-cell
epitopes with the highest percentile rank were screened, and 28 epitopes with high
percentile rank and the highest number of HLA class II allele binders were then
shortlisted (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Tables S5</ext-link> and <ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">S6</ext-link>). Several CTL and HTL epitopes predicted in the present study show
overlapping regions with the epitopes detected to induce T-cell responses in previous
studies done using peripheral blood mononuclear cells from infected patients.<xref rid="b68-idr-11-2377" ref-type="bibr">68</xref> Hence, epitopes screened and
reported in the present study could be predicted to originate from the highly
immunogenic stretch of MERS-CoV protein sequences.</p></sec></sec><sec><title>Population coverage by CTL and HTL epitopes</title><p>In this study, most geographical regions of the world, and in particular, the countries
of Middle East, South Asia, East Asia, and Northeast Asia, were included. This study
indicates that the combined use of all shortlisted CTL and HTL epitopes would have an
average worldwide population coverage of 94.0%, with an SD of 20.19 (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S7</ext-link>).</p></sec><sec><title>B-cell epitope prediction</title><sec><title>Sequence-based B-cell epitope prediction</title><p>Initially, a total of 144 B-cell epitopes were screened from 13 MERS-CoV proteins,
with epitope length of four or more than four amino acids by the BepiPred Linear
Epitope Prediction method. The epitopes predicted by five other methods based on
different physicochemical properties showed a significant consensus overlap of amino
acid sequences with that of BepiPred Linear Epitope Prediction. From the 144 B-cell
epitopes, 12 with the length of 4–19 amino acids were shortlisted (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S8</ext-link> and <xref ref-type="fig" rid="f2-idr-11-2377">Figure
2</xref>).</p></sec><sec><title>Structure-based B-cell epitope prediction</title><p>Discontinuous and linear epitopes predicted by DiscoTope 2.0 and Ellipro methods
showed significant consensus overlap of amino acid sequence with the linear epitopes
predicted by the BepiPred linear epitope method (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S8</ext-link> and <xref ref-type="fig" rid="f2-idr-11-2377">Figure 2</xref>).
This result confirms that the shortlisted BepiPred linear epitopes are highly
immunogenic B-cell epitopes.</p></sec></sec></sec><sec><title>Characterization of potential epitopes</title><sec sec-type="methods"><title>Epitope conservation analysis</title><p>The conservation analysis of shortlisted 28 CTL, 28 HTL, and 12 B-cell epitopes shows
that amino acid sequence conservancy of CTL epitopes varied from 72.7% to 100%, that of
HTL epitopes varied from (50% for two epitopes) 68.18% to 100%, and that of B-cell
epitopes varied from 85.71% to 99.26% (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Tables S3</ext-link>, <ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">S5</ext-link>, and <ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">S8</ext-link>). This result indicates high conservancy nature of the shortlisted CTL,
HTL, and B-cell epitopes.</p></sec><sec><title>Epitope toxicity prediction</title><p>All the shortlisted CTL, HTL, and B-cell epitopes analyzed by the ToxinPred tool were
predicted to be nontoxic (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Tables S3</ext-link>, <ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">S5</ext-link>, and <ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">S8</ext-link>). The analysis was based on the ToxinPred main dataset consisting of
1,805 toxic peptides for its prediction.</p></sec><sec sec-type="methods"><title>Overlapping residue analysis</title><p>MSA analysis of all the screened CTL, HTL, and B-cell epitopes from the 13 MERS-CoV
protein candidates revealed that several epitopes of CTL, HTL, and B-cell have
overlapping amino acid sequence regions. Epitopes with two or more than two residues in
the overlapping region are shown in <xref ref-type="fig" rid="f3-idr-11-2377">Figure
3</xref>.</p></sec><sec sec-type="methods"><title>Epitope selected for molecular interaction study with HLA allele and TAP</title><p>Overlapping CTL and HTL epitopes clustering with all three (CTL, HTL, and B-cell) types
of epitopes or with complete epitope sequence overlap or with the highest number of HLA
allele binders were identified and selected for their molecular interaction analysis
with HLA alleles and TAP (<xref ref-type="fig" rid="f3-idr-11-2377">Figure 3</xref>).
These include CTL epitopes:<xref rid="b47-idr-11-2377" ref-type="bibr">47</xref>AQADTAGLY,<xref rid="b31-idr-11-2377" ref-type="bibr">31</xref>,<xref rid="b55-idr-11-2377" ref-type="bibr">55</xref> FTYIPASGY,<xref rid="b25-idr-11-2377" ref-type="bibr">25</xref>,<xref rid="b39-idr-11-2377" ref-type="bibr">39</xref> STDSIVFTY,<xref rid="b33-idr-11-2377" ref-type="bibr">33</xref>,<xref rid="b58-idr-11-2377" ref-type="bibr">58</xref> SMKMAPLMLL,<xref rid="b14-idr-11-2377" ref-type="bibr">14</xref>,<xref rid="b67-idr-11-2377" ref-type="bibr">67</xref> VTVDGVNFR,<xref rid="b22-idr-11-2377" ref-type="bibr">22</xref>,<xref rid="b51-idr-11-2377" ref-type="bibr">51</xref> and LVQPALYLY;<xref rid="b59-idr-11-2377" ref-type="bibr">59</xref> and HTL epitopes:<xref rid="b52-idr-11-2377" ref-type="bibr">52</xref> AGLYTNFRIDVPSAE,<xref rid="b36-idr-11-2377" ref-type="bibr">36</xref>,<xref rid="b66-idr-11-2377" ref-type="bibr">66</xref>ASGYVAALAVNVCLI,<xref rid="b11-idr-11-2377" ref-type="bibr">11</xref>,<xref rid="b50-idr-11-2377" ref-type="bibr">50</xref> EVLVTVDGVNFRTVV,<xref rid="b25-idr-11-2377" ref-type="bibr">25</xref>,<xref rid="b58-idr-11-2377" ref-type="bibr">58</xref>SMKMAPLMLLQLLGR,<sup>72,117</sup> and FLRNVRFELHEFALL.<sup>131</sup></p></sec></sec><sec sec-type="methods"><title>Molecular interaction analysis of the selected epitopes with HLA allele</title><sec sec-type="methods"><title>Molecular docking and MD simulation study of the selected epitopes with HLA
alleles</title><p>Molecular docking study of all the selected epitopes with their respective HLA allele
binders revealed a significantly favorable molecular interaction. Docking complexes thus
formed have significantly negative binding energy, and several amino acid residues of
epitopes and HLA alleles were involved in hydrogen bond formation (<xref ref-type="fig" rid="f4-idr-11-2377">Figure 4</xref>). To analyze the stability of binding, docking
complexes were further subjected to MD simulation study with an analysis time window of
0.1 ns at the reasonably invariable temperature (~300 K) and pressure (~1 bar). The
results of MD simulation for all the epitope-HLA allele complexes showed a very
convincing reasonably invariant root mean square deviation (RMSD) value between ~0.1 and
0.2 nm, thus indicating stable complex formation (<xref ref-type="fig" rid="f5-idr-11-2377">Figure 5</xref>). Moreover, the reasonably invariant radius of
gyration (Rg) of the complexes (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Figure S2</ext-link>) and RMS fluctuation (RMSF) for all the atoms in the complexes
(<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Figure S3</ext-link>) indicate that the epitope-HLA complexes remain very stable in
their folded form. B-factor of the epitope and HLA allele complexes is shown in the
rainbow color presentation in <ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Figure S4</ext-link>. Most of the regions of the complexes are stable (blue) with a
very small region being acceptably fluctuating (yellow and orange).</p></sec></sec><sec sec-type="methods"><title>Molecular interaction analysis (docking) of the selected CTL epitopes with
TAP</title><p>Molecular docking results show a favorable molecular interaction between the selected CTL
epitopes and the TAP cavity. The result reveals several molecular interaction sites for
the selected epitopes within the TAP cavity. Two sites of interaction—one close to
the cytoplasm and another close to the ER lumen—are shown in <xref ref-type="fig" rid="f6-idr-11-2377">Figure 6</xref>. All the interactions showed a significantly
negative binding energy with one or more than one hydrogen bond formation at both sites of
interaction. From this study, we may predict a smooth passage for selected CTL epitopes
from the cytoplasm to the ER lumen throughout the entire passage of the TAP cavity (<xref ref-type="fig" rid="f6-idr-11-2377">Figure 6</xref>).</p></sec><sec sec-type="methods"><title>Characterization and interaction analysis of designed MEVs with TLR-3</title><sec><title>IFN-γ-inducing epitope prediction</title><p>IFN-γ is involved in both adaptive and innate immune responses. It stimulates
macrophages and natural killer cells. IFN-γ-inducing 15-mer peptide epitopes
were predicted from both CTL and HTL MEVs by IFNepitope server. A total of 486 and 640
IFN-γ epitopes were predicted from CTL and HTL MEVs, respectively. Out of these,
35 CTL MEVs and 18 HTL MEVs, IFN-γ-inducing POSITIVE epitopes, with score of one
or more than one were chosen (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S9</ext-link> and <xref ref-type="fig" rid="f7-idr-11-2377">Figure 7C and
G</xref>).</p></sec><sec><title>Allergenicity and antigenicity prediction of MEVs</title><p>The AlgPred analysis of CTL and HTL MEVs revealed that both MEVs are nonallergens with
the score of −0.95415008 and −0.8647714, respectively, with sensitivity
and specificity of 88.87% and 81.86%, respectively, while the default threshold value
was −0.4. The VaxiJen analysis indicated both MEVs to be probable ANTIGENS with
prediction score of 0.5302 and 0.5097 for CTL MEVs and HTL MEVs, respectively, while the
default threshold value was 0.4 for viral proteins. Hence, both MEVs are predicted to be
nonallergic and potentially antigenic in nature.</p></sec><sec sec-type="methods"><title>Physicochemical analysis of MEVs</title><p>ProtParam analysis showed that CTL MEVs have 500 amino acids, 50.4 kDa molecular
weight, and 9.72 theoretical pI. The half-life in mammalian reticulocytes, yeast, and
<italic>Escherichia coli</italic> was 30 hours, 20 hours, and 10 hours, respectively;
aliphatic index was 61.68, and grand average of hydropathicity (GRAVY) was
−0.020, indicating globular and hydrophilic nature of CTL MEVs; the instability
index was 50.70, indicating that CTL MEVs are theoretically close to stable in nature.
ProtParam study showed HTL MEV has 657 amino acids, 67.583 kDa molecular weight, and
9.29 theoretical pI. The half-life in mammalian reticulocytes, yeast, and <italic>E.
coli</italic> was 30 hours, 20 hours, and 10 hours, respectively; aliphatic index was
94.22, and grand average of hydropathicity (GRAVY) was 0.337, both indicating globular
and hydrophilic nature of HTL MEV; the instability index was 37.66, indicating
theoretically stable nature of HTL MEV.</p></sec><sec><title>3D structure modeling and refinement of MEVs</title><p>The model generated by RaptorX for CTL MEV has 4% helix, 37% β-sheet, and 58%
coil; the model is 26% exposed, 41% medium, and 31% buried. It has three domains: first
domain (1–46 aa, template-1fd3:A); second domain (47–444 aa,
template-4dou:A, 4zch:A); and third domain (445–500 aa, template-1kj6:A) (<xref ref-type="fig" rid="f7-idr-11-2377">Figure 7A</xref>). The model generated by RaptorX
for HTL MEV has 35% helix, 20% β-sheet, and 44% coil; the model is 26% exposed,
35% medium, and 37% buried. It has four domains: first domain (1–46 aa,
template-1fd3:A); second domain (47–546 aa, templates-4ufcA, 2eabA, and 2rdyA);
third domain (547–601 aa, template-1tue:B); and fourth domain (602–657
aa, template-1kj6:A) (<xref ref-type="fig" rid="f7-idr-11-2377">Figure 7E</xref>). The
<italic>P</italic>-values of the best template of CTL and HTL MEV models are 3.98e-05
and 5.41e-04, respectively. Good quality alpha proteins and good quality beta proteins
should have <italic>P</italic>-value of less than 10<sup>−3</sup> and
10<sup>−4</sup> respectively. Hence, both the models of CTL and HTL MEVs
generated by RaptorX are of good quality. Because the CTL and HTL epitopes used for the
design of both MEVs show overlapping with B-cell linear epitopes (<xref ref-type="fig" rid="f3-idr-11-2377">Figure 3</xref>), both the CTL and HTL MEV models also carry
overlapping regions of B-cell linear epitopes (<xref ref-type="fig" rid="f7-idr-11-2377">Figure 7B and F</xref>).</p><p>The structural accuracy of initial model including joining of the gaps was performed by
ModRefiner refinment. Galaxy-Refine was used to further refine the 3D models of CTL and
HTL MEVs. For both MEVs, refined model 1 was chosen on the basis of best scorings. For
CTL MEV refinement, the score of model 1 was as follows: Rama favored was 94.2%, GDT-HA
was 0.9500, RMSD was 0.433, MolProbity was 2.211, Clash score was 18.3, and Poor
rotamers was 1.2. For HTL MEV refinement, the score of model 1 was as follows: Rama
favored was 93.4%, GDT-HA was 0.9502, RMSD was 0.412, MolProbity was 2.262, Clash score
was 21.9, and Poor rotamers was 0.6. Here, MolProbity is the log-weighted combination of
clash score, percentage Ramachandran not favored, and percentage bad side-chain
rotamers. After refinement, all the mentioned parameters improved significantly as
compared to those of the initial model (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S10</ext-link>).</p></sec><sec><title>In silico validation of refined MEV models</title><p>The RAMPAGE analysis showed that the refined CTL MEV model has 94% residues in the
favored region, 3.8% residues in the allowed region, and only 1.4% residues in the
outlier region, while the refined HTL MEV model has 94% of residues in the favored
region, 5.2% residues in the allowed region, and only 0.8% residues in the outlier
region (<xref ref-type="fig" rid="f7-idr-11-2377">Figure 7D and H</xref>).</p></sec><sec><title>Discontinuous B-cell epitope prediction from MEVs</title><p>Discontinuous B-cell epitope prediction from both MEVs was performed by the ElliPro
tool. The screening revealed CTL MEV to have six discontinuous epitopes and HTL MEV to
have five discontinuous epitopes. The PI score for CTL MEV epitopes ranged from 0.549 to
0.906 and that for HTL MEV ranged from 0.56 to 0.729 (<ext-link ext-link-type="uri" xlink:href="https://drive.google.com/file/d/1h-ubHe0O8ogxDj1JWSVw6itOaE88XshB/view?usp=sharing">Table S11</ext-link> and <xref ref-type="fig" rid="f7-idr-11-2377">Figure 7C and
G</xref>). The higher the score, the greater is the potential of the B-cell
discontinuous epitope.</p></sec><sec sec-type="methods"><title>Molecular docking and MD simulation study of MEVs and the immunological receptor
TLR-3</title><p>The refined models of CTL and HTL MEVs were further analyzed for their interaction with
the ECD of human TLR-3 by molecular docking using the PatchDock tool. Docking
conformation chosen for the CTL and HTL MEVs showed scores of 18,096 and 23,690,
respectively, which were highest among all docked complexes. The highest score indicates
the best geometric shape complementarity fitting of ligand and receptor predicted by the
tool. The docking complex shows a fitting confirmation of both the MEVs within the ECD
of TLR-3 (<xref ref-type="fig" rid="f8-idr-11-2377">Figure 8A and E</xref>). Further,
the MD simulation analysis of the docked CTL-TLR-3 and HTL-TLR-3 complexes showed a very
convincing reasonably stable RMSD value betweeñ0.4 and 0.5 nm for a given time
window of 6 ns at the reasonably invariable temperature (~300 K) and pressure (~1 bar).
These results indicate a stable complex formation for both MEVs with TLR-3 (<xref ref-type="fig" rid="f8-idr-11-2377">Figure 8B and F</xref>). The reasonably invariant
Rg of MEV-TLR-3 complexes (<xref ref-type="fig" rid="f8-idr-11-2377">Figure 8C and
G</xref>) and RMSF for all the atoms in the complexes (<xref ref-type="fig" rid="f8-idr-11-2377">Figure 8D and H</xref>) indicate that both the MEV-TLR-3
complexes are reasonably stable and are properly folded. The B-factor of CTL and HTL MEV
complexes with the TLR-3 receptor is shown by rainbow color presentation in <xref ref-type="fig" rid="f8-idr-11-2377">Figure 8A and E</xref>. Most of the regions of
both complexes are stable (blue) with a very small region being acceptably fluctuating
(yellow and orange).</p></sec><sec sec-type="methods"><title>Analysis of cDNAs of both MEVs for cloning and expression</title><p>Optimized cDNAs for both CTL and HTL MEVs were generated by the Codon Usage Wrangler
Tool with a mammalian host cell line (human) as the choice of the expression system. The
GenScript Rare Codon Analysis Tool showed that the GC content of optimized CTL MEV cDNA
was 69.74% and CAI score was 1.0 with 0% tandem rare codons. Likewise, the GC content of
optimized HTL MEV cDNA was 66.63%, and the CAI score was 1.0 with 0% tandem rare codons.
Ideally, the GC content should be 30%–70%, the CAI score indicating the
possibility of cDNA expression in the chosen expression system should be between 0.8 and
1.0, and tandem rare codon frequency indicating the percentage of low-frequency codons
present in cDNA for the chosen expression system should be <30%. Tandem rare
codons may hinder the expression of cDNA or even interrupt the translational machinery.
Hence, the optimized cDNAs of both MEVs are predicted to be highly expressing in the
mammalian host cell line (human).</p></sec></sec></sec><sec><title>Conclusion</title><p>In this study, we propose the design of two MEVs against MERS-CoV that consisted of CTL and
HTL epitopes. The selected CTL and HTL epitopes were validated by in silico methods for
their molecular interaction with HLA alleles and TAP (for CTL epitopes). The population
coverage by the designed MEVs is as high as 94% of the world population. Both MEVs were
found to contain IFN-γ epitopes and B-cell discontinuous epitopes. Moreover, they
also showed stable interaction with the immunoreceptor TLR-3. On the basis of the design and
in silico validation of both the CTL and HTL MEVs, their joint administration is predicted
to induce humoral and cell-mediated immune response. Codon-based cDNAs of both MEVs are
predicted to have high expression in the mammalian host cell line (human); hence, they could
be cloned and expressed at the laboratory level for in vivo trials on humanized
HLA-expressing mice for further study.</p></sec></body><back><ack><title>Acknowledgments</title><p>The authors acknowledge the Advance Instrumentation Research Facility (AIRF) at Jawaharlal
Nehru University, New Delhi, for providing advance computational facility to conduct
experiments. The current research was also supported by DST-PURSE grant to Jawaharlal Nehru
University.</p></ack><fn-group><fn><p><bold>Author contributions</bold></p><p>S Srivastava and MK designed the protocol and performed the experiments. S Srivastava,
MK, S Singh, AKS, and NS contributed toward data analysis, drafting and revising the
article, gave final approval of the version to be published, and agree to be accountable
for all aspects of the work.</p></fn><fn fn-type="COI-statement"><p><bold>Disclosure</bold></p><p>The authors report no conflicts of interest in this work.</p></fn></fn-group><ref-list><title>References</title><ref id="b1-idr-11-2377"><label>1</label><element-citation publication-type="journal"><source>WHO MERS-CoV Global Summary and Risk Assessment</source><year>2016</year><comment>Available from: <ext-link ext-link-type="uri" xlink:href="http://www.who.int/emergencies/mers-cov/mers-summary-2016.pdf">www.who.int/emergencies/mers-cov/mers-summary-2016.pdf</ext-link></comment><date-in-citation>Accessed May 20, 2018</date-in-citation></element-citation></ref><ref id="b2-idr-11-2377"><label>2</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Assiri</surname><given-names>A</given-names></name><name><surname>McGeer</surname><given-names>A</given-names></name><name><surname>Perl</surname><given-names>TM</given-names></name><etal></etal><collab>KSA MERS-CoV Investigation Team</collab></person-group><article-title>Hospital outbreak of Middle East respiratory syndrome
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a Two-step Atomic-level Energy Minimization</article-title><source>Biophys J</source><year>2011</year><volume>101</volume><issue>10</issue><fpage>2525</fpage><lpage>34</lpage><pub-id pub-id-type="pmid">22098752</pub-id></element-citation></ref></ref-list></back><floats-group><fig id="f1-idr-11-2377" position="float"><label>Figure 1</label><caption><p>Multi-epitope vaccine design.</p><p><bold>Notes:</bold> (<bold>A</bold>) CTL and (<bold>B</bold>) HTL epitopes were linked
by the short peptide linker GGGGS. Human β-defensin-2 and β-defensin-3
were used as adjuvant at N and C terminals, respectively, linked by the short peptide
linker EAAAK. Epitopes from different proteins are colored in different colors.
C-terminal 6xHis is designated as His tag.</p><p><bold>Abbreviations:</bold> CTL, cytotoxic T lymphocyte; HTL, helper T lymphocyte.</p></caption><graphic xlink:href="idr-11-2377Fig1"></graphic></fig><fig id="f2-idr-11-2377" position="float"><label>Figure 2</label><caption><p>Overlapping regions of the BepiPred linear B-cell epitopes and the epitopes predicted
by other methods.</p><p><bold>Notes:</bold> This analysis shows a strong consensus between the BepiPred linear
B-cell epitopes and the epitopes predicted by other sequence-based and structure-based
epitope prediction methods. Different colors are used to highlight overlapping regions
of epitopes predicted by the different methods.</p></caption><graphic xlink:href="idr-11-2377Fig2"></graphic></fig><fig id="f3-idr-11-2377" position="float"><label>Figure 3</label><caption><p>Overlapping CTL, HTL, and B-cell epitopes.</p><p><bold>Notes:</bold> Overlapping CTL (red), HTL (blue), and B-cell epitopes (green) were
sorted out by MSA using Clustal Omega at EBI server. The ringed clusters of epitopes
involve all three types of epitopes, epitopes with full sequence overlap, and the
epitopes with highest number of HLA allele binders.</p><p><bold>Abbreviations:</bold> CTL, cytotoxic T lymphocyte; EBI, European Bioinformatics
Institute; HLA, human leukocyte antigen; HTL, helper T lymphocyte; MSA, multiple
sequence alignment.</p></caption><graphic xlink:href="idr-11-2377Fig3"></graphic></fig><fig id="f4-idr-11-2377" position="float"><label>Figure 4</label><caption><p>Molecular docking study of CTL and HTL epitopes with respective HLA allele binders.</p><p><bold>Notes:</bold> (<bold>A</bold>) CTL and (<bold>B</bold>) HTL epitopes docked with
their respective HLA allele binders. The docking study shows acceptable negative binding
energy and hydrogen bonds (green balls) formation between epitopes (magenta sticks) and
HLA alleles (cyan cartoons). (*) Residues forming hydrogen bonds with more than
one residue. <bold>Abbreviations:</bold> CTL, cytotoxic T lymphocyte; HLA, human
leukocyte antigen; HTL, helper T lymphocyte.</p></caption><graphic xlink:href="idr-11-2377Fig4"></graphic></fig><fig id="f5-idr-11-2377" position="float"><label>Figure 5</label><caption><p>Molecular dynamics simulation study of the epitope and HLA allele complexes.</p><p><bold>Notes:</bold> Molecular dynamics simulation study of (<bold>A</bold>) CTL and
(<bold>B</bold>) HTL epitope complexes with their respective HLA allele binders. The
reasonably invariable RMSD value indicates a stable complex formation.</p><p><bold>Abbreviations:</bold> CTL, cytotoxic T lymphocyte; HLA, human leukocyte antigen;
HTL, helper T lymphocyte; RMSD, root mean square deviation.</p></caption><graphic xlink:href="idr-11-2377Fig5"></graphic></fig><fig id="f6-idr-11-2377" position="float"><label>Figure 6</label><caption><p>Molecular docking study of CTL epitopes with the TAP cavity.</p><p><bold>Notes:</bold> TAP is shown by cyan ribbon, and epitopes are shown by magenta. In
every panel of the epitope–TAP complex, (<bold>A</bold>) shows the binding of
epitope at two different sites of the TAP cavity, (<bold>B</bold>) and (<bold>C</bold>)
show the hydrogen bond formation between epitopes and TAP cavity residues at two
respective sites of the TAP cavity. (*) Residues forming hydrogen bonds with
more than one residue. (a and b) Chain A and B of TAP. Binding energy is shown in
kcal/mol. Hydrogen bonds are shown by yellow dots.</p><p><bold>Abbreviations:</bold> CTL, cytotoxic T lymphocyte; TAP, transporter associated
with antigen processing.</p></caption><graphic xlink:href="idr-11-2377Fig6"></graphic></fig><fig id="f7-idr-11-2377" position="float"><label>Figure 7</label><caption><p>3D structure modeling of CTL and HTL MEVs.</p><p><bold>Notes:</bold> (<bold>A</bold> and <bold>E</bold>) 3D structure of CTL and HTL
MEVs models, respectively, showing epitopes from different proteins in different colors
(epitope colors are the same as those shown in <xref ref-type="fig" rid="f1-idr-11-2377">Figure 1</xref>). (<bold>B</bold> and <bold>F</bold>) Overlapping regions belonging
to B-cell linear epitopes from both CTL and HTL MEVs, respectively, are shown by
spheres. From (<bold>C</bold>) CTL and (<bold>G</bold>) HTL MEVs, IFN-γ-inducing
epitopes are shown in cyan, while discontinuous B-cell epitopes are shown in magenta.
The regions shown in wheat color are common to both IFN-γ and discontinuous
B-cell epitopes. (<bold>D</bold> and <bold>H</bold>) RAMPAGE analysis of refined CTL and
HTL MEV models, respectively.</p><p><bold>Abbreviations:</bold> CTL, cytotoxic T lymphocyte; HTL, helper T lymphocyte; IFN,
interferon; MEV, multi-epitope vaccine.</p></caption><graphic xlink:href="idr-11-2377Fig7"></graphic></fig><fig id="f8-idr-11-2377" position="float"><label>Figure 8</label><caption><p>Molecular docking and MD simulation study of CTL and HTL MEVs with TLR-3.</p><p><bold>Notes:</bold> (<bold>A</bold>) CTL and (<bold>E</bold>) HTL MEVs (cartoon) docked
complex with TLR-3 (ribbon), respectively. B-factor of the complexes is shown by rainbow
(VIBGYOR) presentation; the regions in blue are very stable, and the region in red is
unstable. In the above complexes, most of the regions are in blue and a very small
region is in yellow and orange, indicating that both complexes are very stable.
(<bold>B</bold> and <bold>F</bold>) MD simulation study of CTL and HTL MEV complexes
with TLR-3, respectively. (<bold>C</bold> and <bold>G</bold>) Rg across the time window
of 6,000 ps for CTL and HTL MEV complexes with TLR-3, respectively. (<bold>D</bold> and
<bold>H</bold>) RMSF for all the atoms of the CTL and HTL MEV complex with TLR-3,
respectively.</p><p><bold>Abbreviations:</bold> CTL, cytotoxic T lymphocyte; HTL, helper T lymphocyte; MD,
molecular dynamics; MEV, multi-epitope vaccine; Rg, radius of gyration; RMSD, root mean
square deviation; RMSF, root mean square fluctuation; TLR-3, toll-like receptor 3.</p></caption><graphic xlink:href="idr-11-2377Fig8"></graphic></fig></floats-group></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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