Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV
Identifieur interne : 001124 ( Pmc/Checkpoint ); précédent : 001123; suivant : 001125Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV
Auteurs : Mohammad Tuhin Ali [Bangladesh] ; Mohammed Monzur Morshed [Bangladesh] ; Md. Amran Gazi [Bangladesh] ; Md. Abu Musa [Bangladesh] ; Md Golam Kibria [Bangladesh] ; Md Jashim Uddin [Bangladesh] ; Md. Anik Ashfaq Khan [Bangladesh] ; Shihab Hasan [Australie]Source :
- Bioinformation [ 0973-8894 ] ; 2014.
Abstract
Middle East Respiratory Syndrome Coronavirus (MERS-CoV) belongs to the coronaviridae family. In spite of several outbreaks in
the very recent years, no vaccine against this deadly virus is developed yet. In this study, the receptor binding domain (RBD) of
Spike (S) glycoprotein of MERS-CoV was analyzed through Computational Immunology approach to identify the antigenic
determinants (epitopes). In order to do so, the sequences of S glycoprotein that belong to different geographical regions were
aligned to observe the conservancy of MERS-CoV RBD. The immune parameters of this region were determined using different
Url:
DOI: 10.6026/97320630010533
PubMed: 25258490
PubMed Central: 4166774
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
PMC:4166774Le document en format XML
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<author><name sortKey="Khan, Md Anik Ashfaq" sort="Khan, Md Anik Ashfaq" uniqKey="Khan M" first="Md. Anik Ashfaq" last="Khan">Md. Anik Ashfaq Khan</name>
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<wicri:noRegion>Queensland</wicri:noRegion>
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<affiliation wicri:level="1"><nlm:aff id="A5">School of Medicine, The University of Queensland (UQ), Brisbane, Queensland, Australia</nlm:aff>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV</title>
<author><name sortKey="Ali, Mohammad Tuhin" sort="Ali, Mohammad Tuhin" uniqKey="Ali M" first="Mohammad Tuhin" last="Ali">Mohammad Tuhin Ali</name>
<affiliation wicri:level="1"><nlm:aff id="A1">Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh</nlm:aff>
<country xml:lang="fr">Bangladesh</country>
<wicri:regionArea>Department of Biochemistry and Molecular Biology, University of Dhaka</wicri:regionArea>
<wicri:noRegion>University of Dhaka</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Morshed, Mohammed Monzur" sort="Morshed, Mohammed Monzur" uniqKey="Morshed M" first="Mohammed Monzur" last="Morshed">Mohammed Monzur Morshed</name>
<affiliation wicri:level="1"><nlm:aff id="A1">Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh</nlm:aff>
<country xml:lang="fr">Bangladesh</country>
<wicri:regionArea>Department of Biochemistry and Molecular Biology, University of Dhaka</wicri:regionArea>
<wicri:noRegion>University of Dhaka</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Gazi, Md Amran" sort="Gazi, Md Amran" uniqKey="Gazi M" first="Md. Amran" last="Gazi">Md. Amran Gazi</name>
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<wicri:noRegion>Dhaka</wicri:noRegion>
</affiliation>
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<author><name sortKey="Musa, Md Abu" sort="Musa, Md Abu" uniqKey="Musa M" first="Md. Abu" last="Musa">Md. Abu Musa</name>
<affiliation wicri:level="1"><nlm:aff id="A2">Laboratory Science Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh</nlm:aff>
<country xml:lang="fr">Bangladesh</country>
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<wicri:noRegion>Dhaka</wicri:noRegion>
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<author><name sortKey="Kibria, Md Golam" sort="Kibria, Md Golam" uniqKey="Kibria M" first="Md Golam" last="Kibria">Md Golam Kibria</name>
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<wicri:regionArea>Laboratory Science Division, International Centre for Diarrhoeal Disease Research, Dhaka</wicri:regionArea>
<wicri:noRegion>Dhaka</wicri:noRegion>
</affiliation>
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<author><name sortKey="Uddin, Md Jashim" sort="Uddin, Md Jashim" uniqKey="Uddin M" first="Md Jashim" last="Uddin">Md Jashim Uddin</name>
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<wicri:noRegion>Dhaka</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Khan, Md Anik Ashfaq" sort="Khan, Md Anik Ashfaq" uniqKey="Khan M" first="Md. Anik Ashfaq" last="Khan">Md. Anik Ashfaq Khan</name>
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<wicri:regionArea>Laboratory Science Division, International Centre for Diarrhoeal Disease Research, Dhaka</wicri:regionArea>
<wicri:noRegion>Dhaka</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Hasan, Shihab" sort="Hasan, Shihab" uniqKey="Hasan S" first="Shihab" last="Hasan">Shihab Hasan</name>
<affiliation wicri:level="1"><nlm:aff id="A4">Bioinformatics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia</nlm:aff>
<country xml:lang="fr">Australie</country>
<wicri:regionArea>Bioinformatics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Queensland</wicri:regionArea>
<wicri:noRegion>Queensland</wicri:noRegion>
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<series><title level="j">Bioinformation</title>
<idno type="ISSN">0973-8894</idno>
<idno type="eISSN">0973-2063</idno>
<imprint><date when="2014">2014</date>
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<front><div type="abstract" xml:lang="en"><p>Middle East Respiratory Syndrome Coronavirus (MERS-CoV) belongs to the coronaviridae family. In spite of several outbreaks in
the very recent years, no vaccine against this deadly virus is developed yet. In this study, the receptor binding domain (RBD) of
Spike (S) glycoprotein of MERS-CoV was analyzed through Computational Immunology approach to identify the antigenic
determinants (epitopes). In order to do so, the sequences of S glycoprotein that belong to different geographical regions were
aligned to observe the conservancy of MERS-CoV RBD. The immune parameters of this region were determined using different <italic>in
silico</italic>
tools and Immune Epitope Database (IEDB). Molecular docking study was also employed to check the affinity of the potential
epitope towards the binding cleft of the specific HLA allele. The N-terminus RBD (S367-S606) of S glycoprotein was found to be
conserved among all the available strains of MERS-CoV. Based on the lower IC<sub>50</sub>
value, a total of eight potential T-cell epitopes and
19 major histocompatibility complex (MHC) class-I alleles were identified for this conserved region. A 9-mer epitope CYSSLILDY
displayed interactions with the maximum number of MHC class-I molecules and projected the highest peak in the B-cell
antigenicity plot which concludes that it could be a better choice for designing an epitope based peptide vaccine against MERSCoV
considering that it must undergo further <italic>in vitro</italic>
and <italic>in vivo</italic>
experiments. Moreover, in molecular docking study, this epitope
was found to have a significant binding affinity of -8.5 kcal/mol towards the binding cleft of the HLA-C*12:03 molecule.</p>
</div>
</front>
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</div1>
</back>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Bioinformation</journal-id>
<journal-id journal-id-type="iso-abbrev">Bioinformation</journal-id>
<journal-id journal-id-type="publisher-id">Bioinformation</journal-id>
<journal-title-group><journal-title>Bioinformation</journal-title>
</journal-title-group>
<issn pub-type="ppub">0973-8894</issn>
<issn pub-type="epub">0973-2063</issn>
<publisher><publisher-name>Biomedical Informatics</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">25258490</article-id>
<article-id pub-id-type="pmc">4166774</article-id>
<article-id pub-id-type="publisher-id">97320630010533</article-id>
<article-id pub-id-type="doi">10.6026/97320630010533</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Hypothesis</subject>
</subj-group>
</article-categories>
<title-group><article-title>Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>ali</surname>
<given-names>Mohammad Tuhin</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="corresp" rid="COR1">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Morshed</surname>
<given-names>Mohammed Monzur</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Gazi</surname>
<given-names>Md. Amran</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Musa</surname>
<given-names>Md. Abu</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kibria</surname>
<given-names>Md Golam</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Uddin</surname>
<given-names>Md Jashim</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Khan</surname>
<given-names>Md. Anik Ashfaq</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Hasan</surname>
<given-names>Shihab</given-names>
</name>
<xref ref-type="aff" rid="A4">4</xref>
<xref ref-type="aff" rid="A5">5</xref>
<xref ref-type="corresp" rid="COR2">*</xref>
</contrib>
<aff id="A1"><label>1</label>
Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh</aff>
<aff id="A2"><label>2</label>
Laboratory Science Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh</aff>
<aff id="A3"><label>3</label>
Department of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, Sylhet, Bangladesh</aff>
<aff id="A4"><label>4</label>
Bioinformatics Lab, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia</aff>
<aff id="A5"><label>5</label>
School of Medicine, The University of Queensland (UQ), Brisbane, Queensland, Australia</aff>
</contrib-group>
<author-notes><corresp id="COR1"><label>*</label>
Mohammad Tuhin Ali: <email>m.tuhinali@gmail.com</email>
Phone: +8801747687885</corresp>
<corresp id="COR2"><label>*</label>
Shihab Hasan: <email>shihab.hasan@qimrberghofer.edu.au</email>
Phone: +61733620468, +61466097724</corresp>
</author-notes>
<pub-date pub-type="collection"><year>2014</year>
</pub-date>
<pub-date pub-type="epub"><day>30</day>
<month>8</month>
<year>2014</year>
</pub-date>
<volume>10</volume>
<issue>8</issue>
<fpage>533</fpage>
<lpage>538</lpage>
<history><date date-type="received"><day>23</day>
<month>6</month>
<year>2014</year>
</date>
<date date-type="rev-recd"><day>07</day>
<month>7</month>
<year>2014</year>
</date>
<date date-type="accepted"><day>08</day>
<month>7</month>
<year>2014</year>
</date>
</history>
<permissions><copyright-statement>© 2014 Biomedical Informatics</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access"><license-p>This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium,
for non-commercial purposes, provided the original author and source are credited.</license-p>
</license>
</permissions>
<abstract><p>Middle East Respiratory Syndrome Coronavirus (MERS-CoV) belongs to the coronaviridae family. In spite of several outbreaks in
the very recent years, no vaccine against this deadly virus is developed yet. In this study, the receptor binding domain (RBD) of
Spike (S) glycoprotein of MERS-CoV was analyzed through Computational Immunology approach to identify the antigenic
determinants (epitopes). In order to do so, the sequences of S glycoprotein that belong to different geographical regions were
aligned to observe the conservancy of MERS-CoV RBD. The immune parameters of this region were determined using different <italic>in
silico</italic>
tools and Immune Epitope Database (IEDB). Molecular docking study was also employed to check the affinity of the potential
epitope towards the binding cleft of the specific HLA allele. The N-terminus RBD (S367-S606) of S glycoprotein was found to be
conserved among all the available strains of MERS-CoV. Based on the lower IC<sub>50</sub>
value, a total of eight potential T-cell epitopes and
19 major histocompatibility complex (MHC) class-I alleles were identified for this conserved region. A 9-mer epitope CYSSLILDY
displayed interactions with the maximum number of MHC class-I molecules and projected the highest peak in the B-cell
antigenicity plot which concludes that it could be a better choice for designing an epitope based peptide vaccine against MERSCoV
considering that it must undergo further <italic>in vitro</italic>
and <italic>in vivo</italic>
experiments. Moreover, in molecular docking study, this epitope
was found to have a significant binding affinity of -8.5 kcal/mol towards the binding cleft of the HLA-C*12:03 molecule.</p>
</abstract>
<kwd-group><kwd>Epitope</kwd>
<kwd>HLA ligand</kwd>
<kwd>MERS-CoV</kwd>
<kwd>Receptor Binding Domain</kwd>
<kwd>Spike glycoprotein</kwd>
</kwd-group>
</article-meta>
</front>
<floats-group><fig id="F1" position="float"><label>Figure 1</label>
<caption><p>Complex of MERS-CoV RBD in conjugation with its
host cell surface receptor CD26 (PDB ID: 4KR0). The molecular
visualization software PyMol (version 1.5.0.3) was utilized to
produce this figure. The aquamarine surface represents the
MERS-CoV RBD whereas the green surface represents CD26.</p>
</caption>
<graphic xlink:href="97320630010533F1"></graphic>
</fig>
<fig id="F2" position="float"><label>Figure 2</label>
<caption><p>(A) Each potential T- cell epitope of the conserved
region is identified with a blue underline. Their respective
residual position and total score predicted by NetCTL
prediction tool are also provided. (B) Each potential epitope
and their corresponding HLA alleles are represented. Among
the epitopes, CYSSLILDY interacts with the highest number of
11 alleles.</p>
</caption>
<graphic xlink:href="97320630010533F2"></graphic>
</fig>
<fig id="F3" position="float"><label>Figure 3</label>
<caption><p>The T-cell epitopes predicted by NetCTL prediction
tool. Most of the epitopes failed to cross threshold level (1.0).
Green coloured sharp points indicate the epitopes that crossed
the threshold level. In this graph, x-axis represents the residue
positions of predicted epitope whereas y-axis represents their
score.</p>
</caption>
<graphic xlink:href="97320630010533F3"></graphic>
</fig>
<fig id="F4" position="float"><label>Figure 4</label>
<caption><p>Interactions between the HLA C*1203 allele and the
epitopes. (A) Experimental epitope (Immuno dominant
determinant of human type-2 collagen) bound at the binding
groove of HLA C*1203 allele. (B) Designed epitope
CYSSLILDY bound at the binding groove of HLA C*1203
allele. Cartoon represents the HLA C*1203 allele whereas sticks
represent the epitopes.</p>
</caption>
<graphic xlink:href="97320630010533F4"></graphic>
</fig>
<fig id="F5" position="float"><label>Figure 5</label>
<caption><p>B-cell anteginic propensity of the RBD predicted by
the Kolaskar and Tongaonkar prediction method. Twelve
potential B-cell antigenic regions are represented by the yellow
colour whereas the regions represented by the green colour
failed to cross threshold level of 1.0.</p>
</caption>
<graphic xlink:href="97320630010533F5"></graphic>
</fig>
</floats-group>
</pmc>
<affiliations><list><country><li>Australie</li>
<li>Bangladesh</li>
</country>
</list>
<tree><country name="Bangladesh"><noRegion><name sortKey="Ali, Mohammad Tuhin" sort="Ali, Mohammad Tuhin" uniqKey="Ali M" first="Mohammad Tuhin" last="Ali">Mohammad Tuhin Ali</name>
</noRegion>
<name sortKey="Gazi, Md Amran" sort="Gazi, Md Amran" uniqKey="Gazi M" first="Md. Amran" last="Gazi">Md. Amran Gazi</name>
<name sortKey="Khan, Md Anik Ashfaq" sort="Khan, Md Anik Ashfaq" uniqKey="Khan M" first="Md. Anik Ashfaq" last="Khan">Md. Anik Ashfaq Khan</name>
<name sortKey="Kibria, Md Golam" sort="Kibria, Md Golam" uniqKey="Kibria M" first="Md Golam" last="Kibria">Md Golam Kibria</name>
<name sortKey="Morshed, Mohammed Monzur" sort="Morshed, Mohammed Monzur" uniqKey="Morshed M" first="Mohammed Monzur" last="Morshed">Mohammed Monzur Morshed</name>
<name sortKey="Musa, Md Abu" sort="Musa, Md Abu" uniqKey="Musa M" first="Md. Abu" last="Musa">Md. Abu Musa</name>
<name sortKey="Uddin, Md Jashim" sort="Uddin, Md Jashim" uniqKey="Uddin M" first="Md Jashim" last="Uddin">Md Jashim Uddin</name>
</country>
<country name="Australie"><noRegion><name sortKey="Hasan, Shihab" sort="Hasan, Shihab" uniqKey="Hasan S" first="Shihab" last="Hasan">Shihab Hasan</name>
</noRegion>
<name sortKey="Hasan, Shihab" sort="Hasan, Shihab" uniqKey="Hasan S" first="Shihab" last="Hasan">Shihab Hasan</name>
</country>
</tree>
</affiliations>
</record>
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