<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.150049.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Design of SARS-CoV-2 protein S peptides recognized by the most frequent HLA alleles in the Moroccan population using an immunoinformatics approach</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 not approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Fakhkhari</surname>
                        <given-names>Meryem</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-8227-1549</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Badaoui</surname>
                        <given-names>Bouabid</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Oumzil</surname>
                        <given-names>Hicham</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Sadki</surname>
                        <given-names>Khalid</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-9224-5050</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Research Laboratory in Oral Biology and Biotechnology, Faculty of Dentistry, Mohammed V University in Rabat, Rabat, 10112, Morocco</aff>
                <aff id="a2">
                    <label>2</label>Department of Biology, Faculty of Sciences, Mohammed V University in Rabat, Rabat, 101O6, Morocco</aff>
                <aff id="a3">
                    <label>3</label>Medical Biotechnology Laboratory, Faculty of Medicine and Pharmacy, Mohammed V University in Rabat, Rabat, 10112, Morocco</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:ksadki1@yahoo.fr">ksadki1@yahoo.fr</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>20</day>
                <month>5</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>514</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>8</day>
                    <month>5</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Fakhkhari M et al.</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/13-514/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>The coronavirus disease 2019 (COVID-19) is an infectious disease, caused by the new coronavirus known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and exhibits diverse clinical outcomes and symptoms in infected individuals, emphasizing the need to investigate how human genetic diversity influences the virus&#x2019;s impact. This study aims to employ in silico methods to identify epitopes capable of eliciting an immune response, focusing on the most prevalent HLA-I and HLA-II alleles in the Moroccan population.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>Our research consisted in predicting peptide-binding affinities between the most prevalent HLA Class I and Class II alleles in the Moroccan population and SARS-CoV-2 spike glycoprotein (S protein) peptides of variants isolated from strains of Moroccan patients. We performed the same analyses for SARS-CoV-2 wild type S protein to assess the ability of these HLA alleles to interact with peptides in the presence or absence of SARS-CoV-2 mutations.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>In a broader sense, 12 distinct HLA Class I and Class II alleles in the Moroccan population have been identified as possibly interacting with 19 epitopes in the SARS-CoV-2 S protein. Findings of this study must be validated in both in vitro and in vivo models.</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>These data may help clarify the issue of host cell susceptibility and the outcome of SARS-CoV-2 infection, and may guide further research to uncover potential targets for the vaccination strategy.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>SARS-CoV-2</kwd>
                <kwd>S protein</kwd>
                <kwd>peptides</kwd>
                <kwd>Variants</kwd>
                <kwd>HLA alleles Moroccan population</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <def-list>
            <title>List of abbreviations</title>
            <def-item>
                <term id="G1">COVID-19</term>
                <def>
                    <p>Coronavirus disease</p>
                </def>
            </def-item>
            <def-item>
                <term id="G7">E</term>
                <def>
                    <p>Envelope protein</p>
                </def>
            </def-item>
            <def-item>
                <term id="G3">HLA</term>
                <def>
                    <p>Human leukocyte antigen</p>
                </def>
            </def-item>
            <def-item>
                <term id="G8">M</term>
                <def>
                    <p>Membrane glycoprotein</p>
                </def>
            </def-item>
            <def-item>
                <term id="G5">MHC</term>
                <def>
                    <p>Major histocompatibility complex</p>
                </def>
            </def-item>
            <def-item>
                <term id="G9">N</term>
                <def>
                    <p>Nucleocapsid phosphoprotein</p>
                </def>
            </def-item>
            <def-item>
                <term id="G10">ORF</term>
                <def>
                    <p>Open reading frame</p>
                </def>
            </def-item>
            <def-item>
                <term id="G11">RBD</term>
                <def>
                    <p>Receptor-binding domain</p>
                </def>
            </def-item>
            <def-item>
                <term id="G4">S</term>
                <def>
                    <p>Spike glycoprotein</p>
                </def>
            </def-item>
            <def-item>
                <term id="G2">SARS-CoV-2</term>
                <def>
                    <p>Severe acute respiratory syndrome 2</p>
                </def>
            </def-item>
            <def-item>
                <term id="G6">WHO</term>
                <def>
                    <p>World Health Organization</p>
                </def>
            </def-item>
        </def-list>
        <sec id="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>The COVID-19 pandemic has caused unparalleled economic and social disruption across the world. COVID-19 is a respiratory illness that results from an infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus was initially in December 2019 in Wuhan, China, and has quickly spread throughout the world.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> By December 2022, the World Health Organization (WHO) had reported over 651 million cases of COVID-19, with more than 6 million deaths attributed to the disease. The first instance of the COVID-19 virus was registered in the Kingdom of Morocco on March 02, 2020, in Casablanca city. The Moroccan patient had acute pneumonia, and the infection was imported from Europe.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> Between January 3, 2020, and August 16, 2023, the Ministry of Health in Morocco reported a total of 1 275 320 confirmed cases of COVID-19 with 16 297 deaths in within the country. The mortality rate is stated at 1.3% (Ministry of Health, Morocco, CNOUSP report, April 2023).</p>
            <p>A notable characteristic of COVID-19 that continually surprises us is the extensive range of clinical symptoms that patients exhibit across different populations. These symptoms range from mild to severe, with severe cases potentially leading to pneumonia, respiratory failure, multi-organ failure, and death.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> These differences highlight the significance of studying and understanding human genetic variation during infections. Previous studies have linked the susceptibility and outcomes of multiple infectious diseases to the genetic background of the host. The Human Leukocyte Antigen system is believed to be among the components that could explain differences in virus susceptibility and severity, and it has been recommended as a potential genetic factor that affects a person&#x2019;s immune response to SARS-CoV-2.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
            </p>
            <p>The human leukocyte antigen (HLA) system, which is a major component of the adaptive immune system, is in charge of recognizing and binding both endogenous and exogenous antigens.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> HLA molecules are classified into two classes: HLA class I and HLA class II. While HLA class II (DR, DQ, DP) molecules are primarily responsible for displaying peptides from external pathogens, HLA class I (A, B, C) molecules are crucial for immune protection against intracellular pathogens. HLA polymorphism is the highest degree of variability found in the genetic code of the proteins expressed by this system. This variability is considered an important factor in determining a person&#x2019;s resistance to, or susceptibility to specific infectious illnesses.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
            </p>
            <p>The SARS-CoV-2 genome encodes a number of structural proteins, including the spike protein (S), envelope protein (E), membrane glycoprotein (M), and nucleocapsid phosphoprotein (N), which is in accordance with other coronaviruses. Additionally, it encodes nonstructural proteins, such as open reading frame 1ab (ORF1ab), ORF3a, ORF6, ORF7a, ORF8, and ORF10.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> This study focused on the spike protein, which is the primary antigen present on the surface of the virus, facilitating SARS-CoV-2 entrance into human host cells,
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> and additionally because of its high mutation rate, which enables it to alter its shape and escape host immune responses.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> The Spike protein, also known as S protein, is made up of two subunits, S1 and S2, which are connected by a furin cleavage site. The S1 subunit comprises the receptor-binding domain (RBD), which is responsible for the virus&#x2019;s ability to adhere to the host cell membrane and initiate infection. The S2 subunit has a hydrophobic fusion loop which facilitates membrane fusion. Therapeutic developments against SARS-CoV-2 are often targeted at RBD.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> The spike is frequently studied for the development of neutralizing antibodies and vaccines, and is widely considered as a successful target for detection purposes.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup>
            </p>
            <p>Due to their effectiveness and up speed, computational techniques are far superior to laboratory tests in the drug development process because they can anticipate the antigenic epitopes of specific viral proteins.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
            </p>
            <p>In Morocco, like in other countries, the COVID-19 pandemic had a noticeable impact on the health system. Although many risk factors of COVID-19 severity have been described, data from North Africa are limited. This study used an immunoinformatics approach to predict the peptide-binding affinity between the most frequent HLA Class I and Class II alleles in the Moroccan population and SARS-CoV-2 S protein peptides of variants isolated from strains of Moroccan patients. The same analysis was also performed for the SARS-CoV-2 wild-type S protein to assess the ability of these HLA alleles to interact with peptides in the presence or absence of the SARS-CoV-2 mutation, and thus predict which epitopes would be most effective at acting as potent immunogens.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Selection of Major Histocompatibility Complex (MHC) alleles</title>
                <p>The most frequent HLA class I and class II alleles in the Moroccan population were obtained from the Allele Frequency Net Database (
                    <ext-link ext-link-type="uri" xlink:href="http://www.allelefrequencies.net/pop6001a.asp">http://www.allelefrequencies.net/pop6001a.asp</ext-link>), which compiled data from studies conducted in different regions of Moroccan. The average allelic frequency of each allele was then computed using data from multiple regions.</p>
            </sec>
            <sec id="sec8">
                <title>Retrieval of Mutated sequences of SARS-COV-2 S protein</title>
                <p>To evaluate the HLA-peptide-binding affinity predictions, we obtained the mutated sequences of the SARS-COV-2 S protein for each variant of concern, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529), from strains of Moroccan patients available on the GISAID databank.</p>
            </sec>
            <sec id="sec9">
                <title>Retrieval of the Wild-Type SARS-CoV-2 sequence</title>
                <p>The reference genome (WuhanHu-1 strain) was obtained from the NCBI Refseq database under GenBank accession number NC_045512.2. The amino acid sequence of the S protein from the reference genome was retrieved in FASTA format and used as a reference sequence for comparison with the sequences of the variants.</p>
            </sec>
            <sec id="sec10">
                <title>Prediction of SARS-CoV-2-derived HLA-binding peptides</title>
                <p>The NetMHCpan - v4.0 and NetMHCIIpan v. 3.2 programs were used to predict HLA peptide-binding affinity for HLA class I and class II alleles, respectively. The FASTA sequences from both the GISAID databank and the NCBI database were imported and analyzed. Using the aforementioned sequences, we predicted the binding affinity of each HLA allele to all potential 10-mer and 15-mer overlapping peptides for HLA class I and class II, respectively.</p>
            </sec>
            <sec id="sec11">
                <title>Antigenicity prediction</title>
                <p>We used Vaxijen V.2.0 (
                    <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>), to assess the potential antigenicity of the predicted peptides by setting a threshold score of less than 0.5 and employing a virus model to eliminate non-antigenic peptides.</p>
                <p>The antigenicity response assesses the capability of the proposed epitopes to prompt an immune response.</p>
            </sec>
            <sec id="sec12">
                <title>Toxicity prediction</title>
                <p>Toxicity of the predicted peptides was set using the ToxinPred server (
                    <ext-link ext-link-type="uri" xlink:href="https://webs.iiitd.edu.in/raghava/toxinpred/multi_submit.php">https://webs.iiitd.edu.in/raghava/toxinpred/multi_submit.php</ext-link>). This server enables the identification of highly toxic or non-toxic peptides from a large pool of peptides submitted by analyzing their key physico-chemical properties such as hydrophobicity, hydropathicity, amphipathicity, molecular weight, and pI charge.</p>
            </sec>
            <sec id="sec13">
                <title>Binding affinity assessment</title>
                <p>The HLA binding affinity frequencies of peptides from the mutated S protein were compared with those from the reference S protein (Wild-Type) to identify which HLA alleles had varying binding affinities in the presence of mutations.</p>
                <p>This analysis aimed to identify mutated peptides that bind well the most frequent HLA alleles in the Moroccan population.</p>
            </sec>
        </sec>
        <sec id="sec14" sec-type="results">
            <title>Results</title>
            <p>
                <xref ref-type="table" rid="T1">Table 1</xref> lists the most frequent HLA class I and class II alleles in the Moroccan population, according to the HLA Allele Frequency Net Database. The data reveals a prevalence of HLA class I alleles over class II alleles, with a total of 10 HLA-A, 6 HLA-B, 7 HLA-C, and 7 HLA-DRB1 alleles identified.</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Averages frequency of most common HLA class I and II alleles in the Moroccan population.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="6" rowspan="1" valign="top">HLA Class I</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">HLA-A allele</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Frequency</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">HLA-B allele</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Frequency</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">HLA-C allele</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Frequency</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*01:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.131</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">B*08:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.0703</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">C*02:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.065</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*02:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.1673</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">B*18:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.0443</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">C*04:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.134</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*03:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.043</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">B*35:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.037</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">C*05:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.055</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*23:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.08</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">B*44:03</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.084</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">C*06:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.22</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*24:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.048</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">B*45:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.06</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">C*07:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.093</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*29:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.059</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">B*50:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.10</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">C*08:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.0613</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*30:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.05</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">C*16:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.06</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*30:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.057</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*33:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.032</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">A*68:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.0473</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="2" rowspan="1" valign="top">HLA Class II</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Frequency</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DRB1*01:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.0355</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DRB1*03:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.152</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DRB1*04:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.059</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DRB1*04:05</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.045</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DRB1*07:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.163</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DRB1*13:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.071</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DRB1*15:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.105</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>In 
                <xref ref-type="table" rid="T2">Table 2</xref>, mutations identified in the SARS-CoV-2 S protein isolated from strains of Moroccan patients are presented, sourced from the GISAID databank. A total of 23 mutations were identified on the spike protein across the different variants of SARS-CoV-2. The mutations highlighted in bold are the common ones found among all six variants, while each variant also includes unique mutations not observed in other variants of concern.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>SARS-CoV-2 S protein mutations isolated from strains of Moroccan patients (n=23).</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">SARS-CoV-2 variants</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">S protein mutations</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">SARS-CoV-2 variants</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">S protein mutations</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="6" valign="top">Alpha</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">V6F</td>
                            <td align="left" colspan="1" rowspan="6" valign="top">Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">L452R</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">H69-V70</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>E484K</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Y144</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>D614G</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>N501Y</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">P681R</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>D614G</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">T19R</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">P681H</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">T478K</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="4" valign="top">B&#x00ea;ta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">K417N</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">Kappa</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">E484Q</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>E484K</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>D614G</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>N501Y</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="8" valign="top">Omicron</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">E484A</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>D614G</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Q498R</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="6" valign="top">Gamma</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">K417T</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Q954H</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>E484K</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Q493R</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>N501Y</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">S704L</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>D614G</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">T547K</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">V1176F</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">T376A</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">V213G</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Our dataset for peptide-binding affinity prediction comprises only peptides with a mutation in their core. Two hundred and twenty peptides were identified based on the results from NetMHCpan servers. Non-immunogenic or toxic peptides were discarded from further analysis. Consequently, eighty-five immunogenic peptides in the SARS-CoV-2 S protein were retained for the assessment of binding affinities (as shown in 
                <xref ref-type="table" rid="T3">Table 3</xref>).</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>SARS-CoV-2 S peptides for Class I and II HLA alleles of wild and mutated types.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Mutation</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">Peptides for Class I (10mers)</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">Peptides for Class II (15mers)</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Wild</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Mutated</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Wild</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Mutated</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">V6F</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">FVFL
                                <bold>V</bold>LLPLV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">FVFL
                                <bold>F</bold>LLPLV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">--</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">H69-V70</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NVTWFHAI
                                <bold>HV</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NVTWFHAISG</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">FSNVTWFHAI
                                <bold>HV</bold>SGT</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">FSNVTWFHAISGTNG</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Y144-145</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">CNDPFLGV
                                <bold>Y</bold>Y</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">CNDPFLGVYH</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QFCNDPFLGV
                                <bold>Y</bold>YHKN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QFCNDPFLGVYHKNN</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">K417N</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GQTG
                                <bold>K</bold>IADYN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GQTG
                                <bold>N</bold>IADYN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">VRQIAPGQTG
                                <bold>K</bold>IADY</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">VRQIAPGQTG
                                <bold>N</bold>IADY</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">K417T</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GQTG
                                <bold>K</bold>IADYN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GQTG
                                <bold>T</bold>IADYN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">VRQIAPGQTG
                                <bold>K</bold>IADY</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">VRQIAPGQTG
                                <bold>T</bold>IADY</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">L452R</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GGNYNY
                                <bold>L</bold>YRL</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GGNYNY
                                <bold>R</bold>YRL</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">DSKVGGNYNY
                                <bold>L</bold>YRLF</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">DSKVGGNYNY
                                <bold>R</bold>YRLF</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">E484A</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>E</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>A</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QAGSTPCNGV
                                <bold>E</bold>GFNC</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QAGSTPCNGV
                                <bold>A</bold>GFNC</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">E484K</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>E</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>K</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PCNGV
                                <bold>E</bold>GFNCYFPLQ</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PCNGV
                                <bold>K</bold>GFNCYFPLQ</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">E484Q</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>E</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>Q</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PCNGV
                                <bold>E</bold>GFNCYFPLQ</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PCNGV
                                <bold>Q</bold>GFNCYFPLQ</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Q498R</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">YGF
                                <bold>Q</bold>PTNGVG</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">YGF
                                <bold>R</bold>PTNGVG</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">LQSYGF
                                <bold>Q</bold>PTNGVGYQ</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">LQSYGF
                                <bold>R</bold>PTNGVGYQ</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">N501Y</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QSYGFQPT
                                <bold>N</bold>G</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QSYGFQPT
                                <bold>Y</bold>G</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QSYGFQPT
                                <bold>N</bold>GVGYQP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QSYGFQPT
                                <bold>Y</bold>GVGYQP</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">D614G</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">YQ
                                <bold>D</bold>VNCTEVP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">YQ
                                <bold>G</bold>VNCTEVP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NQVAVLYQ
                                <bold>D</bold>VNCTEV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NQVAVLYQ
                                <bold>G</bold>VNCTEV</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">P681H</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NS
                                <bold>P</bold>RRARSVA</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NS
                                <bold>H</bold>RRARSVA</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">YQTQTNS
                                <bold>P</bold>RRARSVA</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">YQTQTNS
                                <bold>H</bold>RRARSVA</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">P681R</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">TNS
                                <bold>P</bold>RRARSV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">TNS
                                <bold>R</bold>RRARSV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">ASYQTQTNS
                                <bold>P</bold>RRARS</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">ASYQTQTNS
                                <bold>R</bold>RRARS</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">V1176F</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">ISGINAS
                                <bold>V</bold>VN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">ISGINAS
                                <bold>F</bold>VN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">DISGINAS
                                <bold>V</bold>VNIQKE</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">DISGINAS
                                <bold>F</bold>VNIQKE</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">T19R</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QCVNL
                                <bold>T</bold>TRTQ</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QCVNL
                                <bold>R</bold>TRTQ</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SSQCVNL
                                <bold>T</bold>TRTQLPP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SSQCVNL
                                <bold>R</bold>TRTQLPP</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">T478K</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">---</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">---</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">---</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">---</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Q954H</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GKLQDVVN
                                <bold>Q</bold>N</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">---</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GKLQDVVN
                                <bold>Q</bold>NAQALN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GKLQDVVN
                                <bold>H</bold>NAQALN</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Q493R</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NCYFPL
                                <bold>Q</bold>SYG</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NCYFPL
                                <bold>R</bold>SYG</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NCYFPL
                                <bold>Q</bold>SYGFQPTN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NCYFPL
                                <bold>R</bold>SYGFQPTN</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">S704L</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">MSLGAEN
                                <bold>S</bold>VA</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">MSLGAEN
                                <bold>L</bold>VA</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SLGAEN
                                <bold>S</bold>VAYSNNSI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SLGAEN
                                <bold>L</bold>VAYSNNSI</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">T547K</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NFNFNGL
                                <bold>T</bold>GT</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NFNFNGL
                                <bold>K</bold>GT</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">KCVNFNFNGL
                                <bold>T</bold>GTGV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">KCVNFNFNGL
                                <bold>K</bold>GTGV</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">T376A</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SFS
                                <bold>T</bold>FKCYGV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SFS
                                <bold>A</bold>FKCYGV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SASFS
                                <bold>T</bold>FKCYGVSPT</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SASFS
                                <bold>A</bold>FKCYGVSPT</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">V213G</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">KHTPINL
                                <bold>V</bold>RD</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">KHTPINL
                                <bold>G</bold>RD</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PINL
                                <bold>V</bold>RDLPQGFSAL</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>-No peptide contains V in its core; --No peptide contains the mutations in its core; ---All predicted peptides were probable non-antigen on Vaxijen.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>The comparison of HLA class I binding repertoires between wild type and mutated S protein peptides revealed that 10 mutations in the S protein had the potential to bind to HLA-A*02:01, HLA-A*29:02, HLA-A*68:02, HLA-B*45:01, and HLA-C*16:01.</p>
            <p>Among these HLA alleles, HLA-A*02:01 and HLA-C*16:01 had one good binder each with T547K and T376A, respectively. HLA-A*29:02 had three good binders with H69-V70, P681R, and D614G. For HLA-A*68:02, four good binders were found with H69-V70, Y144-145, L252R, and T547K. Similarly, HLA-B*45:01 had four good binders with E484K, E484Q, E484A, and D614G.</p>
            <p>Regarding HLA Class II, 9 mutated peptides were found able to interact with HLA-DRB1*01:02, HLA-DRB1*03:01, HLA-DRB1*04:02, HLA-DRB1*04:05, HLA-DRB1*07:01, HLA-DRB1*13:02, and HLA-DRB1*15:01.</p>
            <p>Among these, HLA-DRB1*01:02, DRB1*04:02, and HLA-DRB1*04:05 had a common good binder with V213G. HLA-DRB1*03:01 and HLA-DRB1*15:01 had four good binders each, which were (H69-V70, K417N, K417T, and D614G) and (Y144-145, K417N, K417T, and V213G) respectively. On the other hand, HLA-DRB1*07:01 and HLA-DRB1*13:02 had five good binders each with (K417N, K417T, L252R, T19R, and V213G) and (N501Y, H69-V70, K417T, T19R, and V213G) respectively. 
                <xref ref-type="table" rid="T4">Table 4</xref> provides more details on the peptide sequences.</p>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>Table 4. </label>
                <caption>
                    <title>Sequences of the S protein good binders with their HLA alleles.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top"/>
                            <th align="left" colspan="1" rowspan="1" valign="top">HLA alleles</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Good binders' sequences</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="5" valign="top">Class I</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-A*02:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NFNFNGL
                                <bold>K</bold>GT</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-A*29:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NVTWFHAISG, TNS
                                <bold>R</bold>RRARSV, and YQ
                                <bold>G</bold>VNCTEVP</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-A*68:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NVTWFHAISG, CNDPFLGVYH, GGNYNY
                                <bold>R</bold>YRL and NFNFNGL
                                <bold>K</bold>GT</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-B*45:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>K</bold>GFNCYFP, GV
                                <bold>Q</bold>GFNCYFP, GV
                                <bold>A</bold>GFNCYF, and YQ
                                <bold>G</bold>VNCTEVP</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-C*16:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SFS
                                <bold>A</bold>FKCYGV</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="7" valign="top">Class II</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1*01:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1*03:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">FSNVTWFHAISGTNG, VRQIAPGQTG
                                <bold>N</bold>IADY, VRQIAPGQTG
                                <bold>T</bold>IADY, and NQVAVLYQ
                                <bold>G</bold>VNCTEV</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1*04:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1*04:05</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1*07:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">VRQIAPGQTG
                                <bold>N</bold>IADY, VRQIAPGQTG
                                <bold>T</bold>IADY, DSKVGGNYNY
                                <bold>R</bold>YRLF, SSQCVNL
                                <bold>R</bold>TRTQLPP, and PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1*13:02</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QSYGFQPT
                                <bold>Y</bold>GVGYQP, FSNVTWFHAISGTNG, VRQIAPGQTG
                                <bold>T</bold>IADY, SSQCVNL
                                <bold>R</bold>TRTQLPP, and PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HLA-DRB1*15:01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QFCNDPFLGVYHKNN, VRQIAPGQTG
                                <bold>N</bold>IADY, VRQIAPGQTG
                                <bold>T</bold>IADY, and PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>The HLA-DRB1*15:02 allele was the only one to exhibit good binding affinity to the N501Y mutation, which emerged in the Alpha, Beta and Gamma lineages. Conversely, the H69-V70, Y144-145, L452R, and D614G mutations were presented by both HLA class I and class II alleles, while the K417N, K417T, and V213G mutations were only presented in Class II.</p>
            <p>NetMHCIIpan v. 3.2 did not predict any peptides for the most frequent HLA class II alleles in the Moroccan population for both the Spike V6F mutation and the wild-type spike sequence. All predicted peptides for the T478K mutation in the receptor binding domain (RBD) of the Delta variant were deemed non-antigenic by the Vaxijen tool. This mutation is believed to help evade recognition by the immune system,
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> particularly with regards to antibodies and neutralization, or in impairing the interaction between the RBD and drugs.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> 
                <xref ref-type="table" rid="T5">Tables 5</xref> and 
                <xref ref-type="table" rid="T6">6</xref> present the antigenicity scores of the selected binders.</p>
            <table-wrap id="T5" orientation="portrait" position="float">
                <label>Table 5. </label>
                <caption>
                    <title>Vaxijen scores (antigenicity) of the predicted MHC class I allele binding peptides.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variant</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Peptide</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Vaxijen score</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Final decision</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alpha</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NVTWFHAISG</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.6203</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">TNS
                                <bold>R</bold>RRARSV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.1716</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alpha/Beta/Gamma/Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">YQ
                                <bold>G</bold>VNCTEVP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.0639</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alpha</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">CNDPFLGVYH</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.4600</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GGNYNY
                                <bold>R</bold>YRL</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.2747</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Beta/Gamma/Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>K</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.7415</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Kappa</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>Q</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.7874</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Omicron</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">GV
                                <bold>A</bold>GFNCYFP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.2211</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Omicron</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NFNFNGL
                                <bold>K</bold>GT</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.3565</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Omicron</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SFS
                                <bold>A</bold>FKCYGV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.5764</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>*</label>
                            <p>Selected good binders.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <table-wrap id="T6" orientation="portrait" position="float">
                <label>Table 6. </label>
                <caption>
                    <title>Vaxijen scores (antigenicity) of the predicted MHC class II allele binding peptides.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variant</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Peptide</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Vaxijen score</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Final decision</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alpha</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">FSNVTWFHAISGTNG</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.8214</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Beta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">VRQIAPGQTG
                                <bold>N</bold>IADY</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.1378</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn2">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Gamma</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">VRQIAPGQTG
                                <bold>T</bold>IADY</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.1046</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn2">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alpha/Beta/Gamma/Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">NQVAVLYQ
                                <bold>G</bold>VNCTEV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.7970</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">DSKVGGNYNY
                                <bold>R</bold>YRLF</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.0304</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn2">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alpha/Beta/Gamma</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QSYGFQPT
                                <bold>Y</bold>GVGYQP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.7291</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alpha</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">QFCNDPFLGVYHKNN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.7581</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Delta</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SSQCVNL
                                <bold>R</bold>TRTQLPP</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.2742</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn2">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Omicron</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PINL
                                <bold>G</bold>RDLPQGFSAL</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.9873</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <xref ref-type="table-fn" rid="tfn2">*</xref>
                            </td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <fn-group content-type="footnotes">
                        <fn id="tfn2">
                            <label>*</label>
                            <p>Selected good binders.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
        </sec>
        <sec id="sec15" sec-type="discussion">
            <title>Discussion</title>
            <p>Due to their efficiency and speed, computational approaches have consequently arisen as potent alternatives or choices for the development of diagnostic tools for infectious diseases, as well as new immunotherapies and vaccines.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> Predictive computationals for identifying antigenic epitopes in viral or bacterial proteins are critical and valuable in the development of new drugs.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> It has been recommended to employ these tools before performing laboratory experiments because they are more efficient and faster to use.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> Several studies have utilized immunoinformatic approaches on different SARS-CoV-2 proteins to design potential epitope vaccine candidates against SARS-CoV-2,
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> In this study, we designed SARS-CoV-2 S protein peptides that bind to the most frequent HLA class I and class II alleles in the Moroccan population. The aim was to evaluate the potential of these peptides to elicit an immune response using in silico methods. The SARS-CoV-2 S protein was chosen as the target in this study because it is the most mutated structural protein of SARS-CoV-2 and is frequently studied as it helps in target recognition and cellular entry. This protein promotes viral infection and is essential for the development of neutralizing antibodies and vaccines.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> Additionally, the S protein is commonly acknowledged as a suitable target for detection purposes.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
            </p>
            <p>In this study, we selected twenty-three mutations from five SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, and Omicron) as they are considered key mutations associated with higher transmission and reinfection rates.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> We evaluated the ability of class I and class II HLA molecules to present the mutated peptides of the SARS-CoV-2 spike protein. Our findings showed that HLA class I molecules had a higher proportion of good binders compared to HLA class II alleles, with 10 versus 9, respectively.</p>
            <p>The peptides SSQCVNL
                <bold>R</bold>TRTQLPP, VRQIAPGQTG
                <bold>N</bold>IADY, VRQIAPGQTG
                <bold>T</bold>IADY, DSKVGGNYNY
                <bold>R</bold>YRLF, and PINL
                <bold>G</bold>RDLPQGFSAL were selected as immunogens for HLA class II based on their antigenic score (1.2742; 1,1378; 1,1046; 1,0304 and 0.9873 respectively), non-allergenicity, and lack of toxicity. For HLA class I, the peptides NFNFNGL
                <bold>K</bold>GT, GGNYNY
                <bold>R</bold>YRL, GV
                <bold>A</bold>GFNCYFP, TNS
                <bold>R</bold>RRARSV, and YQ
                <bold>G</bold>VNCTEVP exhibited the best antigenic scores of 1.3565; 1,2747; 1,2211; 1,1716; and 1,0639, respectively. The scores therefore indicate the stimulation of the immune system in response to the proposed epitopes. Given their binding affinity with the most frequent HLA alleles in the Moroccan population and antigenicity response, these epitopes may be promising candidates for vaccine development.</p>
            <p>Potential immunogenic peptides have been identified as prospective COVID-19 vaccine targets using in silico studies. Previous research has indicated that HLA-A*02:01, among other alleles, exhibited the strongest binding to COVID-19 epitopes.
                <sup>
                    <xref ref-type="bibr" rid="ref34">34</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref35">35</xref>
                </sup> Our study revealed that the &#x201c;NFNFNGL
                <bold>K</bold>GT&#x201d; peptide of the 
                <bold>T547K</bold> mutation in the Omicron variant showed a higher antigenicity score and had the highest affinity to this particular allele. Consequently, this epitope could be a promising candidate for the development of a COVID-19 vaccine.</p>
            <p>Regarding the HLA-C allele, a peptide belonging to the Omicron subvariant peptide with the sequence SFS
                <bold>A</bold>FKCYGV was predicted to have high binding affinity with HLA-C*16:02. However, it was not selected due to its Vaxijen score of 0.5764. This gene has been previously reported to have a less distinctive peptide repertoire when compared to HLA-A and HLA-B.
                <sup>
                    <xref ref-type="bibr" rid="ref36">36</xref>
                </sup> HLA-C*16:01 was found to be more prevalent among individuals who had a mild form of COVID-19 compared with those with severe or critical forms of the disease in a cohort of Spanish Mediterranean Caucasians.
                <sup>
                    <xref ref-type="bibr" rid="ref37">37</xref>
                </sup>
            </p>
            <p>HLA-A*68:02 was the MHC-I molecule that bound the immune epitopes of the S protein 
                <bold>L452R</bold> mutation of the Delta variant (GGNYNY
                <bold>R</bold>YRL). A study conducted in Tapachula Chapas, found that although the frequency of HLA-A*68 was lower in COVID-19 patients who were ill, the allele provided 3.3 times more protection against a fatal outcome from SARS-CoV-2 infection in mestizo individuals.
                <sup>
                    <xref ref-type="bibr" rid="ref38">38</xref>
                </sup> Both HLA-A*68:01 and HLA-A*68:02 have the ability to bind to a large number of SARS-CoV-2 peptides with varying degrees of affinity. Furthermore, a systematic review and meta-analysis found that HLA-A*68:02, along with other HLA class I and class II alleles, were associated with COVID- 19 severity.
                <sup>
                    <xref ref-type="bibr" rid="ref39">39</xref>
                </sup>
            </p>
            <p>HLA-A, HLA-B, HLA-C, and HLA-DRB1 may serve as potential indicators of the severity and likelihood of death from COVID-19. However, further research on a larger scale are required to confirm this hypothesis.</p>
            <p>A literature review has revealed that HLA class I alleles may be deemed as determinants of either resistance or susceptibility to COVID-19. This is due to the fact that these alleles have the ability to bind to SARS-CoV-2 peptides, leading to the modulation of the immune response against the virus.
                <sup>
                    <xref ref-type="bibr" rid="ref40">40</xref>
                </sup>
            </p>
            <p>Several studies have employed a similar approach to design peptides for the protein S of SARS-CoV-2. 
                <italic toggle="yes">Baruah et al.</italic> found five CD8+ T cell epitopes YLQPRTFLL, GVYFASTEK, EPVLKGVKL, VVNQNAQAL, and WTAGAAAYY, along with eight B cell epitopes that are more likely to bind MHC class I commonly found in China.
                <sup>
                    <xref ref-type="bibr" rid="ref41">41</xref>
                </sup> In a second study, 
                <italic toggle="yes">Bhattacharya et al.</italic> identified thirteen potential MHC-I antigenic peptides (SQCVNLTTR, GVYYHKNNK, GKQGNFKNL, GIYQTSNFR, VSPTKLNDL, KIADYNYKL, KVGGNYNYL, EGFNCYFPL, GPKKSTNLV, SPRRARSVA, LGAENSVAY, FKNHTSPDV, and DEDDSEPVL) and three potential MHC-II antigenic peptides (IHVSGTNGT, VYYHKNNKS, and FKNHTSPDV).
                <sup>
                    <xref ref-type="bibr" rid="ref42">42</xref>
                </sup>
            </p>
            <p>
                <italic toggle="yes">Joshi et al.</italic> proposed the MHC-I ITLCFTLKR peptide as a potential vaccine candidate,
                <sup>
                    <xref ref-type="bibr" rid="ref43">43</xref>
                </sup> while another study conducted on the Brazilian population found 24 epitopes that bind to 17 different MHC-I alleles.
                <sup>
                    <xref ref-type="bibr" rid="ref44">44</xref>
                </sup> Other studies have also identified B-cell epitopes on spike protein for developing a protective vaccine against SARS-CoV-2.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref45">45</xref>
                </sup>
            </p>
            <p>The current study&#x2019;s findings are novel and have not been previously published. These findings are valuable for the development of broadly accessible vaccine epitopes targeting SARS-CoV-2, and can also offer valuable insights for investigating T-cell responses.</p>
            <p>Nevertheless, to confirm their immunogenicity against SARS-CoV-2, further in-vitro experimental validation or in vivo studies are necessary.</p>
        </sec>
        <sec id="sec16">
            <title>Conclusions and perspectives</title>
            <p>This is the first Moroccan in silico study to assess potential immunogenic peptides within the S protein of various SARS-CoV-2 variants according to the most frequent HLA alleles in the Moroccan population, using an immunoinformatic approach. The findings of the current study have not been published previously. To sum up, we identified 19 epitopes in the SARS-CoV-2 S protein that can bind to 12 distinct HLA Class I and Class II alleles among the Moroccan population, as they were characterized by a probability of triggering an immune response. However, in order to validate their immunogenicity against SARS-CoV-2, additional in-vitro experimental validation or in vivo studies are essential.</p>
        </sec>
        <sec id="sec17">
            <title>Ethics approval and consent to participate</title>
            <p>Not applicable.</p>
        </sec>
        <sec id="sec18">
            <title>Consent for publication</title>
            <p>Not applicable.</p>
        </sec>
        <sec id="sec19">
            <title>Author&#x2019;s contributions</title>
            <p>
                <bold>MF</bold>: Methodology, Data curation, Formal analysis, Writing &#x2013; original draft. 
                <bold>BB</bold>: Data curation, Writing &#x2013; Review &amp; Editing. 
                <bold>HO</bold>: Visualization, Writing &#x2013; review &amp; editing, Investigation. 
                <bold>KS</bold>: Conceptualization, Methodology, Formal analysis, Supervision, Writing &#x2013; review &amp; editing.</p>
        </sec>
    </body>
    <back>
        <sec id="sec22" sec-type="data-availability">
            <title>Data availability statement</title>
            <sec id="sec23">
                <title>Underlying data</title>
                <p>Figshare: Dataset - Design of SARS-CoV-2 protein S peptides recognized by the most frequent HLA alleles in the Moroccan population using an immunoinformatics approach. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.25737534.v1">https://doi.org/10.6084/m9.figshare.25737534.v1</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref46">46</xref>
</sup>
                </p>
                <p>The dataset contains the following data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.docx: COVID-19 Wild Type Sequence and Selected Mutations from Various Variants</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Peptide-HLA Class I Binding Affinity Assessment Wild Type (WT) and Mutated (MT) Peptide Binding Scores</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Peptide-HLA Class II Binding Affinity Assessment Wild Type (WT) and Mutated (MT) Peptide Binding Scores</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.docx: SARS-CoV-2 Sequences of different variants retrieved from GISAID Databank</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Table 1. Averages frequency of most common HLA class I and II alleles in the Moroccan population</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Table 2. SARS-CoV-2 S protein mutations isolated from strains of Moroccan patients (n=23)</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Table 3. SARS-CoV-2 S peptides for Class I and II HLA alleles of wild and mutated types</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Table 4. Sequences of the S protein good binders with their HLA alleles</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Table 5. Vaxijen scores (antigenicity) of the predicted MHC class I allele binding peptides.</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data.xlsx: Table 6. Vaxijen scores (antigenicity) of the predicted MHC class II allele binding peptides.</p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
            <sec id="sec24">
                <title>Extended data</title>
                <p>Extended data is not applicable in this instance. All relevant data and materials utilized in our study have been comprehensively outlined in the &#x2018;Materials and Methods&#x2019; section and provided in the Data Availability section. This includes the data uploaded to the designated repository, as specified in the Data Availability section, which encompasses all materials pertinent to our research. We encourage readers to refer to the repository for access to the complete set of data and materials used in this study. Additionally, all servers, databases and methods utilized in this research are outlined in detail within the manuscript. For further inquiries regarding the data or materials, please contact the corresponding author.</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgements</title>
            <p>Not applicable.</p>
        </ack>
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    <sub-article article-type="reviewer-report" id="report309414">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.164583.r309414</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Vieira</surname>
                        <given-names>Gustavo Fioravanti</given-names>
                    </name>
                    <xref ref-type="aff" rid="r309414a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-2380-8059</uri>
                </contrib>
                <aff id="r309414a1">
                    <label>1</label>Bioinformatic Core, Immunogenetics Laboratory, Genetics Department, Biosciences Institute, Post-Graduation Program in Health and Human Development, Federal University of Rio Grande do Sul, Universidade La Salle, Porto Alegre, Canoas, Brazil</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>23</day>
                <month>9</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Vieira GF</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport309414" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.150049.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>While it is very important to design vaccines and immunotherapeutic approaches considering the genetics of the immunized population, some aspects of the work need to be improved or reconsidered before indexing: 
                <list list-type="bullet">
                    <list-item>
                        <p>The introduction is too basic and lacks a stronger foundation with references supporting the influence of HLA on the variation in severity, particularly in relation to COVID.</p>
                    </list-item>
                    <list-item>
                        <p>What was the criterion for the selected alleles? "Most frequent alleles" is too vague.</p>
                    </list-item>
                    <list-item>
                        <p>NetMHCpan is already at version 4.1 for both class I and II MHC.</p>
                    </list-item>
                    <list-item>
                        <p>For class I, it was essential to use nonamers instead of decamers, as nonamers are the standard fragment length for most alleles. Alternatively, the appropriate size should have been used for each different allele.</p>
                    </list-item>
                    <list-item>
                        <p>VaxiJen is suitable for an initial analysis, but it does not include MHC-related information in its prediction, making it insufficient for this case. Ideally, you should use sequences already described as immunogenic in IEDB.</p>
                    </list-item>
                    <list-item>
                        <p>I didn&#x2019;t understand why the toxicity of the peptides was assessed. Is the idea to administer them synthetically?</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Not applicable</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Partly</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>No</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Immunoinformatics</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
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        <sub-article article-type="response" id="comment13331-309414">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Sadki</surname>
                            <given-names>Khalid</given-names>
                        </name>
                        <aff>Mohammed V University in Rabat, Morocco</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>I have no actual or potential conflict of interest in relation to this work.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>12</day>
                    <month>2</month>
                    <year>2025</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Here is our response to all comments. 
                    <list list-type="bullet">
                        <list-item>
                            <p>
                                <underline>1:</underline> &#x00a0;Some references will be added according to the first comment concerning the introduction section.</p>
                        </list-item>
                        <list-item>
                            <p>
                                <underline>2:</underline> We chose to set an allele frequency threshold of 3% based on HLA polymorphism research conducted in Moroccan communities; hence, any allele with a frequency higher than 3% is regarded as more prevalent. The method section will be updated with this information. &#x00a0;</p>
                        </list-item>
                        <list-item>
                            <p>
                                <underline>3: </underline>In our study, we used NetMHCpan v4.0 for MHC class I predictions and NetMHCIIpan v3.2 for class II. After comparing these with version 4.1, we found that the differences in peptide binding affinities were minimal and statistically insignificant for the targeted mutations. The same peptides were consistently identified across both versions, with no impact on their classification or our conclusions. &#x00a0;In the revised version, we will use NetMHCpan v4.1 to update the analyses rather than NetMHCIIpan v3.2.</p>
                        </list-item>
                        <list-item>
                            <p>
                                <underline>4</underline>: Studies have demonstrated that 10-mer peptides form stable complexes with a variety of HLA alleles, including HLA-A02:01, which is common in many populations, even though 9-mers are generally accepted as the standard [Ahn et al., 2024, doi: 10.1016/j.crstbi.2024.100148; Nerli &amp; Sgourakis, 2020, doi: 10.3389/fmedt.2020.553478].&#x00a0;&#x00a0; Additionally, in the context of SARS-CoV-2, 10-mer peptides have been identified as immunogenic epitopes, eliciting robust CD8+ T cell responses [Ahn et al., 2024, doi: 
                                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.crstbi.2024.100148">10.1016/j.crstbi.2024.100148</ext-link>; Abd El-Baky et al., 2023, doi: 
                                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3390/vaccines11030548">10.3390/vaccines11030548</ext-link>; Kiyotani et al., 2020, doi: 
                                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1038/s10038-020-0771-5">10.1038/s10038-020-0771-5</ext-link>; Arshad et al., 2024, doi: 
                                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.heliyon.2024.e24186">10.1016/j.heliyon.2024.e24186</ext-link>; de Moura RR et al., 2021, doi: 10.1136/jclinpath-2020-206946]. Furthermore, the study by Motozono et al. (2015) demonstrated that MHC class I molecules can undergo structural adaptations to accommodate 10-mer peptides, maintaining stable peptide-MHC interactions, which supports their relevance in T-cell-mediated immune responses [Motozono et al., 2015, doi: 10.1074/jbc.M114.622522].&#x00a0;By incorporating 10-mers in our study, we aimed to capture a broader repertoire of potential T-cell epitopes, accounting for the structural and functional diversity of HLA alleles. This approach ensures comprehensive epitope coverage, enhancing the relevance of our findings for diverse populations. Nevertheless, we will also consider 9-mer peptides in future analyses to further optimize epitope selection.</p>
                        </list-item>
                        <list-item>
                            <p>
                                <underline>5:</underline>
                                <underline> </underline>&#x00a0;We agree that VaxiJen is primarily used for initial antigenicity screening and does not incorporate MHC-related information in its predictions. However, studies begin with VaxiJen to assess antigenicity, particularly when dealing with a large number of generated peptides. This helps minimize the inclusion of peptides that might not be antigenic, allowing for a more efficient selection process before conducting more specific immunogenicity and MHC binding predictions. In the revised version, we will also incorporate IEDB to further validate our findings and confirm the immunogenic potential of the selected peptides.</p>
                        </list-item>
                        <list-item>
                            <p>
                                <underline>6: </underline>While the current focus of our study is on identifying immunogenic peptides, evaluating their toxicity using bioinformatics methods is a preliminary step to ensure the peptides are safe for potential future applications, such as synthetic administration in peptide-based vaccines. Toxicity analysis is commonly used in this type of study to support the safety assessment of candidate peptides. This computational analysis helps identify any harmful properties at an early stage, reducing the risk of toxicity in further experimental or therapeutic developments. We will clarify this in the manuscript to explain the rationale for including this assessment.</p>
                        </list-item>
                    </list>
                </p>
            </body>
        </sub-article>
    </sub-article>
</article>
