<?xml version='1.0' encoding='utf-8'?>
<?xml-stylesheet type="text/xsl" href="/v2/static/oai2.xsl"?>
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd">
  <responseDate>2026-10-13T22:12:36Z</responseDate>
  <request identifier="oai:figshare.com:article/33920581" metadataPrefix="oai_dc" verb="GetRecord">https://api.figshare.com/v2/oai</request>
  <GetRecord>
    <record>
      <header>
        <identifier>oai:figshare.com:article/33920581</identifier>
        <datestamp>2026-09-18T05:39:11Z</datestamp>
        <setSpec>category_696</setSpec>
        <setSpec>portal_316</setSpec>
        <setSpec>item_type_3</setSpec>
        <setSpec>month_year_09_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Table 1_AI-guided epitope engineering of a SARS-CoV-2 spike antigen for broad sarbecovirus neutralization.docx</dc:title>
          <dc:creator>Alexandru Odainic (12225710)</dc:creator>
          <dc:creator>Ioannis Vardaxis (17012379)</dc:creator>
          <dc:creator>Matheus Ferraz (23143355)</dc:creator>
          <dc:creator>Katrin E Wiese (25070230)</dc:creator>
          <dc:creator>Lisette A H M Cornelissen (25070233)</dc:creator>
          <dc:creator>Akhilesh Sharma (8800444)</dc:creator>
          <dc:creator>Richard Stratford (6708653)</dc:creator>
          <dc:creator>Trevor Clancy (235169)</dc:creator>
          <dc:creator>Kaïdre Bendjama (10034978)</dc:creator>
          <dc:subject>Genetic Immunology</dc:subject>
          <dc:subject>artificial intelligence</dc:subject>
          <dc:subject>broadly protective</dc:subject>
          <dc:subject>coronavirus</dc:subject>
          <dc:subject>immunoinformatics</dc:subject>
          <dc:subject>vaccine</dc:subject>
          <dc:description>&lt;p&gt;The rapid evolution of SARS-CoV-2 and the ongoing risk of zoonotic spillover highlight the need for vaccines that provide broad protection beyond strain-specific immunity. Here, we present a structure-guided, AI-enabled strategy for rational antigen design that enhances cross-reactive B-cell epitope recognition across betacoronaviruses. By integrating comparative sequence analysis with conformational epitope prediction, we identified conserved epitope hotspots within the Spike receptor-binding domain and introduced targeted motif-level substitutions into a SARS-CoV-2 BA.2 backbone. Engineered Spike immunogens, delivered as mRNA-lipid nanoparticle vaccines, elicited robust antibody responses in mice and demonstrated broad neutralizing activity against antigenically diverse SARS-CoV-2 variants, including BA.5 and XBB.1.5, as well as zoonotic sarbecoviruses. Selected designs reached neutralisation breadth comparable to an Omicron-adapted clinical benchmark for shared SARS-CoV-2 antigens, while extending neutralising activity to divergent zoonotic sarbecoviruses. These findings show that minimal, structure-guided epitope remodeling can enhance the presentation of conserved epitopes and improve antibody breadth, providing a generalizable framework for designing vaccines resilient to viral evolution and future pandemic threats.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-18T05:39:11Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fimmu.2026.1919664.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/Table_1_AI-guided_epitope_engineering_of_a_SARS-CoV-2_spike_antigen_for_broad_sarbecovirus_neutralization_docx/33920581</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
  </GetRecord>
</OAI-PMH>
