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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Coronavirus</text>
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            <description>An account of the resource</description>
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                <text>Dominio científico: Coronavirus</text>
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          <name>Title</name>
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              <text>An Engineered Antibody with Broad Protective Efficacy in Murine Models of SARS and COVID-19.</text>
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          <name>Creator</name>
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              <text>Trevor D Scobey, Deli Huang, David Nemazee, Jason S McLellan, Lisa E Gralinski, Ralph S Baric, Longping V Tse, C Garrett Rappazzo, Chengzi I Kaku, Daniel Wrapp, Mrunal Sakharkar, Laura M Deveau, Thomas J Yockachonis, Andrew S Herbert, Michael B Battles, Cecilia M O'Brien, Michael E Brown, James C Geoghegan, Jonathan Belk, Linghang Peng, Linlin Yang, Dennis R Burton, John M Dye, James E Voss, Bronwyn M Gunn, Laura M Walker</text>
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              <text>The recurrent zoonotic spillover of coronaviruses (CoVs) into the human population underscores the need for broadly active countermeasures. Here, we employed a directed evolution approach to engineer three SARS-CoV-2 antibodies for enhanced neutralization breadth and potency. One of the affinity-matured variants, ADG-2, displays strong binding activity to a large panel of sarbecovirus receptor binding domains (RBDs) and neutralizes representative epidemic sarbecoviruses with remarkable potency. Structural and biochemical studies demonstrate that ADG-2 employs a unique angle of approach to recognize a highly conserved epitope overlapping the receptor binding site. In murine models of SARS-CoV and SARS-CoV-2 infection, passive transfer of ADG-2 provided complete protection against respiratory burden, viral replication in the lungs, and lung pathology. Altogether, ADG-2 represents a promising broad-spectrum therapeutic candidate for the treatment and prevention of SARS-CoV-2 and future emerging SARS-like CoVs.</text>
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          <name>Date</name>
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              <text>2020</text>
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          <name>Identifier</name>
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              <text>10.1101/2020.11.17.385500</text>
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          <name>Source</name>
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              <text>bioRxiv : the preprint server for biology</text>
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