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<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group>
<journal-title>PLOS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher>
<publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, CA USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.1371/journal.pone.0237295</article-id>
<article-id pub-id-type="publisher-id">PONE-D-20-13266</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Glycobiology</subject><subj-group><subject>Glycosylation</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteins</subject><subj-group><subject>Post-translational modification</subject><subj-group><subject>Glycosylation</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Organisms</subject><subj-group><subject>Viruses</subject><subj-group><subject>RNA viruses</subject><subj-group><subject>Coronaviruses</subject><subj-group><subject>SARS coronavirus</subject><subj-group><subject>SARS CoV 2</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Microbiology</subject><subj-group><subject>Medical microbiology</subject><subj-group><subject>Microbial pathogens</subject><subj-group><subject>Viral pathogens</subject><subj-group><subject>Coronaviruses</subject><subj-group><subject>SARS coronavirus</subject><subj-group><subject>SARS CoV 2</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Pathology and laboratory medicine</subject><subj-group><subject>Pathogens</subject><subj-group><subject>Microbial pathogens</subject><subj-group><subject>Viral pathogens</subject><subj-group><subject>Coronaviruses</subject><subj-group><subject>SARS coronavirus</subject><subj-group><subject>SARS CoV 2</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Organisms</subject><subj-group><subject>Viruses</subject><subj-group><subject>Viral pathogens</subject><subj-group><subject>Coronaviruses</subject><subj-group><subject>SARS coronavirus</subject><subj-group><subject>SARS CoV 2</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Biochemical simulations</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Computational biology</subject><subj-group><subject>Biochemical simulations</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Medical conditions</subject><subj-group><subject>Infectious diseases</subject><subj-group><subject>Viral diseases</subject><subj-group><subject>COVID 19</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteins</subject><subj-group><subject>Protein interactions</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Molecular biology</subject><subj-group><subject>Macromolecular structure analysis</subject><subj-group><subject>Protein structure</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteins</subject><subj-group><subject>Protein structure</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteins</subject><subj-group><subject>Protein domains</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Cell biology</subject><subj-group><subject>Cell physiology</subject><subj-group><subject>Cell binding</subject></subj-group></subj-group></subj-group></subj-group></article-categories>
<title-group>
<article-title>Development and simulation of fully glycosylated molecular models of ACE2-Fc fusion proteins and their interaction with the SARS-CoV-2 spike protein binding domain</article-title>
<alt-title alt-title-type="running-head">Simulating glycosylated ACE2-Fc fusion proteins with SARS-CoV-2 spike fragments</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Bernardi</surname>
<given-names>Austen</given-names>
</name>
<role content-type="https://casrai.org/credit/">Investigation</role>
<role content-type="https://casrai.org/credit/">Methodology</role>
<role content-type="https://casrai.org/credit/">Software</role>
<role content-type="https://casrai.org/credit/">Visualization</role>
<role content-type="https://casrai.org/credit/">Writing – original draft</role>
<role content-type="https://casrai.org/credit/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Huang</surname>
<given-names>Yihan</given-names>
</name>
<role content-type="https://casrai.org/credit/">Investigation</role>
<role content-type="https://casrai.org/credit/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff002"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Harris</surname>
<given-names>Bradley</given-names>
</name>
<role content-type="https://casrai.org/credit/">Investigation</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Xiong</surname>
<given-names>Yongao</given-names>
</name>
<role content-type="https://casrai.org/credit/">Formal analysis</role>
<role content-type="https://casrai.org/credit/">Writing – original draft</role>
<role content-type="https://casrai.org/credit/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Nandi</surname>
<given-names>Somen</given-names>
</name>
<role content-type="https://casrai.org/credit/">Conceptualization</role>
<role content-type="https://casrai.org/credit/">Funding acquisition</role>
<role content-type="https://casrai.org/credit/">Methodology</role>
<role content-type="https://casrai.org/credit/">Project administration</role>
<role content-type="https://casrai.org/credit/">Supervision</role>
<role content-type="https://casrai.org/credit/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff003"><sup>3</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>McDonald</surname>
<given-names>Karen A.</given-names>
</name>
<role content-type="https://casrai.org/credit/">Conceptualization</role>
<role content-type="https://casrai.org/credit/">Funding acquisition</role>
<role content-type="https://casrai.org/credit/">Methodology</role>
<role content-type="https://casrai.org/credit/">Project administration</role>
<role content-type="https://casrai.org/credit/">Supervision</role>
<role content-type="https://casrai.org/credit/">Writing – original draft</role>
<role content-type="https://casrai.org/credit/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff003"><sup>3</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes" xlink:type="simple">
<contrib-id authenticated="true" contrib-id-type="orcid">http://orcid.org/0000-0001-9946-3846</contrib-id>
<name name-style="western">
<surname>Faller</surname>
<given-names>Roland</given-names>
</name>
<role content-type="https://casrai.org/credit/">Conceptualization</role>
<role content-type="https://casrai.org/credit/">Funding acquisition</role>
<role content-type="https://casrai.org/credit/">Methodology</role>
<role content-type="https://casrai.org/credit/">Project administration</role>
<role content-type="https://casrai.org/credit/">Supervision</role>
<role content-type="https://casrai.org/credit/">Writing – original draft</role>
<role content-type="https://casrai.org/credit/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
</contrib-group>
<aff id="aff001"><label>1</label> <addr-line>Chemical Engineering, UC Davis, Davis, CA, United States of America</addr-line></aff>
<aff id="aff002"><label>2</label> <addr-line>Materials Science and Engineering, UC Davis, Davis, CA, United States of America</addr-line></aff>
<aff id="aff003"><label>3</label> <addr-line>Global HealthShare Initiative, UC Davis, Davis, CA, United States of America</addr-line></aff>
<contrib-group>
<contrib contrib-type="editor" xlink:type="simple">
<name name-style="western">
<surname>Millet</surname>
<given-names>Oscar</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"/>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>CIC bioGUNE, SPAIN</addr-line></aff>
<author-notes>
<fn fn-type="conflict" id="coi001">
<p>The authors have declared that no competing interests exist.</p>
</fn>
<corresp id="cor001">* E-mail: <email xlink:type="simple">rfaller@ucdavis.edu</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>5</day>
<month>8</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="collection">
<year>2020</year>
</pub-date>
<volume>15</volume>
<issue>8</issue>
<elocation-id>e0237295</elocation-id>
<history>
<date date-type="received">
<day>5</day>
<month>5</month>
<year>2020</year>
</date>
<date date-type="accepted">
<day>23</day>
<month>7</month>
<year>2020</year>
</date>
</history>
<permissions>
<copyright-year>2020</copyright-year>
<copyright-holder>Bernardi et al</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="info:doi/10.1371/journal.pone.0237295"/>
<abstract>
<p>We develop fully glycosylated computational models of ACE2-Fc fusion proteins which are promising targets for a COVID-19 therapeutic. These models are tested in their interaction with a fragment of the receptor-binding domain (RBD) of the Spike Protein S of the SARS-CoV-2 virus, via atomistic molecular dynamics simulations. We see that some ACE2 glycans interact with the S fragments, and glycans are influencing the conformation of the ACE2 receptor. Additionally, we optimize algorithms for protein glycosylation modelling in order to expedite future model development. All models and algorithms are openly available.</p>
</abstract>
<funding-group>
<award-group id="award001">
<funding-source>
<institution-wrap>
<institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/100007707</institution-id>
<institution>University of California, Davis</institution>
</institution-wrap>
</funding-source>
<award-id>COVID-19 Research Accelerator Funding Track</award-id>
</award-group>
<funding-statement>BH, KAM, RF, and SN are partially supported by a CRAFT award (COVID-19 Research Accelerator Funding Track) by the University of California Davis (<ext-link ext-link-type="uri" xlink:href="https://covid19research.ucdavis.edu/tags/craft" xlink:type="simple">https://covid19research.ucdavis.edu/tags/craft</ext-link>). YX was supported by NASA under grant or cooperative agreement award number NNX17AJ31G. KAM and SN were partially supported by NASA Space Technology Research (award number NNX17AJ31G) and by the Translational Research Institute through NASA (grant number NNX16AO69A). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration (NASA) or the Translational Research Institute for Space Health (TRISH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts>
<fig-count count="5"/>
<table-count count="1"/>
<page-count count="12"/>
</counts>
<custom-meta-group>
<custom-meta id="data-availability">
<meta-name>Data Availability</meta-name>
<meta-value>Simulation data is added in Supplementary information and available for download on the <ext-link ext-link-type="uri" xlink:href="http://datadryad.org" xlink:type="simple">datadryad.org</ext-link> website Analysis tool are available on github.</meta-value>
</custom-meta>
<custom-meta id="outbreaks">
<meta-name>Outbreaks</meta-name>
<meta-value>COVID-19</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="sec001" sec-type="intro">
<title>Introduction</title>
<p>As of June 29, 2020 more than 10 Million people have been confirmed to be infected with coronavirus disease 2019 (COVID-19) which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This zoonotic pandemic has disrupted society worldwide on a peacetime-unprecedented scale. It also spurred a wide range of scientific endeavors to attack the various aspects of this disease. As the disease spreads there is a critical need for tools that enable the strategic design of biopharmaceutical countermeasures. We are here addressing computationally a molecular approach to aid in the design of a specific class of potential COVID-19 countermeasures.</p>
<p>The genomic sequence of the virus responsible for COVID-19, SARS-CoV-2, was made available in January 2020 [<xref ref-type="bibr" rid="pone.0237295.ref001">1</xref>], providing critical information on the primary amino acid sequences of potential targets. A particularly important target is the SARS-CoV-2 spike (S) protein that is responsible for the first step in the viral infection process, binding to human cells via the angiotensin converting enzyme 2 (hACE2) receptor. The conserved expression and interaction of ACE2 indicates a wide range of hosts (human and non-human) for SARS-CoV-2 [<xref ref-type="bibr" rid="pone.0237295.ref002">2</xref>]. The S protein contains two domains S1 and S2 on each monomer. It is a homotrimer with each monomer comprised of 1281 amino acids. The monomers are expected to be highly glycosylated with 22 N-linked glycosylation sequons and 4 O-linked predicted glycosylation sites [<xref ref-type="bibr" rid="pone.0237295.ref003">3</xref>], although only 16 N-linked glycosylation sites were observed in a cryo-EM map of S produced in HEK293F cells [<xref ref-type="bibr" rid="pone.0237295.ref004">4</xref>]. Very recently, Watanabe et al. performed site-specific glycoform analysis of full-length trimeric S protein made recombinantly in transfected HEK293F cells [<xref ref-type="bibr" rid="pone.0237295.ref005">5</xref>]. Their analysis showed high occupancy at all 22 sites, with about 14 sites classified as complex, 2 sites as oligomannose, and the remaining sites containing mixtures of oligomannose, hybrid and complex glycan structures. Seven of the sites with complex glycoforms, including the 2 sites on the RBD, also had a high degree (&gt;95%) of core fucosylation. Viral coat proteins are often glycosylated which helps pathogens evade the host immune system, modulate access of host proteases, and can enhance cellular attachment through modification of protein structure and/or direct participation at the viral coat protein/cell receptor interface. These glycans are, however, only partially resolved in the experimental structure such that a computational approach is helpful to predict their behavior.</p>
<p>The human ACE2 protein is a 788 amino acid integral membrane protein with seven N-linked glycosylation sites in the extracellular domain. The binding kinetics between the SARS-CoV-2 spike protein and the hACE2 receptor will depend on the 3D structures of both molecules and their molecular interactions which may be impacted by glycosylation [<xref ref-type="bibr" rid="pone.0237295.ref006">6</xref>–<xref ref-type="bibr" rid="pone.0237295.ref008">8</xref>], as has been observed for other glycosylated viral spike proteins and their human receptors. Knowledge of the spike protein and ACE2 amino acid sequences have led to the commercial availability of the spike protein, ACE2, and various fragments of these, with and without purification/fusion tags, produced recombinantly in various expression hosts including Human embryonic kidney cells (HEK293), insect cells, Chinese Hamster Ovary cells (CHO), and <italic>E</italic>. <italic>coli</italic>. While the availability of recombinant sources for S and ACE2 glycoproteins have greatly contributed to our understanding of the structure and interactions between these proteins, it is important to recognize that glycosylation of recombinant S and ACE proteins will depend on the host cell [<xref ref-type="bibr" rid="pone.0237295.ref009">9</xref>], the recombinant protein, as well as production [<xref ref-type="bibr" rid="pone.0237295.ref010">10</xref>, <xref ref-type="bibr" rid="pone.0237295.ref011">11</xref>] and purification methods [<xref ref-type="bibr" rid="pone.0237295.ref012">12</xref>]. As molecular models and molecular dynamics simulations can describe the interactions of proteins with glycans and the modulation of protein structure by glycans [<xref ref-type="bibr" rid="pone.0237295.ref013">13</xref>, <xref ref-type="bibr" rid="pone.0237295.ref014">14</xref>] they are powerful tools to assess the significance of glycosylation on 3D structure and binding site interactions between the SARS-CoV-2 spike protein and the human ACE2 receptor, and to design novel biotherapeutics including optimizing glycosylation.</p>
<p>A promising strategy for the design of COVID-19 therapeutic proteins is a fusion of the extracellular domain of ACE2, the human receptor for SARS-CoV-2, with the Fc region of human immunoglobulin, IgG1, by a linker separating the two domains [<xref ref-type="bibr" rid="pone.0237295.ref015">15</xref>]. The neutralization strategy behind ACE2-Fc is shown in <xref ref-type="fig" rid="pone.0237295.g001">Fig 1</xref> [<xref ref-type="bibr" rid="pone.0237295.ref015">15</xref>]. This therapeutic design is often called an immunoadhesin, a chimeric protein combining the ligand-binding region of the cell receptor with the constant domain of an immunoglobulin [<xref ref-type="bibr" rid="pone.0237295.ref016">16</xref>]. These chimeric molecules form dimers through disulfide bonds between Fc domains; this bivalency increases the affinity for the ligand. The human ACE2 receptor has been shown to be the primary receptor that SARS-CoV-2 uses for entry into and infection of human cells [<xref ref-type="bibr" rid="pone.0237295.ref017">17</xref>, <xref ref-type="bibr" rid="pone.0237295.ref018">18</xref>], although the binding site is distinct from the catalytic domain of ACE2. With an ACE2-Fc immunoadhesin the ACE2 portion can act as a circulating “bait or decoy” to bind the SARS-CoV-2 spike protein preventing it from entering human cells while the Fc region confers longer circulatory half-life, provides effector functions of the immune system to clear the virus, and allows simple well-established purification using Protein A affinity chromatography. Immunoadhesins are a distinct class of antivirals that can be used prophylactically as well as post-infection and differ from both vaccines and antibodies. Unlike vaccines, they are not intended to elicit an immune response to the viral infection, and unlike antibody therapies, their design is greatly simplified since once the cellular receptor for viral entry is identified the immunoadhesin can be quickly designed and produced.</p>
<fig id="pone.0237295.g001" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0237295.g001</object-id>
<label>Fig 1</label>
<caption>
<title>Proposed strategy for SARS-CoV-2 neutralization by ACE2-Fc immunoadhesin.</title>
<p>ACE2-Fc binds to the spike (S) protein on the virus and blocks binding to the human cellular receptor ACE2, preventing cellular entrance of SARS-CoV-2.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0237295.g001" xlink:type="simple"/>
</fig>
<p>This strategy also precludes the coronavirus mutating to escape binding with the ACE2-Fc protein, as it would also lose binding affinity to the native ACE2 human cell receptor resulting in a less pathogenic virus. The re-emergent SARS-CoV-1 virus in 2003–2004 had a lower affinity for human ACE2 resulting in less severe infection and no secondary transmissions [<xref ref-type="bibr" rid="pone.0237295.ref019">19</xref>]. In this strategy the exogenous ACE2 would compensate for decreased ACE2 levels in the lungs during infection, contributing to the treatment of acute respiratory distress, and potentially reduce inflammation and reactive oxygen species in the lung [<xref ref-type="bibr" rid="pone.0237295.ref020">20</xref>]. Most importantly, recombinant ACE2-Fc fusion proteins, with native ACE2 catalytic activity as well as a mutant version with lower ACE2 catalytic activity, produced using transfection of HEK293, have shown high affinity binding to the SARS-CoV-2 spike protein and to potently neutralize SARS-CoV-2 <italic>in vitro</italic> [<xref ref-type="bibr" rid="pone.0237295.ref021">21</xref>]. Simulations are an ideal tool to optimize such a construct and guide the experimental production of ACE2-Fc.</p>
<p>Glycans are branched, flexible chains of carbohydrates that explore a much wider range of conformations at equilibrium conditions than the protein chain itself as the latter is typically not dynamically changing strongly from its folded form as that would affect its functionality. The faster dynamics of glycans complicates the structural and conformational characterization of glycans in laboratory experiments [<xref ref-type="bibr" rid="pone.0237295.ref022">22</xref>]. In atomistic molecular dynamics (MD) simulations, glycan conformations can be straight-forwardly analyzed to obtain structural information, as glycan dynamics are much closer to the computational timescale than the protein dynamics. However, neighboring glycans can interact with each other and essentially lock each other in which can lead to very slow equilibration into the correct conformation [<xref ref-type="bibr" rid="pone.0237295.ref013">13</xref>]. Therefore, algorithms are needed to generate realistic glycan configurations as glycans are regularly not fully resolved experimentally. Consequently, only a few simulations of related fully glycosylated proteins available [<xref ref-type="bibr" rid="pone.0237295.ref023">23</xref>–<xref ref-type="bibr" rid="pone.0237295.ref026">26</xref>] among them recently a proposed glycosylated model of the Spike protein [<xref ref-type="bibr" rid="pone.0237295.ref027">27</xref>]. Very recently a short simulation of the Spike protein with glycosylation has been published which is enabling longer studies [<xref ref-type="bibr" rid="pone.0237295.ref028">28</xref>]. Our group has made significant progress in the field of glycan modeling in recent years [<xref ref-type="bibr" rid="pone.0237295.ref013">13</xref>, <xref ref-type="bibr" rid="pone.0237295.ref014">14</xref>, <xref ref-type="bibr" rid="pone.0237295.ref029">29</xref>].</p>
<p>N-glycan structure is highly heterogeneous, and the relative abundance of glycans depends on the expression system for glycoprotein production. Plant-based transient expression systems are well-suited to produce recombinant ACE2-Fc under the current COVID-19 pandemic given high production speeds. Two glycovariants of ACE2-Fc are simulated in this work: one is targeted for ER retention with high mannose glycoforms, and the second is targeted for secretion with plant complex glycoforms. These glycovariants are currently being expressed and purified at UC Davis.</p>
<p>In order to properly understand the interaction between the spike protein and the variant ACE2 receptors bound to its fusion partner the glycosylation of both entities needs to be taken into account. The few existing computational studies of ACE2 interaction with the spike protein we are aware of are using aglycosylated proteins [<xref ref-type="bibr" rid="pone.0237295.ref030">30</xref>–<xref ref-type="bibr" rid="pone.0237295.ref032">32</xref>]. Also, molecular docking studies have been performed with the older related SARS-CoV-1 virus protein implicated in the SARS epidemic in the early 2000s [<xref ref-type="bibr" rid="pone.0237295.ref033">33</xref>]. We develop <italic>in silico</italic> models to predict the 3D structure of two glycosylated ACE2-Fc variants. Additionally, we evaluate the interactions between these two ACE2-Fc variants and a glycosylated spike protein fragment (SpFr) which contains the receptor binding domain of the SARS-CoV-2 spike protein.</p>
</sec>
<sec id="sec002" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="sec003">
<title>Sequences and initial structure</title>
<p>ACE2-Fc is a homodimer of ACE2 bound to Fc via a synthetic linker. Two sequence variants are used in this work to model ACE2-Fc. The ACE2 and Fc domains N- and C-terminal residues for both variants, respectively, are as follows: ACE2, 18Q-740S (NCBI ID: NP_001358344.1); Fc, 109C-330K (UniProt ID: P01857). Variant 1 (<xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>; 960 amino acids) contains a C-terminal SEKDEL tag, which is used to express predominantly ER-retained proteins with high-mannose glycoforms in plant-based expression systems. Variant 2 (<xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>; 954 amino acids) does not use a C-terminal SEKDEL tag, and will express standard plant glycoforms in plant-based expression systems. Variant 2 has two mutations: H357N and H361N. These mutations are used to deactivate the standard function of ACE2, by preventing the coordination of Zn<sup>2+</sup> in the active site [<xref ref-type="bibr" rid="pone.0237295.ref021">21</xref>]. The ACE2-Fc variants contain 18 disulfide bonds, with 4 of them being interchain. S1 Table in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref> describes the disulfide linkages. The variants also contain 8 N-glycosylation sites per monomer. Each peptidase domain of the ACE2-Fc variants is capable of binding one SARS-CoV-2 SpFr (<xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>; 183 amino acids), which contains one glycosylation site. The ACE2-Fc/SpFr structure is depicted in <xref ref-type="fig" rid="pone.0237295.g002">Fig 2</xref>. Zoomed views of the ACE2/SpFr interface are shown in S4 Fig in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>. The coordinated Zn<sup>2+</sup> site is shown in S1 Fig in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>. All 3D structures are rendered with VMD [<xref ref-type="bibr" rid="pone.0237295.ref034">34</xref>].</p>
<fig id="pone.0237295.g002" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0237295.g002</object-id>
<label>Fig 2</label>
<caption>
<title>Infographic of the ACE2-Fc variant 1 homodimer bound to two SpFr.</title>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0237295.g002" xlink:type="simple"/>
</fig>
</sec>
<sec id="sec004">
<title>Simulated systems</title>
<p>ACE2-Fc variant 1 will express high-mannose type glycans when synthesized in plants, while variant 2 will express standard plant glycans. Additionally, SARS-CoV-2 SpFr will exhibit its own glycosylation depending on the host cell; here we assume common mammalian-like glycosylation. Our simulations employed uniform glycosylation profiles to approximate these glycosylation profiles. ACE2-Fc variant 1 is fully glycosylated with Man8 glycans, variant 2 is fully glycosylated with GnGnXF3 glycans the latter is consistent with a recent experimental study [<xref ref-type="bibr" rid="pone.0237295.ref035">35</xref>], and the SpFr is glycosylated with ANaF<sup>6</sup> [<xref ref-type="bibr" rid="pone.0237295.ref036">36</xref>]. <xref ref-type="fig" rid="pone.0237295.g003">Fig 3</xref> shows these glycans using the Consortium of Functional Glycomics nomenclature.</p>
<fig id="pone.0237295.g003" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0237295.g003</object-id>
<label>Fig 3</label>
<caption>
<title>Glycans used in the simulated systems.</title>
<p>All structures were built using GlycanBuilder [<xref ref-type="bibr" rid="pone.0237295.ref037">37</xref>].</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0237295.g003" xlink:type="simple"/>
</fig>
<p>Four systems containing ACE2-Fc variants were simulated in this work. The first system contains ACE2-Fc variant 1 with Man8 glycans. The second system contains ACE2-Fc variant 2 with GnGnXF<sup>3</sup> glycans. The third and fourth systems are the immunoadhesins of the first and second systems with the SARS-CoV-2 SpFr bound, respectively. The SpFr is always glycosylated with ANaF<sup>6</sup>. <xref ref-type="table" rid="pone.0237295.t001">Table 1</xref> summarizes the simulated systems.</p>
<table-wrap id="pone.0237295.t001" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0237295.t001</object-id>
<label>Table 1</label> <caption><title>Description of simulated systems.</title></caption>
<alternatives>
<graphic id="pone.0237295.t001g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0237295.t001" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="left">System ID</th>
<th align="left">ACE2-Fc Sequence</th>
<th align="left">ACE2-Fc Glycosylation</th>
<th align="left">SpFr bound?</th>
<th align="left">ACE2/SpFr ref. PDB</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">AF<sup>M8</sup></td>
<td align="left">Variant 1</td>
<td align="left">Man8</td>
<td align="left">no</td>
<td align="left">6M17</td>
</tr>
<tr>
<td align="left">AF<sup>GG</sup></td>
<td align="left">Variant 2</td>
<td align="left">GnGnXF<sup>3</sup></td>
<td align="left">no</td>
<td align="left">6M17</td>
</tr>
<tr>
<td align="left">AF<sup>M8</sup>/SpFr</td>
<td align="left">Variant 1</td>
<td align="left">Man8</td>
<td align="left">yes</td>
<td align="left">6M18</td>
</tr>
<tr>
<td align="left">AF<sup>GG</sup>/SpFr</td>
<td align="left">Variant 2</td>
<td align="left">GnGnXF<sup>3</sup></td>
<td align="left">yes</td>
<td align="left">6M18</td>
</tr>
</tbody>
</table>
</alternatives>
</table-wrap>
<p>This work is largely made possible due to the recent cryogenic electron microscopy work that resolves the ACE2-B<sup>0</sup>AT1 and ACE2-B<sup>0</sup>AT1/SpFr structures, corresponding to PDB codes 6M18 and 6M17, respectively [<xref ref-type="bibr" rid="pone.0237295.ref038">38</xref>]. The ACE2 and ACE2/SpFr domains were taken from these structures and fused to the Fc domain (PDB 3SGJ) [<xref ref-type="bibr" rid="pone.0237295.ref039">39</xref>]. The Zn<sup>2+</sup> and coordinating residues in 6M17 and 6M18 are poorly coordinated in these structures. The conformation of these residues along with a coordinating water were instead taken from PDB 1R42 [<xref ref-type="bibr" rid="pone.0237295.ref040">40</xref>]. Histidine protonation states for each system were determined using Reduce [<xref ref-type="bibr" rid="pone.0237295.ref041">41</xref>], and are summarized in S2 Table in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>.</p>
</sec>
<sec id="sec005">
<title>Simulation procedure</title>
<p>The simulation procedure includes the following steps:</p>
<list list-type="order">
<list-item><p>Fuse ACE2 with Fc to ACE2-Fc using Modeller [<xref ref-type="bibr" rid="pone.0237295.ref042">42</xref>]</p></list-item>
<list-item><p>Model Zn<sup>2+</sup> and coordinating residues with MCPB.py [<xref ref-type="bibr" rid="pone.0237295.ref043">43</xref>]</p></list-item>
<list-item><p>Attach glycans using <ext-link ext-link-type="uri" xlink:href="http://glycam.org" xlink:type="simple">glycam.org</ext-link> [<xref ref-type="bibr" rid="pone.0237295.ref044">44</xref>]</p></list-item>
<list-item><p>Merge structures from 2. and 3. using <ext-link ext-link-type="uri" xlink:href="http://github.com/austenb28/MCPB_Glycam_merge" xlink:type="simple">github.com/austenb28/MCPB_Glycam_merge</ext-link> [<xref ref-type="bibr" rid="pone.0237295.ref045">45</xref>]</p></list-item>
<list-item><p>Generate topology files using AmberTools [<xref ref-type="bibr" rid="pone.0237295.ref043">43</xref>]</p></list-item>
<list-item><p>Convert topology files to Gromacs format using Acpype [<xref ref-type="bibr" rid="pone.0237295.ref029">29</xref>, <xref ref-type="bibr" rid="pone.0237295.ref046">46</xref>]</p></list-item>
<list-item><p>Perform rigid energy minimization (EM) of glycans using <ext-link ext-link-type="uri" xlink:href="http://github.com/austenb28/GlyRot" xlink:type="simple">github.com/austenb28/GlyRot</ext-link> [<xref ref-type="bibr" rid="pone.0237295.ref047">47</xref>]</p></list-item>
<list-item><p>Perform EM (emtol = 1000 kJ/mol/nm)</p></list-item>
<list-item><p>Solvate and add ions</p></list-item>
<list-item><p>Perform 10 ps constant volume (NVT) (dt = 0.2 fs, T = 310 K)</p></list-item>
<list-item><p>Perform EM (emtol = 1000 kJ/mol/nm)</p></list-item>
<list-item><p>Perform 100 ps NVT (dt = 2 fs, T = 310 K)</p></list-item>
<list-item><p>Perform 100 ps constant pressure (NPT) (dt = 2 fs, T = 310 K, P = 1 atm)</p></list-item>
<list-item><p>Perform 75 ns production NPT (dt = 2 fs, T = 310 K, P = 1 atm)</p></list-item>
</list>
<p>Steps 2 and 4 are only required for AF<sup>M8</sup> and AF<sup>M8</sup>/SpFr, since they contain the coordinated Zn<sup>2+</sup> sites. Steps 4 and 7 exhibit new, publicly available software under GNU General Public Licenses. GlyRot has previously been used to model glycosylated butyrylcholinesterase and CMG2-Fc [<xref ref-type="bibr" rid="pone.0237295.ref013">13</xref>, <xref ref-type="bibr" rid="pone.0237295.ref014">14</xref>]. Forcefield topologies were generated using the AmberFF14SB [<xref ref-type="bibr" rid="pone.0237295.ref048">48</xref>]forcefield for protein atoms, the Glycam06-j [<xref ref-type="bibr" rid="pone.0237295.ref049">49</xref>] forcefield for glycan atoms, and the SPC/E water model [<xref ref-type="bibr" rid="pone.0237295.ref050">50</xref>]. Steps 8 through 14 are performed using the Gromacs suite [<xref ref-type="bibr" rid="pone.0237295.ref051">51</xref>–<xref ref-type="bibr" rid="pone.0237295.ref053">53</xref>]. Systems were solvated in rectangular boxes such the minimum distance between the solute and periodic boundary is 1.2 nm. A rectangular box (for size see S3 Table in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>) was found to be sufficient for 75 ns; longer simulations may require a larger cubic box if the solute rotates significantly. A reduced timestep NVT in step 10 is required to relax solute-solvent contacts. Steps 10–13 used position restraints on the protein atoms. All simulations were performed at 310K and 1 atm with the Velocity Rescale thermostat [<xref ref-type="bibr" rid="pone.0237295.ref054">54</xref>] and Parinello-Rahman barostat [<xref ref-type="bibr" rid="pone.0237295.ref055">55</xref>] using time constants of 0.1 ps and 2 ps, respectively. All water bonds are constrained with SETTLE [<xref ref-type="bibr" rid="pone.0237295.ref056">56</xref>]; all other bonds are constrained with LINCS [<xref ref-type="bibr" rid="pone.0237295.ref057">57</xref>]. A 1 nm cutoff was used for short-range nonbonded interactions. Particle Mesh Ewald was used to model long-range electrostatics [<xref ref-type="bibr" rid="pone.0237295.ref058">58</xref>]. S3 Table in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref> contains additional information on system sizes and solvation. Each system was simulated using one compute node with 16 cores. Simulations averaged 2.9 ns/day for systems without the SpFr, and 2.0 ns/day for systems with the SpFr.</p>
</sec>
</sec>
<sec id="sec006" sec-type="conclusions">
<title>Results and discussion</title>
<p><xref ref-type="fig" rid="pone.0237295.g004">Fig 4</xref> shows the starting configurations generated as described above (left) and the configurations after MD for 75 ns (right) of all simulated systems. Systems of this size will not fully equilibrate in 75 ns, but evidence of structural stability and concerted motion can still be observed. This is in agreement with a recent equilibration study of a fully glycosylated Spike protein [<xref ref-type="bibr" rid="pone.0237295.ref028">28</xref>]. All systems exhibit varying length of the flexible linker domain between ACE2 and Fc during simulation. The domain separation can be quantified by analyzing the center of mass distance between the ACE2 and Fc ordered domains, shown in S2 Fig in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>. AF<sup>M8</sup> and AF<sup>M8</sup>/SpFr exhibit clearly more shortening of the linker domain than AF<sup>GG</sup> and AF<sup>GG</sup>/SpFr, possibly due to the difference in glycosylation in the Fc domain, which is closest to the flexible linker region. AF<sup>M8</sup>/SpFr has the shortest distance between the ACE2 and Fc domains after 75 ns, which is consistent with its final configuration shown in <xref ref-type="fig" rid="pone.0237295.g004">Fig 4</xref>. In the AF<sup>M8</sup>/SpFr and AF<sup>GG</sup>/SpFr systems, ACE2 glycans near the ACE2/SpFr interface form contacts across the binding interface, indicating that glycosylation may significantly affect binding kinetics. Additionally, glycans on SpFr that were initially oriented away from the protein are reoriented towards ACE2 after 75 ns. The structure of the ordered domains of ACE2-Fc and SpFr appear to retain structural stability. As expected, the glycans, on the other hand, show significant reorientation, as the configurational dynamics of glycans is faster than proteins [<xref ref-type="bibr" rid="pone.0237295.ref013">13</xref>].</p>
<fig id="pone.0237295.g004" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0237295.g004</object-id>
<label>Fig 4</label>
<caption>
<title/>
<p>Initial (left) and 75 ns simulated (right) configurations of all systems.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0237295.g004" xlink:type="simple"/>
</fig>
<p>To quantitatively assess structural stability, the root mean square deviation (RMSD) of the ordered domains of ACE2-Fc are shown in <xref ref-type="fig" rid="pone.0237295.g005">Fig 5</xref>. All profiles exhibit dynamics near or below 2.5 Å, indicating no major unfolding events have occurred. Conformational trending occurs when the RMSD increases from the initial and decreases towards the final. Conformational trending is evident in the ACE2 domain of all systems. Conformational trending is less evident for the Fc domains, except for the AF<sup>GG</sup>/SpFr system, which exhibits significant conformational trending during the first 20 ns. This difference could indicate that GnGnXF<sup>3</sup> glycosylation in the Fc domain of the AF<sup>GG</sup>/SpFr promoted a conformational change in the Fc domain. Backbone RMSD profiles for the SpFr are provided in S3 Fig in <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>. The SpFr domains show RMSD profiles with significant conformational trending, potentially due to contacts with nearby glycans.</p>
<fig id="pone.0237295.g005" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0237295.g005</object-id>
<label>Fig 5</label>
<caption>
<title/>
<p><bold>Backbone RMSD profiles of ACE2 (top) and Fc (bottom) ordered domains referenced to initial and final simulation configurations.</bold> ACE2: residues 4–707. Fc: residues 745–950. (see <xref ref-type="supplementary-material" rid="pone.0237295.s001">S1 File</xref>).</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0237295.g005" xlink:type="simple"/>
</fig>
</sec>
<sec id="sec007" sec-type="conclusions">
<title>Conclusions</title>
<p>We have developed fully glycosylated models of ACE2-Fc immunoadhesins with and without interactions to glycosylated SARS-CoV-2 spike protein fragments. Atomic resolution models can be used to help guide the development of ACE2 and/or ACE2-Fc therapeutics for COVID-19 and potentially other coronavirus borne diseases.</p>
<p>We found that glycosylations affects protein structure, and potentially ACE2/SpFr binding. It is not yet clear how important these differences are, but they must be treated carefully when designing ACE2-Fc variants. The work exhibited here provides a direct avenue for collaborations between experimental and computational researchers.</p>
<p>All models developed here are freely available for researchers and future COVID-19 related simulations. Simulations with a wider variety of glycosylations as well as for longer times are in progress and will be reported in the future. The open-source workflows and tools that have been generated for glycoprotein simulations will be useful for general simulations of glycosylated systems. We hope that glycosylation becomes a standard variable in protein molecular simulations in the near future.</p>
</sec>
<sec id="sec008">
<title>Supporting information</title>
<supplementary-material id="pone.0237295.s001" mimetype="application/zip" position="float" xlink:href="info:doi/10.1371/journal.pone.0237295.s001" xlink:type="simple">
<label>S1 File</label>
<caption>
<title>Supporting information contains all sequence definitions as well as additional analysis.</title>
<p>Also, all configurations discussed in this paper are available in pdb format both in supporting information as well as from the datadryad.org (<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.25338/B82G9B" xlink:type="simple">https://doi.org/10.25338/B82G9B</ext-link>). Software tools developed for this project are available on GitHub [<xref ref-type="bibr" rid="pone.0237295.ref045">45</xref>, <xref ref-type="bibr" rid="pone.0237295.ref047">47</xref>].</p>
<p>(ZIP)</p>
</caption>
</supplementary-material>
</sec>
</body>
<back>
<ack>
<p>We thank Priya Shah for stimulating discussions. Simulations were performed on the HPC1 computing cluster at UC Davis.</p>
</ack>
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