About: Insights on cross-species transmission of SARS-CoV-2 from structural modeling

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Insights on cross-species transmission of SARS-CoV-2 from structural modeling
Creator	Barrera-Vilarmau, Susana Kastritis, Panagiotis Levitt, Michael Rodrigues, João Mc, Teixeira Seckel,
Source	BioRxiv; Medline; PMC; WHO
abstract	Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the ongoing global pandemic that has infected more than 6 million people in more than 180 countries worldwide. Like other coronaviruses, SARS-CoV-2 is thought to have been transmitted to humans from wild animals. Given the scale and widespread geographical distribution of the current pandemic, the question emerges whether human-to-animal transmission is possible and if so, which animal species are most at risk. Here, we investigated the structural properties of several ACE2 orthologs bound to the SARS-CoV-2 spike protein. We found that species known not to be susceptible to SARS-CoV-2 infection have non-conservative mutations in several ACE2 amino acid residues that disrupt key polar and charged contacts with the viral spike protein. Our models also predict affinity-enhancing mutations that could be used to design ACE2 variants for therapeutic purposes. Finally, our study provides a blueprint for modeling viral-host protein interactions and highlights several important considerations when designing these computational studies and analyzing their results.
has issue date	2020-06-05(xsd:dateTime)
bibo:doi	10.1101/2020.06.05.136861
bibo:pmid	32577636
has license	cc-by-nc-nd
sha1sum (hex)	70bf28b1265023fa1f9d76fee22192da98111358
schema:url	https://doi.org/10.1101/2020.06.05.136861
resource representing a document's title	Insights on cross-species transmission of SARS-CoV-2 from structural modeling
has PubMed Central identifier	PMC7302186
has PubMed identifier	32577636
schema:publication	bioRxiv
resource representing a document's body	covid:70bf28b1265023fa1f9d76fee22192da98111358#body_text
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