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Titel: Structural models of human ACE2 variants with SARS-CoV-2 Spike protein for structure-based drug design
Autor(en): Sorokina, Marija
Teixeira, João M. C.
Barrera-Vilarmau, Susana
Paschke, ReinhardIn der Gemeinsamen Normdatei der DNB nachschlagen
Papasotiriou, Ioannis
Rodrigues, João P. G. L. M.
Kastritis, Panagiotis L.In der Gemeinsamen Normdatei der DNB nachschlagen
Erscheinungsdatum: 2020
Art: Artikel
Sprache: Englisch
Zusammenfassung: Emergence of coronaviruses poses a threat to global health and economy. The current outbreak of SARS-CoV-2 has infected more than 28,000,000 people and killed more than 915,000. To date, there is no treatment for coronavirus infections, making the development of therapies to prevent future epidemics of paramount importance. To this end, we collected information regarding naturally-occurring variants of the Angiotensin-converting enzyme 2 (ACE2), an epithelial receptor that both SARS-CoV and SARS-CoV-2 use to enter the host cells. We built 242 structural models of variants of human ACE2 bound to the receptor binding domain (RBD) of the SARS-CoV-2 surface spike glycoprotein (S protein) and refined their interfaces with HADDOCK. Our dataset includes 140 variants of human ACE2 representing missense mutations found in genome-wide studies, 39 mutants with reported effects on the recognition of the RBD, and 63 predictions after computational alanine scanning mutagenesis of ACE2-RBD interface residues. This dataset will help accelerate the design of therapeutics against SARS-CoV-2, as well as contribute to prevention of possible future coronaviruses outbreaks.
URI: https://opendata.uni-halle.de//handle/1981185920/110770
http://dx.doi.org/10.25673/108815
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY 4.0) Creative Commons Namensnennung 4.0 International(CC BY 4.0) Creative Commons Namensnennung 4.0 International
Journal Titel: Scientific data
Verlag: Nature Publ. Group
Verlagsort: London
Band: 7
Originalveröffentlichung: 10.1038/s41597-020-00652-6
Seitenanfang: 1
Seitenende: 10
Enthalten in den Sammlungen:Open Access Publikationen der MLU

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