Computational redesign of Beta-27 Fab with substantially better predicted binding affinity to the SARS-CoV-2 Omicron variant than human ACE2 receptor
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Computational redesign of Beta-27 Fab with substantially better predicted binding affinity to the SARS-CoV-2 Omicron variant than human ACE2 receptor ; volume:13 ; number:1 ; day:19 ; month:9 ; year:2023 ; pages:1-15 ; date:12.2023
Scientific reports ; 13, Heft 1 (19.9.2023), 1-15, 12.2023
- Creator
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Treewattanawong, Wantanee
Sitthiyotha, Thassanai
Chunsrivirot, Surasak
- Contributor
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SpringerLink (Online service)
- DOI
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10.1038/s41598-023-42442-1
- URN
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urn:nbn:de:101:1-2024020515423975948392
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:31 AM CEST
Data provider
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Associated
- Treewattanawong, Wantanee
- Sitthiyotha, Thassanai
- Chunsrivirot, Surasak
- SpringerLink (Online service)
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Next generation course redesign
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The agroecology of redesign
Compensatory epistasis maintains ACE2 affinity in SARS-CoV-2 Omicron BA.1
Structures of ACE2–SIT1 recognized by Omicron variants of SARS-CoV-2
Omicron sub-lineage BA.5 infection results in attenuated pathology in hACE2 transgenic mice
Signet-Redesign
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An ACE2 decoy can be administered by inhalation and potently targets omicron variants of SARS‐CoV ‐2
Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions
Qualitätsorientiertes Redesign von Dienstleistungen
Next generation course redesign
Redesign of Optimistic Methods